CN111562540A - Electric energy meter detection monitoring method based on dynamic image recognition and analysis - Google Patents
Electric energy meter detection monitoring method based on dynamic image recognition and analysis Download PDFInfo
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Abstract
The invention discloses an electric energy meter detection monitoring method based on dynamic image recognition and analysis, relates to the technical field of electric energy metering monitoring, solves the technical problem of poor monitoring of large-range abnormal phenomena in the conventional electric energy meter verification assembly line workshop, and provides a novel solution. The invention organically combines an electronic sensor technology, an image processing technology, a data processing technology, a control technology and a computer technology, is applied to the field of electric energy meter detection, realizes intelligent and automatic monitoring of the detection technology, and improves the monitoring strength of the electric energy meter detection field.
Description
Technical Field
The invention relates to the technical field of electric energy metering, in particular to an electric energy meter detection monitoring method based on dynamic image recognition and analysis.
Background
In the technical field of electric energy meter detection, particularly in the detection process of a large-scale electric energy meter production line, a component main body of a detection production line, such as a feeding machine, a mechanical transmission conveyor, a blanking machine, an image identification seal device, a labeling machine, a power source, a standard meter and other components are all important components for detecting the electric energy meter, the automatic production line detection system of the intelligent electric energy meter can realize the functions of automatic transmission, automatic wire connection and disconnection, automatic detection, automatic seal, labeling, intelligent sorting and warehousing and the like of the intelligent electric energy meter, realizes the automation and intellectualization of the whole detection process of the intelligent electric energy meter, effectively avoids manual errors and improves the detection quality and efficiency of the intelligent electric energy meter. However, in the detection process, especially in the connection place, the electric energy meter in operation is prone to be jammed and suspended due to the arrangement of the hardware in the arrangement position and the assembly line. The manual monitoring working condition not only needs to consume a large amount of manpower, increases the production cost of enterprises, but also is easy to cause errors due to artificial fatigue caused by long-term manual labor. In the field of a large-scale electric energy meter verification assembly line, suspicious personnel also exist, and meter tools are stolen, so that a monitoring method is needed, and the monitoring method is specially used for monitoring the production working condition of a large-scale production workshop and monitoring the suspicious personnel.
Disclosure of Invention
Aiming at the defects of the prior art, the invention discloses an electric energy meter detection monitoring method based on dynamic image recognition and analysis, which can realize the monitoring of the site working condition of a large-scale electric energy meter production line, effectively avoid abnormal accidents in the operation process of the electric energy meter and monitor the occurrence of suspicious personnel.
In order to solve the technical problems, the invention adopts the following technical scheme:
the utility model provides an electric energy meter detects monitoring system based on dynamic image discernment and analysis which characterized in that: the monitoring system includes:
the electric energy meter calibration device, the electric energy meter calibration assembly line, the sensor equipment or the electric energy meter calibration system are at least arranged in the equipment layer and used for detecting data information of the electric energy meter, wherein the data information of the electric energy meter at least comprises current, voltage, power, vibration or ripple waves, and the sensor equipment at least envelops an electric sensor, an infrared sensor, a speed sensor, an acceleration sensor, a GIS sensor, a vibration sensor, a ripple wave sensor, a temperature and humidity sensor, an angle sensor, a magnetic field sensor, a rotating speed sensor, an RFID tag, GPS equipment, a ray radiation sensor, a thermosensitive sensor, an energy consumption sensor or an M2M terminal;
the detection layer is at least internally provided with an image acquisition unit and is used for acquiring the verification condition of the electric energy meter in the plant and the in-out information of abnormal personnel in the plant so as to realize the unmanned detection of the electric energy meter detection site; the image acquisition unit at least comprises an industrial camera and an image sensor, and data transmission is carried out on the image acquisition unit through a wired communication module at least comprising an RS485 communication module, an RS232 communication module, an infrared communication module or a carrier communication module and a wireless communication module at least comprising a TCP/IP communication module, a ZigBee wireless communication module, a GPRS communication module, a CDMA wireless communication module or a Bluetooth communication module;
the image processing layer is at least internally provided with an image recognition unit, the image recognition unit at least comprises an image analysis module and an image extraction module, the image extraction module is used for extracting the acquired image information, segmenting the extracted image, and analyzing and calculating the segmented image information through the image analysis module;
the monitoring layer is at least internally provided with a monitoring device, the monitoring device is connected with an alarm module and a display module, and the monitoring layer carries out unmanned, remote and intelligent monitoring on the electric energy meter detection site by analyzing and calculating the acquired images; wherein:
the output end of the equipment layer is connected with the input end of the detection layer, the output end of the detection layer is connected with the input end of the image processing layer, and the output end of the image processing layer is connected with the input end of the monitoring layer.
As a further aspect of the invention, the image sensor employs an OV7670 module with AL422B cache, the industrial camera is a CCD industrial camera with a 360 ° rotating camera.
As a further technical scheme of the invention, the control component of the image recognition unit is an STM32 microprocessor, and the STM32 microprocessor adopts an STM32F103VET6 embedded control chip based on a Cortex-M3 kernel.
As a further technical scheme of the invention, the image extraction module and the image analysis module are respectively provided with an I/O interface for receiving digital signals and analog information.
As a further technical scheme of the invention, the alarm module is an audible and visual alarm module, and the display module is an LCD large screen rolling display screen.
In order to solve the technical problems, the invention adopts the following technical scheme:
a method for detecting and monitoring an electric energy meter based on dynamic image recognition and analysis is characterized by comprising the following steps: the method comprises the following steps:
(S1) data acquisition; acquiring data information of an electric energy meter detection site, wherein the data information comprises electric energy meter working condition information and site abnormal personnel activity information, cleaning or preprocessing the acquired electric energy meter image information or data information, outputting pure electric energy meter site data detection information, and acquiring original data;
(S2) data transfer; receiving and transmitting the running conditions of the electric energy meters in different electric energy meter detection stations in the plant and the in-and-out conditions of field abnormal personnel in a wired communication or wireless communication mode;
(S3) data processing; extracting the acquired image by an improved difference method, realizing the anomaly analysis of the electric energy meter detection site by adopting an ant colony algorithm, and dynamically monitoring the anomaly condition of the electric energy meter detection site;
(S4) electric energy meter field monitoring; through image analysis and processing, the electric energy meter detection site condition is remotely and dynamically observed in a monitoring room, and the monitoring site is displayed in real time.
As a further technical solution of the present invention, the improved difference method in the step (S3) is:
suppose the monitored image is in coordinates
At a pixel value of
For treatment
Is shown in
Is represented by
Setting a threshold value of
Then, there are:
when in use
If so, indicating that the environment has an abnormal phenomenon;
when in use
If so, indicating that the environment is not changed; wherein the threshold value
In the range of 0.1 to 1000.
As a further technical solution of the present invention, the improved difference method in the step (S3) is a maximum inter-class variance method, wherein the maximum inter-class variance method is:
let the gray scale range of the image be
，
The pixel of (b) is denoted as
In the decimated image, the total pixels are represented by the following formula:
；
assume that the probability of each gray level in the image is:
；
the mean gray value can be expressed
；
When performing image segmentation, the gray threshold of the image is expressed as
Dividing the image into
、
In the two categories of the anti-cancer drugs,
gray value range of
The gray scale probability value is expressed by the following formula:
(ii) a Then
Has a gray value range of
Then the gray level probability is
(ii) a The mean values of the two classes of gray values can be formulated as:
as a further technical solution of the present invention, the relationship between the two types of gray value average values is:
and wherein
And
the inter-class variance between can be expressed as:
as a further technical solution of the present invention, it is assumed that the set threshold is expressed by a formula:
the result after image segmentation can be expressed as:
has the positive and beneficial effects that:
the invention organically combines an electronic sensor technology, an image processing technology, a data processing technology, a control technology and a computer technology, is applied to the field of electric energy meter detection, realizes intelligent and automatic monitoring of the detection technology, and improves the monitoring strength of the electric energy meter detection field.
Drawings
FIG. 1 is a schematic diagram of an electric energy meter detection monitoring system based on dynamic image recognition and analysis according to the present invention;
FIG. 2 is a schematic diagram of an image acquisition unit architecture in an electric energy meter detection monitoring system based on dynamic image recognition and analysis according to the present invention;
FIG. 3 is a schematic diagram of an image recognition unit in the electric energy meter detection monitoring system based on dynamic image recognition and analysis according to the present invention;
FIG. 4 is a schematic flow chart of a method for detecting and monitoring an electric energy meter based on dynamic image recognition and analysis according to the present invention;
FIG. 5 is a schematic diagram of an algorithm model in the electric energy meter detection monitoring method based on dynamic image recognition and analysis.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
Example 1 System
As shown in fig. 1-3, a power meter detection monitoring system based on dynamic image recognition and analysis includes: an electric energy meter detection monitoring system based on dynamic image recognition and analysis, wherein the monitoring system comprises:
the electric energy meter calibration device, the electric energy meter calibration assembly line, the sensor equipment or the electric energy meter calibration system are at least arranged in the equipment layer and used for detecting data information of the electric energy meter, wherein the data information of the electric energy meter at least comprises current, voltage, power, vibration or ripple waves, and the sensor equipment at least envelops an electric sensor, an infrared sensor, a speed sensor, an acceleration sensor, a GIS sensor, a vibration sensor, a ripple wave sensor, a temperature and humidity sensor, an angle sensor, a magnetic field sensor, a rotating speed sensor, an RFID tag, GPS equipment, a ray radiation sensor, a thermosensitive sensor, an energy consumption sensor or an M2M terminal;
the detection layer is at least internally provided with an image acquisition unit and is used for acquiring the verification condition of the electric energy meter in the plant and the in-out information of abnormal personnel in the plant so as to realize the unmanned detection of the electric energy meter detection site; the image acquisition unit at least comprises an industrial camera and an image sensor, and data transmission is carried out on the image acquisition unit through a wired communication module at least comprising an RS485 communication module, an RS232 communication module, an infrared communication module or a carrier communication module and a wireless communication module at least comprising a TCP/IP communication module, a ZigBee wireless communication module, a GPRS communication module, a CDMA wireless communication module or a Bluetooth communication module;
the image processing layer is at least internally provided with an image recognition unit, the image recognition unit at least comprises an image analysis module and an image extraction module, the image extraction module is used for extracting the acquired image information, segmenting the extracted image, and analyzing and calculating the segmented image information through the image analysis module;
the monitoring layer is at least internally provided with a monitoring device, the monitoring device is connected with an alarm module and a display module, and the monitoring layer carries out unmanned, remote and intelligent monitoring on the electric energy meter detection site by analyzing and calculating the acquired images; wherein:
the output end of the equipment layer is connected with the input end of the detection layer, the output end of the detection layer is connected with the input end of the image processing layer, and the output end of the image processing layer is connected with the input end of the monitoring layer.
By adopting the technical scheme, the invention organically combines the electronic sensor technology, the image processing technology, the data processing technology, the control technology and the computer technology together and is applied to the field of electric energy meter detection, the invention realizes the intelligent and automatic monitoring of the detection technology, improves the monitoring strength of the electric energy meter detection site, realizes the extraction of the dynamic condition information of the electric energy meter in the production line by using an improved difference method, the on-site motion state information is obtained by segmenting the image, the ant colony algorithm is adopted to realize the anomaly analysis of the electric energy meter detection site, thereby realizing the monitoring of the detection working condition of the electric energy meter and the monitoring of suspicious personnel, the invention has high intellectualization and automation degree, can realize remote monitoring, and further, the monitoring of the site working condition of the electric energy meter verification assembly line is realized, and the detection working condition of the electric energy meter is effectively monitored.
In a further embodiment, and with particular reference to fig. 2, the image sensor employs an OV7670 module with AL422B cache, the industrial camera being a CCD industrial camera with a 360 ° rotating camera. In a specific application, the image acquisition unit can realize three-dimensional motion in X-axis, Y-axis and Z-axis directions in a three-dimensional space coordinate, and the three-dimensional motion can be realized by arranging the image acquisition unit on a slide way with a slide block and a guide rail. More specifically, motors connected with the sliding blocks are arranged on the X-axis arm, the Y-axis arm and the Z-axis arm respectively, and the sliding blocks are driven by the motors, so that the image acquisition unit can move freely in the X-axis direction, the Y-axis direction and the Z-axis direction, and dead-angle-free image acquisition is realized. In other embodiments, the shooting angle is adjusted through an automatic focusing camera, so that the image information acquisition of the electric energy meter detection range in the electric energy meter production workshop is realized.
In a further embodiment, with particular reference to fig. 3, the control component of the image recognition unit is an STM32 microprocessor, and the STM32 microprocessor adopts an STM32F103VET6 embedded control chip based on a Cortex-M3 kernel. The method comprises the steps that an image extraction module, a training module, a classifier, an image generation module, an image analysis module, an ant colony algorithm module and the like are controlled through a microprocessor, wherein the image extraction module is used for extracting features of images to be processed in an image set and a background image set in an electric energy meter detection workshop, the training module is used for training by using the features to obtain the classifier used for distinguishing objects and backgrounds, and the image generation module can also be used for outputting images and displaying the finally generated images. The image extraction module and the image analysis module are respectively provided with an I/O interface for receiving digital signals and analog information, and the output of image data is realized through the arranged I/O interface.
In a further embodiment, the alarm module is an audible and visual alarm module, and the display module is an LCD large screen rolling display screen.
EXAMPLE 2 method
A method for detecting and monitoring an electric energy meter based on dynamic image recognition and analysis is characterized by comprising the following steps: the method comprises the following steps:
(S1) data acquisition; acquiring data information of an electric energy meter detection site, wherein the data information comprises electric energy meter working condition information and site abnormal personnel activity information, cleaning or preprocessing the acquired electric energy meter image information or data information, outputting pure electric energy meter site data detection information, and acquiring original data;
(S2) data transfer; receiving and transmitting the running conditions of the electric energy meters in different electric energy meter detection stations in the plant and the in-and-out conditions of field abnormal personnel in a wired communication or wireless communication mode;
(S3) data processing; extracting the acquired image by an improved difference method, realizing the anomaly analysis of the electric energy meter detection site by adopting an ant colony algorithm, and dynamically monitoring the anomaly condition of the electric energy meter detection site; this technical solution will be explained in detail below.
Image recognition scheme one
Firstly, the image is divided, because the field motion state is multi-target motion, the electric energy meter in the assembly line dynamically changes position along with the time, when the abnormal change information is extracted, the change between adjacent frames of the monitoring image is very obvious after the image in motion appears in the detection range, the invention applies the difference method, and when the image pixel information extracted at the previous moment is assumed to be expressed by a formula, the monitoring image is assumed to be in the coordinate
At a pixel value of
For treatment
Is shown in
Is represented by
Setting a threshold value of
Then, there are:
when in use
When the abnormal phenomenon exists, the abnormal phenomenon exists in the environment
If so, the environment is not changed. In the above calculation process, the threshold value
According to specific work occasions and daily experience accumulation, management personnel set the requirements, evaluation objects are different, threshold values are different, and for example, the requirements for judging the operation condition of the electric energy meter on a production line and judging whether workshop personnel are abnormal or not are different.
Image recognition scheme two
When the image recognition scheme I is adopted for calculation, the phenomena of low precision and the like easily caused by the setting of a threshold value are easily caused, the method is utilized, the maximum inter-class variance method is matched for image segmentation, and the gray scale range of the image is set as
For the convenience of calculation, will
The pixel of (b) is denoted as
In the decimated image, the total pixels are represented by the following formula:
then there is the following relationship:
wherein
And
the inter-class variance between can be expressed as:
wherein the set threshold is formulated as:
the result after image segmentation can be expressed as:
and further acquiring areas of two adjacent frames of suspected target objects moving in the picture acquired by the electric energy meter detection site through the divided areas. The moving area of the suspicious object can be detected through the texture characteristics, and then the judgment of the moving object is realized.
The following describes an image analysis method
The invention adopts the ant colony algorithm to realize the abnormity analysis of the electric energy meter detection field, and assumes that the extracted image information is
Then each pixel in the image is defined as
Wherein
The ant elements are expressed as a plurality of small pixels for dividing the image, each ant is expressed as the gray level, the gradient and the field of the image, the three-dimensional vector is formed, after the image is divided into a plurality of small pixels, the distance between the pixels is calculated by adopting an Euclidean distance formula, and the formula is expressed as follows:
in the above-mentioned formula,
representing arbitrary pixels in a decimated image
And
the distance between them.
The degree of influence of different components of each pixel on the distance is determined by the information amount, wherein the calculation formula of the information amount can be expressed as:
in the above-mentioned formula,
representing a plurality of small pixels, i.e., ant elements, that are divided, in one embodiment,
may range from 2 to 5,
expressed as a weighting factor, is a function of,
expressed as the radius of the cluster or clusters,
expressed as a volume of information.
The probability formula for path selection may be:
in the above formula, 0 is the other case, and indicates selection
To
A probability of a path therebetween, wherein
Representing the information accumulated during the clustering process for each different pixel,
expressed as the influence factor of the heuristic guiding function on the path selection, wherein:
Because of the continuous movement of the field personnel, the information amount on each pixel changes in real time, which requires continuous adjustment of the information amount, and the adjustment formula is as follows:
in the above-mentioned formula,
indicating the degree of attenuation of the amount of information as the test site moves,
indicating the increment of the information amount in the new cyclic path during the new movement, wherein
Wherein
Is shown as
The amount of information left by only ant elements in the new circular path.
And selecting an abnormal information area through the algorithm, wherein the abnormal area comprises working condition information, detection field equipment information and suspicious personnel information in the electric energy meter detection range. According to the invention, dynamic images of a large-scale observation area are obtained, dynamic image information is obtained through dynamic image analysis and processing, and early warning is carried out on abnormal signals.
(S4) electric energy meter field monitoring; through image analysis and processing, the electric energy meter detection site condition is remotely and dynamically observed in a monitoring room, and the monitoring site is displayed in real time.
In this step, the processed data information can be transmitted to an upper management center, so that real-time and online monitoring of data is realized. The method is beneficial to the field identification of the electric energy meter detection, and when the electric energy meter running in the production line is stuck or because the electric energy meter is in failure stagnation, suspicious personnel walk around, the field detection of the electric energy meter can be effectively realized, and the method is beneficial to the normal running of the electric energy meter detection production line and the monitoring of the suspicious personnel on the field.
Although specific embodiments of the present invention have been described above, it will be understood by those skilled in the art that these specific embodiments are merely illustrative and that various omissions, substitutions and changes in the form of the detail of the methods and systems described above may be made by those skilled in the art without departing from the spirit and scope of the invention. For example, it is within the scope of the present invention to combine the steps of the above-described methods to perform substantially the same function in substantially the same way to achieve substantially the same result. Accordingly, the scope of the invention is to be limited only by the following claims.
Claims (10)
1. The utility model provides an electric energy meter detects monitoring system based on dynamic image discernment and analysis which characterized in that: the monitoring system includes:
the electric energy meter calibration device, the electric energy meter calibration assembly line, the sensor equipment or the electric energy meter calibration system are at least arranged in the equipment layer and used for detecting data information of the electric energy meter, wherein the data information of the electric energy meter at least comprises current, voltage, power, vibration or ripple waves, and the sensor equipment at least envelops an electric sensor, an infrared sensor, a speed sensor, an acceleration sensor, a GIS sensor, a vibration sensor, a ripple wave sensor, a temperature and humidity sensor, an angle sensor, a magnetic field sensor, a rotating speed sensor, an RFID tag, GPS equipment, a ray radiation sensor, a thermosensitive sensor, an energy consumption sensor or an M2M terminal;
the detection layer is at least internally provided with an image acquisition unit and is used for acquiring the verification condition of the electric energy meter in the plant and the in-out information of abnormal personnel in the plant so as to realize the unmanned detection of the electric energy meter detection site; the image acquisition unit at least comprises an industrial camera and an image sensor, and data transmission is carried out on the image acquisition unit through a wired communication module at least comprising an RS485 communication module, an RS232 communication module, an infrared communication module or a carrier communication module and a wireless communication module at least comprising a TCP/IP communication module, a ZigBee wireless communication module, a GPRS communication module, a CDMA wireless communication module or a Bluetooth communication module;
the image processing layer is at least internally provided with an image recognition unit, the image recognition unit at least comprises an image analysis module and an image extraction module, the image extraction module is used for extracting the acquired image information, segmenting the extracted image, and analyzing and calculating the segmented image information through the image analysis module;
the monitoring layer is at least internally provided with a monitoring device, the monitoring device is connected with an alarm module and a display module, and the monitoring layer carries out unmanned, remote and intelligent monitoring on the electric energy meter detection site by analyzing and calculating the acquired images; wherein:
the output end of the equipment layer is connected with the input end of the detection layer, the output end of the detection layer is connected with the input end of the image processing layer, and the output end of the image processing layer is connected with the input end of the monitoring layer.
2. The electric energy meter detection and monitoring system based on dynamic image recognition and analysis as claimed in claim 1, wherein: the image sensor employs an OV7670 module with AL422B cache, the industrial camera is a CCD industrial camera with a 360 ° rotating camera.
3. The electric energy meter detection and monitoring system based on dynamic image recognition and analysis as claimed in claim 1, wherein: the control component that the image recognition unit is STM32 microprocessor, STM32 microprocessor adopts STM32F103VET6 embedded control chip based on Cortex-M3 kernel.
4. The electric energy meter detection and monitoring system based on dynamic image recognition and analysis as claimed in claim 1, wherein: the image extraction module and the image analysis module are respectively provided with an I/O interface for receiving digital signals and analog information.
5. The electric energy meter detection and monitoring system based on dynamic image recognition and analysis as claimed in claim 1, wherein: the alarm module is an audible and visual alarm module, and the display module is an LCD large screen rolling display screen.
6. The method for monitoring the electric energy meter detection and monitoring system based on dynamic image recognition and analysis according to any one of claims 1 to 5, wherein the method comprises the following steps: the method comprises the following steps:
(S1) data acquisition; acquiring data information of an electric energy meter detection site, wherein the data information comprises electric energy meter working condition information and site abnormal personnel activity information, cleaning or preprocessing the acquired electric energy meter image information or data information, outputting pure electric energy meter site data detection information, and acquiring original data;
(S2) data transfer; receiving and transmitting the running conditions of the electric energy meters in different electric energy meter detection stations in the plant and the in-and-out conditions of field abnormal personnel in a wired communication or wireless communication mode;
(S3) data processing; extracting the acquired image by an improved difference method, realizing the anomaly analysis of the electric energy meter detection site by adopting an ant colony algorithm, and dynamically monitoring the anomaly condition of the electric energy meter detection site;
(S4) electric energy meter field monitoring; through image analysis and processing, the electric energy meter detection site condition is remotely and dynamically observed in a monitoring room, and the monitoring site is displayed in real time.
7. The method of claim 5, wherein: the improved difference method in the step (S3) is:
suppose the monitored image is in coordinates
At a pixel value of
For treatment
Is shown in
Is represented by
Setting a threshold value of
Then, there are:
when in use
If so, indicating that the environment has an abnormal phenomenon;
when in use
If so, indicating that the environment is not changed; wherein the threshold value
In the range of 0.1 to 1000.
8. The method of claim 5, wherein: the improved difference method in the step (S3) is a maximum inter-class variance method, wherein the maximum inter-class variance method is:
let the gray scale range of the image be
，
The pixel of (b) is denoted as
In the decimated image, the total pixels are represented by the following formula:
；
assume that the probability of each gray level in the image is:
；
the mean gray value can be expressed
；
When performing image segmentation, the gray threshold of the image is expressed as
Dividing the image into
、
In the two categories of the anti-cancer drugs,
gray value range of
The gray scale probability value is expressed by the following formula:
(ii) a Then
Has a gray value range of
Then the gray level probability is
(ii) a The mean values of the two classes of gray values can be formulated as:
9. the method of claim 5, wherein: the relationship between the two types of gray value average values is:
and wherein
And
the inter-class variance between can be expressed as:
10. the method of claim 5, wherein: assume that the set threshold is formulated as:
the result after image segmentation can be expressed as:
。
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114114130A (en) * | 2021-09-18 | 2022-03-01 | 宁夏隆基宁光仪表股份有限公司 | Electric energy meter testing method, system and device based on actual load on simulation site |
| CN117406160A (en) * | 2023-10-23 | 2024-01-16 | 国网黑龙江省电力有限公司营销服务中心 | Intelligent ammeter fault diagnosis system based on historical state comparison |
| CN117635905A (en) * | 2023-12-13 | 2024-03-01 | 国网上海市电力公司 | Intelligent monitoring method for electric energy meter installation quality based on image recognition algorithm |
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