CN112461289A - Ring main unit fault monitoring method, system, terminal and storage medium - Google Patents
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Abstract
本发明提供一种环网柜故障监控方法、系统、终端及存储介质，包括：利用传感器采集环网柜监控参数；从所述监控参数提取变化趋势特征值；判断所述变化趋势特征值是否在预设阈值范围内：若否，则生成故障告警，并将所述变化趋势特征值导入预先训练好的故障诊断模型进行故障诊断。本发明能够及时发现环网柜故障并对故障进行诊断，提高环网柜监管效率，简化了环网柜的修检过程。
The invention provides a fault monitoring method, system, terminal and storage medium for a ring main unit, including: collecting monitoring parameters of the ring main unit by using a sensor; extracting a change trend characteristic value from the monitoring parameter; and judging whether the change trend characteristic value is within Within the preset threshold range: if not, a fault alarm is generated, and the change trend characteristic value is imported into the pre-trained fault diagnosis model for fault diagnosis. The invention can timely discover and diagnose the fault of the ring network cabinet, improve the supervision efficiency of the ring network cabinet, and simplify the maintenance and inspection process of the ring network cabinet.
Description
Technical Field
The invention relates to the technical field of ring network power supply systems, in particular to a method, a system, a terminal and a storage medium for monitoring faults of a ring main unit.
Background
The ring network power supply is a main structural form of an urban power supply network, the ring main unit is an important component and a control node of the urban 6-10 kV power supply network at present, the number is large, the distribution range is wide, and therefore the running state of equipment in the ring main unit is directly related to the reliability of the urban power supply system.
The existing ring main unit state evaluation still mainly takes power failure maintenance, offline test and rated service life, and the equipment state perception and data diagnosis coverage are insufficient or lack. Therefore, on one hand, equipment failure can be caused due to insufficient experience of inspection personnel or untimely maintenance, so that production cannot be effectively guaranteed, and economic loss and even major accidents are caused; on the other hand, the well-operated equipment can be stopped for maintenance, which causes unnecessary production interruption and waste of maintenance cost.
Disclosure of Invention
In view of the above-mentioned deficiencies of the prior art, the present invention provides a method, a system, a terminal and a storage medium for monitoring a fault of a ring main unit, so as to solve the above-mentioned technical problems.
In a first aspect, the present invention provides a method for monitoring a fault of a ring main unit, including:
collecting monitoring parameters of the ring main unit by using a sensor;
extracting a variation trend characteristic value from the monitoring parameters;
judging whether the change trend characteristic value is within a preset threshold value range:
if not, generating a fault alarm, and importing the change trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
Further, utilize sensor acquisition looped netowrk cabinet control parameter, include:
collecting a voltage value, a current value and a frequency value of the ring main unit;
the environmental parameters of the ring main unit are collected, and the environmental parameters comprise temperature, humidity, smog and mechanical characteristics.
Further, the extracting the characteristic value of the variation trend from the monitoring parameter includes:
and calculating the change slope, jump amplitude and change amplitude of the monitoring parameters according to the acquisition time of the monitoring parameters.
Further, the method for training the fault diagnosis model comprises the following steps:
acquiring historical fault information, wherein the historical fault information comprises fault characteristic values and corresponding fault types;
training the multilayer feedforward neural network model by using the historical fault information pair to the created training set of the multilayer feedforward neural network model;
and outputting the trained multilayer feedforward neural network model as a fault diagnosis model.
In a second aspect, the present invention provides a ring main unit fault monitoring system, including:
the parameter acquisition unit is configured for acquiring monitoring parameters of the ring main unit by using the sensor;
the characteristic extraction unit is used for extracting a change trend characteristic value from the monitoring parameters by characteristics;
the characteristic judgment unit is configured for judging whether the change trend characteristic value is within a preset threshold value range;
and the fault diagnosis unit is configured to generate a fault alarm if the change trend characteristic value is not within a preset threshold range, and introduce the change trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
Further, the parameter acquisition unit includes:
the first acquisition module is configured for acquiring a voltage value, a current value and a frequency value of the ring main unit;
and the second acquisition module is configured to acquire environmental parameters of the ring main unit, wherein the environmental parameters comprise temperature, humidity, smoke and mechanical characteristics.
Further, the feature extraction unit includes:
and the characteristic extraction module is configured for calculating the change slope, the jump amplitude and the change amplitude of the monitoring parameters according to the acquisition time of the monitoring parameters.
Further, the method for training the fault diagnosis model comprises the following steps:
acquiring historical fault information, wherein the historical fault information comprises fault characteristic values and corresponding fault types;
training the multilayer feedforward neural network model by using the historical fault information pair to the created training set of the multilayer feedforward neural network model;
and outputting the trained multilayer feedforward neural network model as a fault diagnosis model.
In a third aspect, a terminal is provided, including:
a processor, a memory, wherein,
the memory is used for storing a computer program which,
the processor is used for calling and running the computer program from the memory so as to make the terminal execute the method of the terminal.
In a fourth aspect, a computer storage medium is provided having stored therein instructions that, when executed on a computer, cause the computer to perform the method of the above aspects.
The beneficial effect of the invention is that,
the method, the system, the terminal and the storage medium for monitoring the faults of the ring main unit can automatically acquire the operation parameters and the environmental parameters of the ring main unit, process the acquired parameters, find the faults in time, and diagnose the faults by using the fault diagnosis model in time after the faults of the ring main unit are found, so that operation and maintenance personnel can conveniently and specifically process the faults in time. The invention can find the fault of the ring main unit in time and diagnose the fault, thereby improving the supervision efficiency of the ring main unit and simplifying the repair process of the ring main unit.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention.
FIG. 2 is another schematic flow diagram of a method of one embodiment of the invention.
FIG. 3 is a schematic block diagram of a system of one embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention. The execution main body in fig. 1 may be a ring main unit fault monitoring system.
As shown in fig. 1, the method includes:
and 140, if not, generating a fault alarm, and importing the change trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
Specifically, referring to fig. 2, the method for monitoring a fault of a ring main unit includes:
and S1, collecting monitoring parameters of the ring main unit by using the sensor.
The sensor comprises a temperature and humidity sensor, a smoke sensor, a water level sensor, a voltage sensor, a current sensor, a frequency sensor, a mechanical characteristic sensor, a partial discharge sensor and the like, and the sensor is installed on the ring main unit to realize signal conversion of the running state of the equipment.
A/D conversion (converting a data state signal into a digital signal suitable for computer processing), signal conditioning and storage of ring main unit related configuration files are carried out on signals collected by a sensor, and the conditioned signals are preprocessed according to configuration information; the types of data extracted from the acquired signal include valid values, peak values, instantaneous values, frequency values. The acquired data includes temperature, humidity, smoke, water level, voltage, current, mechanical property sensors, partial discharge sensors and the like configured in each interval ring main unit, but is not limited to the above, and all the required data can be acquired through the terminal layer; the configuration file comprises ring main unit configuration information such as installation position coordinates, factories, secondary factories and the like of the ring main unit.
And S2, extracting a change trend characteristic value from the monitoring parameters.
And extracting change trend characteristic values from the data extracted in the step S1, wherein the change trend characteristic values comprise change slopes, jump amplitudes and change amplitudes.
S3, judging whether the change trend characteristic value is within a preset threshold value range: if not, generating a fault alarm, and importing the change trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
Threshold value ranges of the feature values of each item of data are preset, whether the feature values of each item of data extracted in step S2 are within the corresponding threshold value ranges is judged, and if an abnormal feature value that is not within the corresponding threshold value range exists, it is indicated that the ring main unit has a fault.
And inputting the abnormal characteristic value into a fault diagnosis model trained in advance to perform fault diagnosis.
The training method of the fault diagnosis model comprises the following steps:
(1) model training
a) Acquiring historical operating data of the ring main unit from a data center (a cloud or a platform layer);
b) performing data processing and feature extraction, and determining a training sample set by combining fault types corresponding to all data;
c) determining parameters of the BP neural network, including the number of input layer nodes, the number of hidden layer nodes and the number of output layer nodes, training the BP neural network according to a training sample set to obtain a neural network weight matrix, and establishing a fault diagnosis model;
(2) real-time diagnosis
a) Collecting real-time operation data of the ring main unit;
b) processing data and extracting features, and performing alarm judgment by using the extracted features, wherein the specific alarm judgment method can adopt different measures according to specific conditions as long as the aim of a designer can be achieved; comparing the characteristic value with a set threshold value, and when the characteristic value does not exceed the threshold value, not triggering an alarm, and when the characteristic value exceeds the threshold value, triggering the alarm;
c) if an alarm is generated, calling a corresponding fault diagnosis model, and inputting the characteristic values corresponding to the group of data into the fault diagnosis model to finish the fault diagnosis process;
as shown in fig. 3, the system 300 includes:
the parameter acquisition unit 310 is configured to acquire the ring main unit monitoring parameters by using a sensor;
a feature extraction unit 320 configured to extract a variation trend feature value from the monitoring parameter by a feature;
a characteristic determining unit 330 configured to determine whether the variation trend characteristic value is within a preset threshold range;
and the fault diagnosis unit 340 is configured to generate a fault alarm if the variation trend characteristic value is not within a preset threshold range, and introduce the variation trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
Optionally, as an embodiment of the present invention, the parameter acquiring unit includes:
the first acquisition module is configured for acquiring a voltage value, a current value and a frequency value of the ring main unit;
and the second acquisition module is configured to acquire environmental parameters of the ring main unit, wherein the environmental parameters comprise temperature, humidity, smoke and mechanical characteristics.
Optionally, as an embodiment of the present invention, the feature extraction unit includes:
and the characteristic extraction module is configured for calculating the change slope, the jump amplitude and the change amplitude of the monitoring parameters according to the acquisition time of the monitoring parameters.
Optionally, as an embodiment of the present invention, a method for training a fault diagnosis model includes:
acquiring historical fault information, wherein the historical fault information comprises fault characteristic values and corresponding fault types;
training the multilayer feedforward neural network model by using the historical fault information pair to the created training set of the multilayer feedforward neural network model;
and outputting the trained multilayer feedforward neural network model as a fault diagnosis model.
Fig. 4 is a schematic structural diagram of a terminal 400 according to an embodiment of the present invention, where the terminal 400 may be used to execute the ring main unit fault monitoring method according to the embodiment of the present invention.
Among them, the terminal 400 may include: a processor 410, a memory 420, and a communication unit 430. The components communicate via one or more buses, and those skilled in the art will appreciate that the architecture of the servers shown in the figures is not intended to be limiting, and may be a bus architecture, a star architecture, a combination of more or less components than those shown, or a different arrangement of components.
The memory 420 may be used for storing instructions executed by the processor 410, and the memory 420 may be implemented by any type of volatile or non-volatile storage terminal or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The executable instructions in memory 420, when executed by processor 410, enable terminal 400 to perform some or all of the steps in the method embodiments described below.
The processor 410 is a control center of the storage terminal, connects various parts of the entire electronic terminal using various interfaces and lines, and performs various functions of the electronic terminal and/or processes data by operating or executing software programs and/or modules stored in the memory 420 and calling data stored in the memory. The processor may be composed of an Integrated Circuit (IC), for example, a single packaged IC, or a plurality of packaged ICs connected with the same or different functions. For example, the processor 410 may include only a Central Processing Unit (CPU). In the embodiment of the present invention, the CPU may be a single operation core, or may include multiple operation cores.
A communication unit 430, configured to establish a communication channel so that the storage terminal can communicate with other terminals. And receiving user data sent by other terminals or sending the user data to other terminals.
The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and the program may include some or all of the steps in the embodiments provided by the present invention when executed. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
Therefore, the invention can automatically collect the operation parameters and the environmental parameters of the ring main unit, process the collected parameters, find the fault in time, and diagnose the fault by using the fault diagnosis model in time after finding the fault of the ring main unit, thereby facilitating the operation and maintenance personnel to deal with the fault in time in a targeted manner. According to the invention, the fault of the ring main unit can be found and diagnosed in time, the supervision efficiency of the ring main unit is improved, and the repair process of the ring main unit is simplified.
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in the form of a software product, where the computer software product is stored in a storage medium, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like, and the storage medium can store program codes, and includes instructions for enabling a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, and the like) to perform all or part of the steps of the method in the embodiments of the present invention.
The same and similar parts in the various embodiments in this specification may be referred to each other. Especially, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant points can be referred to the description in the method embodiment.
In the embodiments provided in the present invention, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
Although the present invention has been described in detail by referring to the drawings in connection with the preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made on the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and these modifications or substitutions are within the scope of the present invention/any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A ring main unit fault monitoring method is characterized by comprising the following steps:
collecting monitoring parameters of the ring main unit by using a sensor;
extracting a variation trend characteristic value from the monitoring parameters;
judging whether the change trend characteristic value is within a preset threshold value range:
if not, generating a fault alarm, and importing the change trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
2. The method according to claim 1, wherein the collecting the ring main unit monitoring parameters by using the sensor comprises:
collecting a voltage value, a current value and a frequency value of the ring main unit;
the environmental parameters of the ring main unit are collected, and the environmental parameters comprise temperature, humidity, smog and mechanical characteristics.
3. The method of claim 1, wherein extracting a trend-of-change feature value from the monitored parameter comprises:
and calculating the change slope, jump amplitude and change amplitude of the monitoring parameters according to the acquisition time of the monitoring parameters.
4. The method of claim 1, wherein the method of training the fault diagnosis model comprises:
acquiring historical fault information, wherein the historical fault information comprises fault characteristic values and corresponding fault types;
training the multilayer feedforward neural network model by using the historical fault information pair to the created training set of the multilayer feedforward neural network model;
and outputting the trained multilayer feedforward neural network model as a fault diagnosis model.
5. The utility model provides a looped netowrk cabinet fault monitoring system which characterized in that includes:
the parameter acquisition unit is configured for acquiring monitoring parameters of the ring main unit by using the sensor;
the characteristic extraction unit is used for extracting a change trend characteristic value from the monitoring parameters by characteristics;
the characteristic judgment unit is configured for judging whether the change trend characteristic value is within a preset threshold value range;
and the fault diagnosis unit is configured to generate a fault alarm if the change trend characteristic value is not within a preset threshold range, and introduce the change trend characteristic value into a pre-trained fault diagnosis model for fault diagnosis.
6. The system of claim 5, wherein the parameter acquisition unit comprises:
the first acquisition module is configured for acquiring a voltage value, a current value and a frequency value of the ring main unit;
and the second acquisition module is configured to acquire environmental parameters of the ring main unit, wherein the environmental parameters comprise temperature, humidity, smoke and mechanical characteristics.
7. The system of claim 5, wherein the feature extraction unit comprises:
and the characteristic extraction module is configured for calculating the change slope, the jump amplitude and the change amplitude of the monitoring parameters according to the acquisition time of the monitoring parameters.
8. The system of claim 5, wherein the method for training the fault diagnosis model comprises:
acquiring historical fault information, wherein the historical fault information comprises fault characteristic values and corresponding fault types;
training the multilayer feedforward neural network model by using the historical fault information pair to the created training set of the multilayer feedforward neural network model;
and outputting the trained multilayer feedforward neural network model as a fault diagnosis model.
9. A terminal, comprising:
a processor;
a memory for storing instructions for execution by the processor;
wherein the processor is configured to perform the method of any one of claims 1-4.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-4.
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