CN118243240B - Hot defect detection system and method for electrified cable - Google Patents
Hot defect detection system and method for electrified cable Download PDFInfo
- Publication number
- CN118243240B CN118243240B CN202410688453.1A CN202410688453A CN118243240B CN 118243240 B CN118243240 B CN 118243240B CN 202410688453 A CN202410688453 A CN 202410688453A CN 118243240 B CN118243240 B CN 118243240B
- Authority
- CN
- China
- Prior art keywords
- temperature
- data
- thermal
- coefficient
- cable
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000007547 defect Effects 0.000 title claims abstract description 165
- 238000001514 detection method Methods 0.000 title claims abstract description 93
- 238000000034 method Methods 0.000 title claims abstract description 65
- 238000001931 thermography Methods 0.000 claims abstract description 61
- 238000012545 processing Methods 0.000 claims abstract description 58
- 238000009826 distribution Methods 0.000 claims abstract description 56
- 238000004891 communication Methods 0.000 claims abstract description 53
- 238000012544 monitoring process Methods 0.000 claims abstract description 28
- 230000002159 abnormal effect Effects 0.000 claims description 102
- 230000008859 change Effects 0.000 claims description 83
- 238000012937 correction Methods 0.000 claims description 49
- 238000010586 diagram Methods 0.000 claims description 32
- 238000004422 calculation algorithm Methods 0.000 claims description 30
- 230000009467 reduction Effects 0.000 claims description 27
- 230000035945 sensitivity Effects 0.000 claims description 19
- 230000008569 process Effects 0.000 claims description 15
- 238000011156 evaluation Methods 0.000 claims description 11
- 230000000007 visual effect Effects 0.000 claims description 11
- 230000004044 response Effects 0.000 claims description 9
- 238000013507 mapping Methods 0.000 claims description 7
- 230000005856 abnormality Effects 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 6
- 230000010365 information processing Effects 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000009529 body temperature measurement Methods 0.000 claims description 4
- 230000003287 optical effect Effects 0.000 claims description 4
- 230000010354 integration Effects 0.000 claims description 3
- 238000012856 packing Methods 0.000 claims description 3
- 238000012896 Statistical algorithm Methods 0.000 claims description 2
- 238000004590 computer program Methods 0.000 description 7
- 238000012546 transfer Methods 0.000 description 6
- 238000013528 artificial neural network Methods 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 238000010801 machine learning Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000003860 storage Methods 0.000 description 5
- 230000006872 improvement Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 230000008447 perception Effects 0.000 description 4
- 238000005070 sampling Methods 0.000 description 4
- 229910010293 ceramic material Inorganic materials 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000032683 aging Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000003750 conditioning effect Effects 0.000 description 2
- 229920003020 cross-linked polyethylene Polymers 0.000 description 2
- 239000004703 cross-linked polyethylene Substances 0.000 description 2
- 230000002950 deficient Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000009413 insulation Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000011810 insulating material Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 239000010421 standard material Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/48—Thermography; Techniques using wholly visual means
- G01J5/485—Temperature profile
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/0096—Radiation pyrometry, e.g. infrared or optical thermometry for measuring wires, electrical contacts or electronic systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/02—Constructional details
- G01J5/03—Arrangements for indicating or recording specially adapted for radiation pyrometers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Computing Systems (AREA)
- Databases & Information Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Multimedia (AREA)
- Quality & Reliability (AREA)
- Radiation Pyrometers (AREA)
Abstract
The invention discloses a thermal defect detection system and a thermal defect detection method for a live cable. The hot defect detection system of this electrified cable includes: a temperature monitoring module; a data processing module; a thermal imaging module; and an alarm communication module. According to the invention, the temperature of the electrified cable in a preset time period is monitored in real time, the temperature signal is converted into the digital signal, then the digital signal is converted into the temperature data according to the temperature threshold method, the data is processed to obtain the first temperature data, then the thermal image of the electrified cable is generated according to the first temperature data to obtain a temperature distribution map, and finally the alarm signal is converted into the thermal defect information of the electrified cable through the alarm device and is output in a communication form when the specific position of the thermal defect of the electrified cable in the preset time period is detected, so that the thermal defect detection efficiency is improved, and the problem of low thermal defect detection efficiency in the prior art is solved.
Description
Technical Field
The invention relates to the technical field of thermal defect detection, in particular to a thermal defect detection system and method for an electrified cable.
Background
With the rapid development of the power industry, the cable is used as a main carrier for power transmission, and the safe operation of the cable is important for guaranteeing the stability of a power system. However, because the cable is in a working environment with high voltage and high current for a long time, thermal defects such as poor contact, insulation aging and the like are easy to occur, and the problems can lead to the rise of the temperature of the cable and even cause safety accidents such as fire disaster and the like. The traditional cable thermal defect detection method mainly relies on manual inspection and regular temperature measurement, and has the problems of low working efficiency, high omission ratio, incapability of real-time monitoring and the like. In addition, with development of infrared technology, nondestructive testing devices such as thermal infrared imagers are gradually applied to cable thermal defect detection, but these devices often only provide qualitative temperature distribution information, and cannot directly identify the type and severity of thermal defects. Therefore, it is important to develop a detection system and method capable of timely detecting and diagnosing cable thermal defects.
In the prior art, a thermal image is generated by detecting infrared energy radiated by the surface of an object and transmitted to a monitoring system in real time; triggering an alarm to collect cable temperature data and image data by setting a threshold or applying an anomaly detection algorithm; training a machine learning model for automatically identifying and classifying thermal defects; and automatically extracting key features according to the machine learning model, and judging whether the cable has thermal defects or not.
For example, bulletin numbers: the invention patent publication of CN113468841B discloses a distribution cable thermal defect detection method, a device, a computer device and a storage medium, comprising: determining section temperature units of the power distribution cable, and acquiring heat data of the two section temperature units and the environmental temperature of the environment where the section temperature units are located at the current moment; acquiring a first radial heat transfer parameter, a second radial heat transfer parameter and an axial heat transfer parameter between a conductor layer and a protection layer of a section temperature unit; and inputting the environmental temperature, the heat data, the first radial heat transfer parameter, the second radial heat transfer parameter and the axial heat transfer data into an equivalent thermal path model of the built section temperature unit, obtaining the temperature of the distribution points in the section temperature unit at the current moment, and determining the thermal defect level of the distribution cable.
For example, publication No.: the patent application of CN117454708A discloses a rail internal defect detection method based on a thermal perception neural network, which comprises the following steps: selecting known non-defective samples and defective samples as experimental objects, and performing experimental tests to obtain 3D ECPT experimental data and simulation data so as to construct an experimental simulation data set; the physical information neural network and the thermal information are coupled to construct a thermal perception neural network, and training and optimizing are carried out; and obtaining temperature time sequence data according to the experimental parameters in combination with a standard database, inputting the temperature time sequence data into a thermal perception neural network, and obtaining the internal temperature distribution of a standard sample for quantitative analysis.
However, in the process of implementing the technical scheme of the embodiment of the application, the application discovers that the above technology has at least the following technical problems:
In the prior art, the thermal infrared imager can only provide qualitative temperature information, so that the temperature information is not reported, the processing speed of data in the thermal defect detection process of the electrified cable is slow, and the problem of low thermal defect detection efficiency exists.
Disclosure of Invention
The embodiment of the application solves the problem of low thermal defect detection efficiency in the prior art by providing the thermal defect detection system and the thermal defect detection method for the electrified cable, and realizes the improvement of the thermal defect detection efficiency.
The embodiment of the application provides a thermal defect detection system of a live cable, which comprises the following components: the system comprises a temperature monitoring module, a data processing module, a thermal imaging module and an alarm communication module; the temperature monitoring module is used for monitoring the temperature of the electrified cable in a preset time period in real time and converting a temperature signal into a digital signal, wherein the temperature signal comprises measurement precision, response speed and a temperature resistant range; the data processing module is used for converting the digital signal into temperature data according to a temperature threshold value method and performing data processing to obtain first temperature data, and the temperature threshold value method is used for identifying thermal defects of the electrified cable in a preset time period under the condition of abnormal temperature change according to a temperature threshold value coefficient; the thermal imaging module is used for generating a thermal image of the electrified cable according to the first temperature data to obtain a temperature distribution map, the temperature distribution map is used for visualizing the temperature distribution condition of the surface of the electrified cable, and the thermal image is used for positioning the specific position of the thermal defect of the electrified cable in a preset time period; the alarm communication module is used for sending an alarm signal through the alarm device and communicating by combining communication equipment when detecting the specific position of the thermal defect of the electrified cable in the preset time period, and the communication equipment is used for converting the alarm signal into the thermal defect information of the electrified cable and outputting the thermal defect information in a communication mode.
Further, the data processing module comprises a data preprocessing unit, a feature extraction unit, an abnormality detection unit and a result evaluation unit; the data preprocessing unit: the method comprises the steps of converting a digital signal into temperature data according to a temperature threshold coefficient in a temperature threshold method, and performing primary processing, wherein the primary processing comprises noise removal, filling of missing values, error correction, data packing and data standardization, and the temperature threshold coefficient is an accuracy index for identifying thermal defects of the power-supplied cable in a preset time period under the condition of temperature change; the feature extraction unit: the method comprises the steps of extracting first key characteristic data from temperature data after primary processing, wherein the first key characteristic data comprises first temperature change data, first thermal gradient data and first abnormal temperature peak value data; the abnormality detection unit: the method comprises the steps of detecting thermal defects according to first key characteristic data and combining an anomaly detection algorithm to obtain first temperature data, wherein the anomaly detection algorithm comprises a temperature threshold detection algorithm, a temperature measurement statistical algorithm and a thermal defect learning algorithm; the result evaluation unit: and the abnormal detection algorithm is used for evaluating the detection result of the thermal defect according to the first temperature data and adjusting the abnormal detection algorithm according to the evaluation result.
Further, the thermal imaging module comprises a thermal image generating unit, an image acquisition unit, an image processing unit and a temperature mapping unit; the thermal image generation unit: the method comprises the steps of generating a thermal image of a power-on cable in a preset time period according to first temperature data to obtain a temperature distribution diagram, and obtaining the temperature change condition in the temperature distribution diagram according to a thermal imaging analysis method; the image acquisition unit: the temperature change condition in the temperature distribution diagram is converted into a second digital signal, and the second digital signal is used for displaying the temperature of the surface of the charged cable in the temperature distribution diagram; the image processing unit: the second processing unit is used for carrying out secondary processing on the second digital signal to extract second key characteristic data and adjust a thermal image, wherein the secondary processing unit comprises image enhancement and temperature calibration, and the second key characteristic data comprises second temperature change data, second thermal gradient data and second abnormal temperature peak value data; the temperature mapping unit: the method is used for corresponding the pixel value in the adjusted thermal image to the actual temperature value according to the thermal imaging coefficient and generating a temperature distribution map, wherein the thermal imaging coefficient is a sensitivity index of micro temperature coefficient change in the adjusted thermal image, and the micro temperature coefficient is an accuracy index of converting the pixel value in the thermal image into the actual temperature value.
Further, the alarm communication module comprises an alarm triggering unit, an alarm signal generating unit, a communication interface unit and an information formatting unit; the alarm triggering unit is used for: is used for judging whether to trigger the alarm device according to the abnormal state of the hot cable in the preset time period provided by the data processing module and the abnormal temperature reduction coefficient, the abnormal temperature reduction coefficient is the influence degree of converting the pixel value in the thermal image into the actual temperature value; the alarm signal generating unit: the alarm device is used for generating corresponding alarm signals according to the triggering result of the alarm device so as to display the specific position of the thermal defect of the electrified cable in a preset time period, wherein the alarm signals comprise sound, optical signals and electric signals; the communication interface unit: for transmitting the alarm signal into the communication device to obtain a communication signal; the information formatting unit: the communication signal is formatted into a preset format to obtain alarm data, wherein the alarm data comprises alarm time, alarm level, alarm type and thermal image data, and the thermal image data is used for reflecting the thermal defect state of the electrified cable in a preset time period.
Further, the specific process of converting the temperature signal into the digital signal is as follows: receiving a temperature signal acquired by a temperature sensor through a signal acquisition card and monitoring in real time; and converting the temperature signal into visual image information according to the real-time monitoring result and carrying out information processing to obtain a digital signal, wherein the information processing represents converting the visual image information into the digital signal according to the abnormal temperature reduction coefficient.
Further, the temperature threshold coefficient is calculated using the following formula:
in which, in the process, For the number of the preset time period,，For the total number of preset time periods,Represent the firstA temperature threshold coefficient for a predetermined period of time,Is a natural constant which is used for the production of the high-temperature-resistant ceramic material,Representing a reference deviation of the base temperature value from the actual temperature value,A value of the reference temperature is indicated,Represent the firstThe actual temperature value for a predetermined period of time,Representing the weight of the actual temperature value relative to the temperature threshold coefficient,Indicating that the maximum temperature allows for a reference deviation,Indicating the maximum temperature reference deviation of the temperature,Represent the firstMaximum temperature deviation for a preset period of time,The weight representing the maximum temperature deviation with respect to the temperature threshold coefficient,Indicating that the rate of change of temperature allows for a reference deviation,Indicating the reference rate of change of temperature,Represent the firstThe rate of temperature change for a predetermined period of time,The weight of the temperature change rate with respect to the temperature threshold coefficient is expressed,The indication duration allows a reference threshold value,A duration reference threshold value is indicated,Represent the firstA duration threshold for a predetermined period of time,A weight representing the duration threshold relative to the temperature threshold coefficient; the maximum temperature deviation is the maximum deviation value of the surface temperature of the electrified cable relative to a reference temperature value, the temperature change rate is the change rate of the surface temperature of the electrified cable in unit time, and the duration threshold is the reference duration of abnormal temperature change of the surface of the electrified cable.
Further, the specific acquisition method of the thermal imaging coefficient comprises the following steps: acquiring a thermal imaging coefficient total correction factor and a thermal imaging total coefficient according to the first key feature data and the second key feature data, wherein the thermal imaging coefficient total correction factor comprises a first correction factor, a second correction factor, a third correction factor and a fourth correction factor, the thermal imaging total coefficient comprises a temperature change data coefficient, a thermal gradient data coefficient and an abnormal temperature peak data coefficient, the temperature change data coefficient is the product of relative deviation of temperature change data and the second correction factor, the relative deviation of temperature change data is the product of the absolute value of the difference between the second temperature change data and the first temperature change data and the corresponding reference deviation, the thermal gradient data coefficient is the product of the relative deviation of the thermal gradient data and the third correction factor, the relative deviation of the thermal gradient is the product of the absolute value of the difference between the second thermal gradient data and the first thermal gradient data and the corresponding reference deviation, the abnormal temperature peak data coefficient is the product of relative deviation of abnormal temperature peak data and the fourth correction factor, and the abnormal temperature peak data is the product of the absolute value of the difference between the second abnormal temperature peak data and the first abnormal temperature peak data and the corresponding reference deviation; and combining the obtained thermal imaging total coefficient and the thermal imaging coefficient total correction factor to obtain a thermal imaging coefficient, wherein the thermal imaging coefficient is the product of the thermal imaging total coefficient and the first correction factor.
Further, the micro temperature coefficient is calculated by the following formula:
in which, in the process, Represent the firstThe micro temperature coefficient for a preset period of time,A reference deviation representing an abnormal temperature reduction coefficient,Represents the reference abnormal temperature reduction coefficient,Represent the firstAbnormal temperature reduction coefficients for a predetermined period of time,The weight of the abnormal temperature reduction coefficient with respect to the micro temperature coefficient is expressed,A reference deviation of the temperature sensitivity coefficient is indicated,Indicating the sensitivity coefficient of the reference temperature,Represent the firstThe temperature sensitivity coefficient for a predetermined period of time,Representing the weight of the temperature sensitivity coefficient relative to the micro temperature coefficient,A reference deviation representing the temperature linearity coefficient,Representing the coefficient of linearity of the reference temperature,Represent the firstA temperature linearity coefficient for a preset period of time,A weight representing a temperature linearity coefficient relative to a micro temperature coefficient; the abnormal temperature reduction coefficient is the influence degree of converting a pixel value in the thermal image into an actual temperature value, the temperature sensitivity coefficient is the response degree of converting the pixel value in the thermal image into the actual temperature value, and the temperature linearity coefficient is the linear relation degree between the pixel value in the thermal image and the actual temperature value.
Further, the specific step of acquiring the first temperature data in the anomaly detection unit includes: extracting characteristic temperature data from first key characteristic data, wherein the characteristic temperature data comprises temperature space distribution data, temperature linear change trend data and operation data of a live cable in a preset environment in a temperature distribution map; selecting a corresponding abnormal detection algorithm to detect the extracted characteristic temperature data, and identifying an abnormal temperature region according to a detection result to obtain a thermal defect region; and acquiring thermal defect temperature data from the thermal defect area and performing thermal defect treatment to obtain first temperature data, wherein the thermal defect data comprise an abnormal temperature maximum value, abnormal environment data and abnormal operation data of the power cable in a preset time period, and the thermal defect treatment is used for performing data integration and data classification on the thermal defect data in the thermal defect area.
The embodiment of the application provides a thermal defect detection method of an electrified cable, which comprises the following steps of: monitoring the temperature of the electrified cable in a preset time period in real time and converting a temperature signal into a digital signal, wherein the temperature signal comprises measurement precision, response speed and a temperature resistant range; converting the digital signal into temperature data according to a temperature threshold method and performing data processing to obtain first temperature data, wherein the temperature threshold method is used for identifying thermal defects of the electrified cable in a preset time period under the condition of abnormal temperature change according to a temperature threshold coefficient; generating a thermal image of the electrified cable according to the first temperature data to obtain a temperature distribution map, wherein the temperature distribution map is used for visualizing the temperature distribution condition of the surface of the electrified cable, and the thermal image is used for positioning the specific position of the thermal defect of the electrified cable in a preset time period; when the specific position of the thermal defect of the electrified cable in the preset time period is detected, an alarm signal is sent out through an alarm device and is communicated by combining communication equipment, and the communication equipment is used for converting the alarm signal into the thermal defect information of the electrified cable and outputting the thermal defect information in a communication mode.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. The temperature of the electrified cable in a preset time period is monitored in real time, a temperature signal is converted into a digital signal, then the digital signal is converted into temperature data according to a temperature threshold method, the data is processed to obtain first temperature data, a thermal image of the electrified cable is generated according to the first temperature data to obtain a temperature distribution map, and finally the specific position of the thermal defect of the electrified cable in the preset time period is detected, an alarm signal is sent out through an alarm device and communication is carried out by combining communication equipment, so that more accurate detection of the thermal defect is realized, further the improvement of the thermal defect detection efficiency is realized, and the problem of low thermal defect detection efficiency in the prior art is effectively solved;
2. the temperature signal acquired by the temperature sensor is received by the signal acquisition card and monitored in real time, then the temperature signal is converted into visual image information according to the real-time monitoring result, and finally the visual image information is converted into a digital signal according to the abnormal temperature reduction coefficient, so that more accurate acquisition of the digital signal is realized, and further more accurate monitoring of the temperature signal is realized;
3. The characteristic temperature data is extracted from the first key characteristic data, the corresponding abnormal detection algorithm is selected to detect the extracted characteristic temperature data, then an abnormal temperature region is identified according to the detection result to obtain a thermal defect region, finally the thermal defect temperature data is obtained from the thermal defect region and thermal defect processing is carried out to obtain the first temperature data, so that the accurate acquisition of the first temperature data is realized, and further, the more accurate detection of the characteristic temperature data is realized.
Drawings
Fig. 1 is a schematic structural diagram of a thermal defect detecting system for an electrified cable according to an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating a data processing module in a thermal defect detecting system for an electrified cable according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of a thermal imaging module in a thermal defect detection system for an electrified cable according to an embodiment of the present application;
FIG. 4 is a flowchart of acquiring first temperature data according to an embodiment of the present application;
FIG. 5 is a flowchart of a method for detecting thermal defects of an electrified cable according to an embodiment of the present application;
fig. 6 is a temperature distribution diagram of a cable according to an embodiment of the present application.
Detailed Description
According to the hot defect detection system and method for the live cable, the problem of low hot defect detection efficiency in the prior art is solved, the temperature of the live cable in a preset time period is monitored in real time through the temperature monitoring module, a temperature signal is converted into a digital signal, then the digital signal is converted into temperature data according to a temperature threshold coefficient through the data processing module, the temperature data are processed once, first key characteristic data are extracted, meanwhile, the hot defect is detected through an anomaly detection algorithm to obtain first temperature data, a hot image of the live cable in the preset time period is generated according to the first temperature data to obtain a temperature distribution diagram, second key characteristic data are obtained through secondary processing of a second digital signal converted from the temperature change condition in the temperature distribution diagram, meanwhile, the temperature distribution diagram is generated according to a thermal imaging coefficient, finally the specific position of the hot defect of the live cable in the preset time period is detected through the alarm communication module, the alarm signal is converted into hot defect information of the live cable through the alarm device, and meanwhile, the hot defect information is output in a communication mode, and improvement of the hot defect detection efficiency is achieved.
The technical scheme in the embodiment of the application aims to solve the problem of low thermal defect detection efficiency, and the general thought is as follows:
the temperature of the electrified cable in the preset time period is monitored in real time, the temperature signal is converted into a digital signal, then the thermal defect of the electrified cable in the preset time period under the condition of abnormal temperature change is identified according to the digital signal and by combining a temperature threshold coefficient, the specific position of the thermal defect of the electrified cable in the preset time period is detected, and finally the alarm signal is converted into the thermal defect information of the electrified cable through the alarm device and is output in a communication mode, so that the effect of improving the thermal defect detection efficiency is achieved.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
As shown in fig. 1, a schematic structural diagram of a thermal defect detection system for an electrified cable according to an embodiment of the present application is shown, where the thermal defect detection system for an electrified cable according to an embodiment of the present application includes: the system comprises a temperature monitoring module, a data processing module, a thermal imaging module and an alarm communication module; the temperature monitoring module is used for monitoring the temperature of the electrified cable in a preset time period in real time and converting a temperature signal into a digital signal, wherein the temperature signal comprises measurement precision, response speed and a temperature resistant range; the data processing module is used for converting the digital signal into temperature data according to a temperature threshold value method and carrying out data processing to obtain first temperature data, and the temperature threshold value method is used for identifying thermal defects of the electrified cable in a preset time period under the condition of abnormal temperature change according to a temperature threshold value coefficient; the thermal imaging module is used for generating a thermal image of the electrified cable according to the first temperature data to obtain a temperature distribution diagram, the temperature distribution diagram is used for visualizing the temperature distribution condition of the surface of the electrified cable, and the thermal image is used for positioning the specific position of the thermal defect of the electrified cable in a preset time period; the alarm communication module is used for sending an alarm signal through the alarm device and communicating by combining communication equipment when detecting the specific position of the thermal defect of the electrified cable in the preset time period, and the communication equipment is used for converting the alarm signal into the thermal defect information of the electrified cable and outputting the thermal defect information in a communication mode.
In this embodiment, the core of the temperature threshold method is to identify abnormal temperature changes according to a preset temperature threshold coefficient, and set the abnormal temperature changes based on the normal operation temperature and the allowable maximum temperature of the power cable in a preset time period, wherein the preset temperature threshold coefficient is generally obtained by the following method: the long-term allowable working temperature, overload temperature and short-circuit temperature of the crosslinked polyethylene insulated cable are determined according to the manufacturing standard and insulating material of the cable, for example, the long-term allowable working temperature of the crosslinked polyethylene insulated cable is generally 90 ℃, the short-time overload maximum temperature is not more than 130 ℃, the short-time overload maximum temperature is not more than 250 ℃ (the maximum duration time is not more than 5 seconds), and the standard values can be used as reference bases for setting temperature thresholds so as to determine preset temperature threshold coefficients; in practical application, the temperature change of the cable is monitored in real time, the temperature data is processed and analyzed by utilizing an intelligent algorithm, the temperature threshold coefficient can be dynamically adjusted to adapt to the change of the operation condition of the cable, when the temperature is detected to exceed the preset threshold, the thermal defect detection system considers that the cable has thermal defects, the abnormal temperature data are marked as first temperature data, the thermal defects are used for describing the abnormal mode of the thermal state of the live cable, the potential risk of the live cable caused by the thermal defects is reduced by the cooperative work of the temperature monitoring module, the data processing module, the thermal imaging module and the alarm communication module, the improvement of the thermal defect detection efficiency is realized, and as shown in fig. 6, the specific acquisition steps of the thermal distribution map are as follows: converting the processed temperature data into a visual image (i.e., a thermal image), the thermal image typically representing the temperature distribution in color coding, the higher the temperature, the warmer the color (e.g., white, orange), the lower the temperature, the cooler the color (e.g., blue, purple); through color comparison, temperature differences of different areas on the surface of the cable can be intuitively observed, so that potential faults and problems in the cable, such as overheating of joints, insulation aging, overload of the cable and the like, can be rapidly identified.
Further, as shown in fig. 2, a schematic structural diagram of a data processing module in a hot defect detection system for an electrified cable according to an embodiment of the present application is shown, where the data processing module includes a data preprocessing unit, a feature extraction unit, an anomaly detection unit, and a result evaluation unit; a data preprocessing unit: the method comprises the steps of converting a digital signal into temperature data according to a temperature threshold coefficient in a temperature threshold method, and performing primary processing, wherein the primary processing comprises noise removal, missing value filling, error correction, data packing and data standardization, and the temperature threshold coefficient is an accuracy index for identifying the thermal defect of the electrified cable in a preset time period under the condition of temperature change; feature extraction unit: the method comprises the steps of extracting first key characteristic data from temperature data after primary processing, wherein the first key characteristic data comprises first temperature change data, first thermal gradient data and first abnormal temperature peak value data; an abnormality detection unit: the method comprises the steps of detecting thermal defects according to first key characteristic data and combining an anomaly detection algorithm to obtain first temperature data, wherein the anomaly detection algorithm comprises a temperature threshold detection algorithm, a temperature measurement statistics algorithm and a thermal defect learning algorithm; a result evaluation unit: and the abnormal detection algorithm is used for evaluating the detection result of the thermal defect according to the first temperature data and adjusting the abnormal detection algorithm according to the evaluation result.
In this embodiment, the temperature change data is the rate and trend of temperature change, the thermal gradient data is the difference of temperatures at different positions or time points, and the abnormal temperature peak data is the abnormal high and low temperature values of the potential thermal defect; the evaluation of the thermal defect detection result by the result evaluation unit generally involves comparing the first temperature data with the actual thermal defect situation, calculating the accuracy, recall rate and F1 fraction, wherein the F1 fraction is generally used for evaluating the accuracy of thermal defect detection in the thermal defect detection process of the live cable, and a higher F1 fraction generally represents higher accuracy in comparing the first temperature data with the actual thermal defect situation.
Further, as shown in fig. 3, a schematic structural diagram of a thermal imaging module in a thermal defect detection system for an electrified cable according to an embodiment of the present application is shown, where the thermal imaging module includes a thermal image generating unit, an image collecting unit, an image processing unit and a temperature mapping unit; a thermal image generation unit: the method comprises the steps of generating a thermal image of a power-on cable in a preset time period according to first temperature data to obtain a temperature distribution diagram, and obtaining the temperature change condition in the temperature distribution diagram according to a thermal imaging analysis method; an image acquisition unit: the temperature change condition in the temperature distribution diagram is converted into a second digital signal, and the second digital signal is used for displaying the temperature of the surface of the charged cable in the temperature distribution diagram; an image processing unit: the second processing unit is used for carrying out secondary processing on the second digital signal to extract second key characteristic data and adjust a thermal image, wherein the secondary processing comprises image enhancement and temperature calibration, and the second key characteristic data comprises second temperature change data, second thermal gradient data and second abnormal temperature peak value data; temperature mapping unit: the method is used for generating a temperature distribution map by corresponding the pixel value in the adjusted thermal image to the actual temperature value according to the thermal imaging coefficient, wherein the thermal imaging coefficient is a sensitivity index of the change of the micro temperature coefficient in the adjusted thermal image, and the micro temperature coefficient is an accuracy index of the conversion of the pixel value in the thermal image into the actual temperature value.
In this embodiment, the image acquisition unit is responsible for converting the temperature change condition in the temperature distribution map into a second digital signal, and this process is implemented by an analog-to-digital converter (ADC), which converts a continuous analog signal into a discrete second digital signal, so that the computer can analyze and display the continuous analog signal, and the converted second digital signal can accurately reflect the temperature information on the surface of the charged cable; through temperature mapping, the temperature change in the thermal image can be quantized into an actual temperature value, so that operators can more intuitively and accurately know the temperature condition of the surface of the cable, and more accurate acquisition of the temperature condition of the surface of the electrified cable is realized.
Further, the alarm communication module comprises an alarm triggering unit, an alarm signal generating unit, a communication interface unit and an information formatting unit; an alarm triggering unit: is used for judging whether to trigger the alarm device according to the abnormal state of the hot cable in the preset time period provided by the data processing module and the abnormal temperature reduction coefficient, the abnormal temperature reduction coefficient is the influence degree of converting the pixel value in the thermal image into the actual temperature value; an alarm signal generation unit: the alarm device is used for generating corresponding alarm signals according to the triggering result of the alarm device so as to display the specific position of the thermal defect of the electrified cable in a preset time period, wherein the alarm signals comprise sound, optical signals and electric signals; a communication interface unit: for transmitting the alarm signal into the communication device to obtain a communication signal; an information formatting unit: the communication signal is formatted into a preset format to obtain alarm data, and the alarm data comprises alarm time, alarm level, alarm type and thermal image data, wherein the thermal image data is used for reflecting the thermal defect state of the electrified cable in a preset time period.
In this embodiment, the alarm triggering unit is a core part of the alarm communication module, and judges whether the alarm device needs to be triggered according to the abnormal information of the thermal state of the power cable in the preset time period provided by the data processing module, when the abnormal temperature exceeds the preset threshold value and the abnormal temperature reduction coefficient reaches a certain degree, the alarm triggering unit can judge the thermal defect state and start the alarm program, and the alarm communication module is beneficial to improving the operation safety and stability of the power system; the alarm data in the information formatting unit specifically comprises specific time for triggering an alarm, severity of the thermal defect and source of the thermal defect, and through the formatted alarm data, related personnel can comprehensively know the condition of the thermal defect and make corresponding processing decisions, so that timely alarm and information transmission of the thermal defect of the electrified cable are realized.
Further, the specific process of converting the temperature signal into the digital signal is as follows: receiving a temperature signal acquired by a temperature sensor through a signal acquisition card and monitoring in real time; and converting the temperature signal into visual image information according to the real-time monitoring result and carrying out information processing to obtain a digital signal, wherein the information processing represents converting the visual image information into the digital signal according to the abnormal temperature reduction coefficient.
In this embodiment, the temperature sensor is attached to the surface of the electrified cable to obtain a temperature signal in a preset time period, and the signal acquisition card can capture the change condition of the temperature signal according to the sampling frequency, the sampling resolution and the signal conditioning parameter, wherein the sampling frequency determines the number of data points collected per second, the sampling resolution determines the precision of each data point, the signal conditioning parameter comprises amplifying and filtering operations to optimize the quality of the temperature signal, ensure that the analog temperature signal obtained from the temperature sensor can be accurately and reliably converted into a digital signal, and realize more accurate acquisition of the surface temperature of the electrified cable.
Further, the temperature threshold coefficient can be obtained through a more accurate calculation method besides being obtained through a machine learning algorithm:
in which, in the process, For the number of the preset time period,，For the total number of preset time periods,Represent the firstA temperature threshold coefficient for a predetermined period of time,Is a natural constant which is used for the production of the high-temperature-resistant ceramic material,Representing a reference deviation of the base temperature value from the actual temperature value,A value of the reference temperature is indicated,Represent the firstThe actual temperature value for a predetermined period of time,Representing the weight of the actual temperature value relative to the temperature threshold coefficient,Indicating that the maximum temperature allows for a reference deviation,Indicating the maximum temperature reference deviation of the temperature,Represent the firstMaximum temperature deviation for a preset period of time,The weight representing the maximum temperature deviation with respect to the temperature threshold coefficient,Indicating that the rate of change of temperature allows for a reference deviation,Indicating the reference rate of change of temperature,Represent the firstThe rate of temperature change for a predetermined period of time,The weight of the temperature change rate with respect to the temperature threshold coefficient is expressed,The indication duration allows a reference threshold value,A duration reference threshold value is indicated,Represent the firstA duration threshold for a predetermined period of time,A weight representing the duration threshold relative to the temperature threshold coefficient; the maximum temperature deviation is the maximum deviation value of the surface temperature of the electrified cable relative to the reference temperature value, the temperature change rate is the change rate of the surface temperature of the electrified cable in unit time, and the duration threshold is the reference duration of abnormal temperature change of the surface of the electrified cable.
In this embodiment, the reference temperature value is generally determined based on the design specification, the operation environment and the historical data of the live cable, the rapid change of the surface temperature of the live cable can cause the cable surface to be interfered by external factors, the longer the duration of the abnormal temperature change is, the longer the continuous thermal defect problem is, the temperature state of the surface of the live cable can be comprehensively evaluated by calculating the temperature threshold coefficient, and whether an alarm device is triggered or further analysis and processing are performed can be judged according to the set threshold value, so that the potential thermal defect problem can be found timely, and the stability in the thermal defect detection process is improved.
Further, the specific acquisition method of the thermal imaging coefficient comprises the following steps: acquiring a thermal imaging coefficient total correction factor and a thermal imaging total coefficient according to the first key feature data and the second key feature data, wherein the thermal imaging coefficient total correction factor comprises a first correction factor, a second correction factor, a third correction factor and a fourth correction factor, the thermal imaging total coefficient comprises a temperature change data coefficient, a thermal gradient data coefficient and an abnormal temperature peak data coefficient, the temperature change data coefficient is the product of the relative deviation of the temperature change data and the second correction factor, the relative deviation of the temperature change data is the ratio of the absolute value of the difference between the second temperature change data and the first temperature change data to the corresponding reference deviation, the thermal gradient data coefficient is the product of the relative deviation of the thermal gradient data and the third correction factor, the relative deviation of the thermal gradient is the ratio of the absolute value of the difference between the second thermal gradient data and the first thermal gradient data to the corresponding reference deviation, the abnormal temperature peak data coefficient is the product of the relative deviation of the abnormal temperature peak data and the fourth correction factor, and the relative deviation of the abnormal temperature peak data is the ratio of the absolute value of the difference between the second abnormal temperature peak data and the first abnormal temperature peak data to the corresponding reference deviation; and combining the obtained thermal imaging total coefficient and the thermal imaging coefficient total correction factor to obtain a thermal imaging coefficient, wherein the thermal imaging coefficient is the product of the thermal imaging total coefficient and the first correction factor.
In this embodiment, the thermal imaging coefficient may be obtained by a more accurate calculation method in addition to the machine learning algorithm:
in which, in the process, For the number of the preset time period,，For the total number of the preset time period,As a result of the first correction factor,Represent the firstThermal imaging coefficients for a predetermined period of time,Is a natural constant which is used for the production of the high-temperature-resistant ceramic material,A reference deviation of the temperature change data is represented,Represent the firstFirst temperature change data for a preset period of time,Represent the firstSecond temperature change data for a preset period of time,A second correction factor is indicated and is indicated,Representing a reference deviation of the thermal gradient data,Represent the firstFirst thermal gradient data for a predetermined period of time,Represent the firstSecond thermal gradient data for a predetermined period of time,A third correction factor is indicated and is indicated,A reference deviation representing the abnormal temperature peak data,Represent the firstFirst abnormal temperature peak data for a preset period of time,Represent the firstSecond abnormal temperature peak data for a preset period of time,Representing a fourth correction factor; the total correction factors of the thermal imaging coefficients consist of a first correction factor, a second correction factor, a third correction factor and a fourth correction factor, the four correction factors are used for adjusting the accuracy and precision of thermal imaging data, the specific calculation modes of the correction factors in the actual calculation process can be based on an empirical formula, historical data and equipment performance parameters, the thermal imaging data are comprehensively evaluated according to the total thermal imaging coefficients to determine whether further correction or adjustment is needed, and the thermal imaging data can be correspondingly corrected according to the specific influence degree of the correction factors, so that the more accurate acquisition of the thermal imaging coefficients is realized through the accuracy and the reliability of the data.
Further, the micro temperature coefficient can be obtained through a more accurate calculation method besides being obtained through a machine learning algorithm:
in which, in the process, Represent the firstThe micro temperature coefficient for a preset period of time,A reference deviation representing an abnormal temperature reduction coefficient,Represents the reference abnormal temperature reduction coefficient,Represent the firstAbnormal temperature reduction coefficients for a predetermined period of time,The weight of the abnormal temperature reduction coefficient with respect to the micro temperature coefficient is expressed,A reference deviation of the temperature sensitivity coefficient is indicated,Indicating the sensitivity coefficient of the reference temperature,Represent the firstThe temperature sensitivity coefficient for a predetermined period of time,Representing the weight of the temperature sensitivity coefficient relative to the micro temperature coefficient,A reference deviation representing the temperature linearity coefficient,Representing the coefficient of linearity of the reference temperature,Represent the firstA temperature linearity coefficient for a preset period of time,A weight representing a temperature linearity coefficient relative to a micro temperature coefficient; the abnormal temperature shrinkage coefficient is the influence degree of converting a pixel value in a thermal image into an actual temperature value, the temperature sensitivity coefficient is the response degree of converting the pixel value in the thermal image into the actual temperature value, and the temperature linearity coefficient is the linear relation degree between the pixel value in the thermal image and the actual temperature value.
In this embodiment, the abnormal temperature reduction coefficient, the temperature sensitivity coefficient and the temperature linearity coefficient describe how these three coefficients affect the micro temperature coefficient, and the micro temperature coefficient is specifically a tiny change of the surface temperature of the live cable in a preset period of time, in practical application, the micro temperature coefficient may also be written in a function form, and how the three coefficients interact with each other and how they affect the micro temperature coefficient specifically, which is beneficial to improving accuracy of acquiring the micro temperature coefficient, and realizing more accurate detection of the surface temperature of the live cable.
Further, as shown in fig. 4, in a flowchart for acquiring first temperature data provided in an embodiment of the present application, the specific steps for acquiring the first temperature data in the anomaly detection unit include: extracting characteristic temperature data from the first key characteristic data, wherein the characteristic temperature data comprises temperature space distribution data, temperature linear change trend data and operation data of the electrified cable in a preset environment in a temperature distribution map; selecting a corresponding abnormal detection algorithm to detect the extracted characteristic temperature data, and identifying an abnormal temperature region according to a detection result to obtain a thermal defect region; and acquiring thermal defect temperature data from the thermal defect area and performing thermal defect treatment to obtain first temperature data, wherein the thermal defect data comprises an abnormal temperature maximum value, abnormal environment data and abnormal operation data of the electrified cable in a preset time period, and the thermal defect treatment is used for performing data integration and data classification on the thermal defect data in the thermal defect area.
In this embodiment, the operation data of the live cable in the preset environment is collected, which may include the ambient temperature, humidity and cable load, and the abnormal operation data of the live cable also includes the fluctuation condition of voltage and current; the first temperature data is a comprehensive index, reflects the severity of thermal defects and the influence degree on the operation of the cable, has important significance for evaluating the health state of the cable, predicting potential faults and formulating maintenance strategies, and achieves more accurate acquisition of the first temperature data.
As shown in fig. 5, a flowchart of a method for detecting a thermal defect of a live cable according to an embodiment of the present application is shown, where the method for detecting a thermal defect of a live cable according to an embodiment of the present application includes the following steps: monitoring the temperature of the electrified cable in a preset time period in real time, and converting a temperature signal into a digital signal, wherein the temperature signal comprises measurement accuracy, response speed and a temperature resistant range; converting the digital signal into temperature data according to a temperature threshold method and performing data processing to obtain first temperature data, wherein the temperature threshold method is used for identifying thermal defects of the electrified cable in a preset time period under the condition of abnormal temperature change according to a temperature threshold coefficient; generating a thermal image of the electrified cable according to the first temperature data to obtain a temperature distribution diagram, wherein the temperature distribution diagram is used for visualizing the temperature distribution condition of the surface of the electrified cable, and the thermal image is used for positioning the specific position of the thermal defect of the electrified cable in a preset time period; when the specific position of the thermal defect of the electrified cable in the preset time period is detected, an alarm signal is sent out through the alarm device and is communicated by combining with communication equipment, and the communication equipment is used for converting the alarm signal into the thermal defect information of the electrified cable and outputting the thermal defect information in a communication mode.
In this embodiment, the temperature threshold method is a method for judging whether the abnormal temperature change exists in the live cable in the preset time period based on the preset temperature threshold, and the method can identify the temperature change beyond the normal range, and simultaneously, when the live cable is positioned to a specific position of the thermal defect, the communication equipment is combined to timely transmit alarm information to related personnel or a live cable thermal defect detection system so as to perform remote monitoring and fault processing.
The technical scheme provided by the embodiment of the application at least has the following technical effects or advantages: relative to the bulletin number: the distribution cable thermal defect detection method, the distribution cable thermal defect detection device, the computer equipment and the storage medium disclosed by the patent publication of CN113468841B are characterized in that the temperature signals acquired by the temperature sensor are received through the signal acquisition card and monitored in real time, then the temperature signals are converted into visual image information according to the real-time monitoring result, and finally the visual image information is converted into digital signals according to the abnormal temperature reduction coefficient, so that more accurate acquisition of the digital signals is realized, and further more accurate monitoring of the temperature signals is realized; relative to publication No.: according to the rail internal defect detection method based on the thermal perception neural network disclosed by the patent application CN117454708A, the embodiment of the application extracts the characteristic temperature data from the first key characteristic data, selects the corresponding abnormal detection algorithm to detect the extracted characteristic temperature data, then identifies the abnormal temperature region according to the detection result to acquire the thermal defect region, finally acquires the thermal defect temperature data from the thermal defect region and carries out thermal defect treatment to acquire the first temperature data, so that the accurate acquisition of the first temperature data is realized, and further the more accurate detection of the characteristic temperature data is realized.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of systems, apparatuses (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. The hot defect detection system of the electrified cable is characterized by comprising a temperature monitoring module, a data processing module, a thermal imaging module and an alarm communication module;
The temperature monitoring module is used for monitoring the temperature of the electrified cable in a preset time period in real time and converting a temperature signal into a digital signal, wherein the temperature signal comprises measurement precision, response speed and a temperature resistant range;
the data processing module is used for converting the digital signal into temperature data according to a temperature threshold method and performing data processing to obtain first temperature data, and the temperature threshold method is used for identifying thermal defects of the electrified cable in a preset time period under the condition of abnormal temperature change;
The thermal imaging module is used for generating a thermal image of the electrified cable according to the first temperature data to obtain a temperature distribution map, the temperature distribution map is used for visualizing the temperature distribution condition of the surface of the electrified cable, and the thermal image is used for positioning the specific position of the thermal defect of the electrified cable in a preset time period;
the alarm communication module is used for sending an alarm signal through the alarm device and communicating by combining communication equipment when detecting the specific position of the thermal defect of the electrified cable in a preset time period, and the communication equipment is used for converting the alarm signal into the thermal defect information of the electrified cable and outputting the thermal defect information in a communication form;
The data processing module comprises a data preprocessing unit, a feature extraction unit, an abnormality detection unit and a result evaluation unit;
The data preprocessing unit: the method comprises the steps of converting a digital signal into temperature data according to a temperature threshold coefficient in a temperature threshold method, and performing primary processing, wherein the primary processing comprises noise removal, filling of missing values, error correction, data packing and data standardization, and the temperature threshold coefficient is an accuracy index for identifying thermal defects of the power-supplied cable in a preset time period under the condition of temperature change;
The feature extraction unit: the method comprises the steps of extracting first key characteristic data from temperature data after primary processing, wherein the first key characteristic data comprises first temperature change data, first thermal gradient data and first abnormal temperature peak value data;
The abnormality detection unit: the method comprises the steps of detecting thermal defects according to first key characteristic data and combining an anomaly detection algorithm to obtain first temperature data, wherein the anomaly detection algorithm comprises a temperature threshold detection algorithm, a temperature measurement statistical algorithm and a thermal defect learning algorithm;
The result evaluation unit: the abnormal detection algorithm is used for evaluating the detection result of the thermal defect according to the first temperature data and adjusting the abnormal detection algorithm according to the evaluation result;
The temperature threshold coefficient is calculated using the following formula:
，
Where g is the number of the preset time period, g=1, 2,..2, K is the total number of the preset time periods, ψ g represents the temperature threshold coefficient of the g-th preset time period, e is a natural constant, Δa represents the reference deviation of the base temperature value from the actual temperature value, a 0 represents the reference temperature value, a g represents the actual temperature value of the g-th preset time period, α 1 represents the weight of the actual temperature value with respect to the temperature threshold coefficient, Δb represents the maximum temperature allowable reference deviation, B 0 represents the maximum temperature reference deviation, B g represents the maximum temperature deviation of the g-th preset time period, α 2 represents the weight of the maximum temperature deviation with respect to the temperature threshold coefficient, Δc represents the temperature change rate allowable reference deviation, C 0 represents the temperature change reference rate, C g represents the temperature change rate of the g-th preset time period, α 3 represents the weight of the temperature change rate with respect to the temperature threshold coefficient, Δd represents the duration allowable reference threshold, D 0 represents the duration threshold, D g represents the weight of the g-th preset time period with respect to the temperature threshold coefficient, α 4 duration;
The maximum temperature deviation is the maximum deviation value of the surface temperature of the electrified cable relative to a reference temperature value, the temperature change rate is the change rate of the surface temperature of the electrified cable in unit time, and the duration threshold is the reference duration of abnormal temperature change of the surface of the electrified cable.
2. A thermal defect detection system for live cables as defined in claim 1 wherein: the thermal imaging module comprises a thermal image generation unit, an image acquisition unit, an image processing unit and a temperature mapping unit; the thermal image generation unit: the method comprises the steps of generating a thermal image of a power-on cable in a preset time period according to first temperature data to obtain a temperature distribution diagram, and obtaining the temperature change condition in the temperature distribution diagram according to a thermal imaging analysis method; the image acquisition unit: the temperature change condition in the temperature distribution diagram is converted into a second digital signal, and the second digital signal is used for displaying the temperature of the surface of the charged cable in the temperature distribution diagram;
The image processing unit: the second processing unit is used for carrying out secondary processing on the second digital signal to extract second key characteristic data and adjust a thermal image, wherein the secondary processing unit comprises image enhancement and temperature calibration, and the second key characteristic data comprises second temperature change data, second thermal gradient data and second abnormal temperature peak value data;
The temperature mapping unit: the method is used for corresponding the pixel value in the adjusted thermal image to the actual temperature value according to the thermal imaging coefficient and generating a temperature distribution map, wherein the thermal imaging coefficient is a sensitivity index of micro temperature coefficient change in the adjusted thermal image, and the micro temperature coefficient is an accuracy index of converting the pixel value in the thermal image into the actual temperature value.
3. A thermal defect detection system for live cables as defined in claim 1 wherein: the alarm communication module comprises an alarm triggering unit, an alarm signal generating unit, a communication interface unit and an information formatting unit; the alarm triggering unit is used for: is used for judging whether to trigger the alarm device according to the abnormal state of the hot cable in the preset time period provided by the data processing module and the abnormal temperature reduction coefficient, the abnormal temperature reduction coefficient is the influence degree of converting the pixel value in the thermal image into the actual temperature value;
The alarm signal generating unit: the alarm device is used for generating corresponding alarm signals according to the triggering result of the alarm device so as to display the specific position of the thermal defect of the electrified cable in a preset time period, wherein the alarm signals comprise sound, optical signals and electric signals;
The communication interface unit: for transmitting the alarm signal into the communication device to obtain a communication signal;
The information formatting unit: the communication signal is formatted into a preset format to obtain alarm data, wherein the alarm data comprises alarm time, alarm level, alarm type and thermal image data, and the thermal image data is used for reflecting the thermal defect state of the electrified cable in a preset time period.
4. The hot-fault detection system for an electrical cable according to claim 1, wherein the specific process of converting the temperature signal into the digital signal comprises:
receiving a temperature signal acquired by a temperature sensor through a signal acquisition card and monitoring in real time;
and converting the temperature signal into visual image information according to the real-time monitoring result and carrying out information processing to obtain a digital signal, wherein the information processing represents converting the visual image information into the digital signal according to the abnormal temperature reduction coefficient.
5. The hot-fault detection system for an electrical cable according to claim 2, wherein the specific acquisition method for the thermal imaging coefficient comprises:
Acquiring a thermal imaging coefficient total correction factor and a thermal imaging total coefficient according to the first key feature data and the second key feature data, wherein the thermal imaging coefficient total correction factor comprises a first correction factor, a second correction factor, a third correction factor and a fourth correction factor, the thermal imaging total coefficient comprises a temperature change data coefficient, a thermal gradient data coefficient and an abnormal temperature peak data coefficient, the temperature change data coefficient is the product of relative deviation of temperature change data and the second correction factor, the relative deviation of temperature change data is the product of the absolute value of the difference between the second temperature change data and the first temperature change data and the corresponding reference deviation, the thermal gradient data coefficient is the product of the relative deviation of the thermal gradient data and the third correction factor, the relative deviation of the thermal gradient is the product of the absolute value of the difference between the second thermal gradient data and the first thermal gradient data and the corresponding reference deviation, the abnormal temperature peak data coefficient is the product of relative deviation of abnormal temperature peak data and the fourth correction factor, and the abnormal temperature peak data is the product of the absolute value of the difference between the second abnormal temperature peak data and the first abnormal temperature peak data and the corresponding reference deviation;
And combining the obtained thermal imaging total coefficient and the thermal imaging coefficient total correction factor to obtain a thermal imaging coefficient, wherein the thermal imaging coefficient is the product of the thermal imaging total coefficient and the first correction factor.
6. The hot-fault detection system for an electrical cable of claim 5, wherein the micro-temperature coefficient is calculated by the formula:
，
Wherein ζ g represents a micro temperature coefficient of a g-th preset time period, Δλ represents a reference deviation of an abnormal temperature reduction coefficient, λ 0 represents a reference abnormal temperature reduction coefficient, λ g represents an abnormal temperature reduction coefficient of a g-th preset time period, δ represents a weight of the abnormal temperature reduction coefficient with respect to the micro temperature coefficient, Δh represents a reference deviation of a temperature sensitivity coefficient, H 0 represents a reference temperature sensitivity coefficient, H g represents a temperature sensitivity coefficient of a g-th preset time period, ε 1 represents a weight of the temperature sensitivity coefficient with respect to the micro temperature coefficient, Δl represents a reference deviation of the temperature linearity coefficient, L 0 represents a reference temperature linearity coefficient, L g represents a temperature linearity coefficient of a g-th preset time period, ε 2 represents a weight of the temperature linearity coefficient with respect to the micro temperature coefficient; the abnormal temperature reduction coefficient is the influence degree of converting a pixel value in the thermal image into an actual temperature value, the temperature sensitivity coefficient is the response degree of converting the pixel value in the thermal image into the actual temperature value, and the temperature linearity coefficient is the linear relation degree between the pixel value in the thermal image and the actual temperature value.
7. The thermal defect detecting system for live cables according to claim 1, wherein the specific step of acquiring the first temperature data in the abnormality detecting unit comprises:
Extracting characteristic temperature data from first key characteristic data, wherein the characteristic temperature data comprises temperature space distribution data, temperature linear change trend data and operation data of a live cable in a preset environment in a temperature distribution map;
Selecting a corresponding abnormal detection algorithm to detect the extracted characteristic temperature data, and identifying an abnormal temperature region according to a detection result to obtain a thermal defect region;
And acquiring thermal defect temperature data from the thermal defect area and performing thermal defect treatment to obtain first temperature data, wherein the thermal defect data comprise an abnormal temperature maximum value, abnormal environment data and abnormal operation data of the power cable in a preset time period, and the thermal defect treatment is used for performing data integration and data classification on the thermal defect data in the thermal defect area.
8. A method for application to a thermal defect detection system for live cables according to any one of claims 1 to 7, characterized by comprising the steps of:
Monitoring the temperature of the electrified cable in a preset time period in real time and converting a temperature signal into a digital signal, wherein the temperature signal comprises measurement precision, response speed and a temperature resistant range;
Converting the digital signal into temperature data according to a temperature threshold method and performing data processing to obtain first temperature data, wherein the temperature threshold method is used for identifying thermal defects of the electrified cable in a preset time period under the condition of abnormal temperature change according to a temperature threshold coefficient;
Generating a thermal image of the electrified cable according to the first temperature data to obtain a temperature distribution map, wherein the temperature distribution map is used for visualizing the temperature distribution condition of the surface of the electrified cable, and the thermal image is used for positioning the specific position of the thermal defect of the electrified cable in a preset time period;
when the specific position of the thermal defect of the electrified cable in the preset time period is detected, an alarm signal is sent out through an alarm device and is communicated by combining communication equipment, and the communication equipment is used for converting the alarm signal into the thermal defect information of the electrified cable and outputting the thermal defect information in a communication mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410688453.1A CN118243240B (en) | 2024-05-30 | 2024-05-30 | Hot defect detection system and method for electrified cable |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410688453.1A CN118243240B (en) | 2024-05-30 | 2024-05-30 | Hot defect detection system and method for electrified cable |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118243240A CN118243240A (en) | 2024-06-25 |
| CN118243240B true CN118243240B (en) | 2024-08-16 |
Family
ID=91562891
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410688453.1A Active CN118243240B (en) | 2024-05-30 | 2024-05-30 | Hot defect detection system and method for electrified cable |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118243240B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118773860B (en) * | 2024-09-06 | 2024-11-29 | 江苏亨通光电股份有限公司 | Flat belt cable and production process thereof |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115824421A (en) * | 2022-10-31 | 2023-03-21 | 国网浙江省电力有限公司湖州供电公司 | Cable terminal temperature defect early warning method, system and equipment based on trend analysis |
| CN116879683A (en) * | 2023-09-04 | 2023-10-13 | 湖南华菱线缆股份有限公司 | A method and device for identifying local defects in high-voltage power cables |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102013224573B3 (en) * | 2013-11-29 | 2014-10-02 | Hagenuk KMT Kabelmeßtechnik GmbH | Method and device for locating partial discharges in electrical cables |
| DE102020003143B4 (en) * | 2020-05-26 | 2021-12-09 | Lapp Engineering Ag | Device and method for line and cable diagnosis |
| CN117890696A (en) * | 2023-12-13 | 2024-04-16 | 国网湖北省电力有限公司电力科学研究院 | A high voltage cable defect identification method, device and storage medium |
-
2024
- 2024-05-30 CN CN202410688453.1A patent/CN118243240B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115824421A (en) * | 2022-10-31 | 2023-03-21 | 国网浙江省电力有限公司湖州供电公司 | Cable terminal temperature defect early warning method, system and equipment based on trend analysis |
| CN116879683A (en) * | 2023-09-04 | 2023-10-13 | 湖南华菱线缆股份有限公司 | A method and device for identifying local defects in high-voltage power cables |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118243240A (en) | 2024-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103901072B (en) | Method for diagnosing equipment overheating defects by utilizing infrared spectrum analysis | |
| KR101200053B1 (en) | Thereof method and, progressive unusual condition real time diagnostic equipment of transformers and insulator | |
| CN118243240B (en) | Hot defect detection system and method for electrified cable | |
| CN112147444B (en) | Power transformer working state monitoring method and system | |
| CN105548747A (en) | Equipment fault identification system and method based on infrared temperature measurement technology | |
| CN117407679B (en) | Data acquisition method and system of intelligent end screen sensor | |
| CN108181556A (en) | Porcelain insulator zero value detection method based on chapeau de fer temperature difference time series analysis | |
| CN111157886A (en) | A method for fault diagnosis of catenary isolation switch | |
| Taib et al. | Thermal imaging for enhancing inspection reliability: detection and characterization | |
| WO2019100030A1 (en) | Remote monitoring of electrical equipment with multi-factor historical / statistical anomaly detection and prediction | |
| CN111007366A (en) | Oil type casing hidden danger monitoring system and method | |
| CN116704733A (en) | Aging early warning method and system for aluminum alloy cable | |
| CN114942075A (en) | Fault detection and analysis method of power equipment | |
| CN114895163A (en) | Cable inspection positioning device and method based on cable insulation performance | |
| CN118091407B (en) | Method and device for testing insulation performance of engine stator | |
| CN118311363A (en) | Defect detection method and system for substation equipment | |
| CN111562450B (en) | System and method for monitoring service life of reactor | |
| CN113153262A (en) | Offshore oilfield accessible capacity evaluation method based on cable thermal characteristics | |
| CN112684293A (en) | A diagnostic device for insulation faults in power distribution systems | |
| CN117907739A (en) | Transmission line detection method | |
| CN116128810A (en) | Infrared defect detection method and system based on front end identification | |
| CN109186786B (en) | A device and method for monitoring electrical contact overheating of electrical equipment | |
| CN114235181A (en) | An installation and positioning system for RFID wireless passive temperature measurement chip | |
| CN118641920B (en) | Silicon carbide power device detection method for self-detection of heating point | |
| CN219800139U (en) | Transformer fault monitoring device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |