CN113947564A - Image verification method and system for low-voltage distribution area metering equipment in power industry - Google Patents
Image verification method and system for low-voltage distribution area metering equipment in power industry Download PDFInfo
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Abstract
The invention discloses an image checking method and a system for metering equipment in a low-voltage distribution area in the power industry, which comprises the steps of acquiring an image to be detected of the metering equipment in the low-voltage distribution area in the power industry, inputting the acquired image into a preset power image quality analysis model, carrying out image quality analysis, outputting a final image quality analysis result, judging whether the quality of the image meets a preset quality standard, inputting the image to be detected into a cloud for identification if the quality of the image meets the preset quality standard, detecting whether the power equipment has a fault, reacquiring the image to be detected if the quality of the image does not meet the preset quality detection standard, judging the quality of the image to be detected firstly before identifying the image to be detected, screening out the low-quality image to be detected, only identifying the high-quality image to be detected, and improving the quality of the image to be detected, the accuracy of the fault identification result of the power equipment is improved.
Description
Technical Field
The invention belongs to the field of power equipment safety, and particularly relates to a method for verifying image acquisition integrity of metering equipment in a low-voltage transformer area in the power industry.
Background
Along with the development of science and technology, the safety monitoring and the fault analysis of the power equipment are mostly analyzed through the intelligent detection system, the intelligent detection system is adopted, powerful human resources are saved, the accident rate in the detection process of the power equipment is reduced, and meanwhile, the equipment detection efficiency is greatly improved. However, in the process of detecting equipment by the intelligent detection system, due to the fact that a series of quality problems exist in the collected images, the problems that an analysis result is inaccurate, faults of power equipment are missed and mistakenly checked and the like are often caused.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an image verification method and system for metering equipment in a low-voltage distribution room in the power industry.
The embodiment of the invention provides an image verification method for metering equipment in a low-voltage transformer area in the power industry, which comprises the following steps:
acquiring an image to be detected of low-voltage transformer area metering equipment in the power industry;
inputting an image to be detected of the metering equipment in the low-voltage distribution room of the power industry into the power image quality analysis model for quality analysis, and outputting an image quality analysis result;
judging whether the image to be detected meets a preset quality standard or not based on the image quality analysis result;
and if the quality meets the preset quality standard, cloud identification is carried out on the image to be detected.
A second aspect of the embodiments of the present invention provides an image verification system for metering devices in a low-voltage distribution room in the power industry, where the system includes:
the image acquisition module is used for acquiring an image to be detected of the metering equipment in the low-voltage transformer area in the power industry;
the image analysis module is used for inputting an image to be detected of the metering equipment in the low-voltage distribution area of the power industry into the power image quality analysis model for quality analysis and outputting an image quality analysis result;
the result detection module is used for judging whether the image to be detected meets a preset quality standard or not based on the image quality analysis result;
and if the quality meets the preset quality standard, cloud identification is carried out on the image to be detected.
A third aspect of an embodiment of the present invention provides a terminal, where the terminal includes a processor and a memory, where the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement the foregoing method for verifying an image of a metering device in a low voltage distribution area in an electric power industry.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, where at least one program code is stored in the storage medium, and the at least one program code is loaded and executed by a processor to implement the foregoing method for checking an image of a low-voltage distribution area metering device in an electric power industry.
The invention discloses an image verification method and system for metering equipment in a low-voltage transformer area in the power industry, which have the following beneficial effects:
the invention discloses an image checking method and a system for metering equipment in a low-voltage distribution area in the power industry, which comprises the steps of acquiring an image to be detected of the metering equipment in the low-voltage distribution area in the power industry, inputting the acquired image into a preset power image quality analysis model, carrying out image quality analysis, outputting a final image quality analysis result, judging whether the quality of the image meets a preset quality standard, inputting the image to be detected into a cloud for identification if the quality of the image meets the preset quality standard, detecting whether the power equipment has a fault, reacquiring the image to be detected if the quality of the image does not meet the preset quality detection standard, judging the quality of the image to be detected firstly before identifying the image to be detected, screening out the low-quality image to be detected, only identifying the high-quality image to be detected, and improving the quality of the image to be detected, the accuracy of the fault identification result of the power equipment is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is an overall flow chart of an image verification method for a low-voltage distribution area metering device in the power industry according to the invention;
FIG. 2 is a flow chart of a screening process for an initial set of images;
FIG. 3 is a flow chart of an analysis process of the results of the model analysis.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
The embodiment of the invention provides an image verification method for low-voltage distribution area metering equipment in the power industry, which comprises the following steps:
acquiring an image to be detected of low-voltage transformer area metering equipment in the power industry;
inputting an image to be detected of the metering equipment in the low-voltage transformer area of the power industry into a power image quality analysis model for quality analysis, and outputting an image quality analysis result;
judging whether the image to be detected meets a preset quality standard or not based on the image quality analysis result;
and if the quality meets the preset quality standard, cloud identification is carried out on the image to be detected.
Referring to fig. 1, in this embodiment, first, an image to be detected of a metering device in a low-voltage distribution area in the power industry is acquired through an image acquisition device, the acquired image is input into a preset power image quality analysis model for image quality analysis, and a final image quality analysis result is output, then judging whether the quality of the image meets a preset quality standard, if so, inputting the image to be detected into a cloud end for identification, detecting whether the power equipment has faults, if not, the image to be detected is obtained again, and in this embodiment, before the image to be detected is identified, the quality of the image to be detected is firstly judged, the image to be detected with low quality is screened out, only the image to be detected with high quality is identified, by improving the quality of the image to be detected, the accuracy of the fault identification result of the power equipment is improved.
Based on the method, the power image quality analysis model comprises:
acquiring an initial image set of low-voltage transformer area metering equipment in the power industry;
screening out error images in the initial image set, and forming the residual images into a standard image set;
inputting the standard image set into a network model for image target detection, and extracting power equipment in the standard image set;
calculating the number of pixel points occupied by the electric power equipment and the positions of the pixel points based on the electric power equipment in the extracted standard image set;
performing quality analysis on the image based on the number of the pixel points occupied by the power equipment and the positions of the pixel points, and outputting a model analysis result;
adopting OpenCV computer vision software to carry out uniform reading analysis on the standard data set and outputting a reading analysis result;
and combining the model training result and the reading analysis result into the final output of the power image quality analysis model.
In this embodiment, the penCV computer vision software is used to further read and analyze the sample image, and verify the analysis result of the model, so as to improve the accuracy of the power image quality analysis model. Specifically, an initial image set of metering equipment in a low-voltage distribution area in the power industry is obtained, error images in the initial image set are screened out, the remaining images form a standard image set, images in the standard image set are input into a network model for image target detection, power equipment in the standard image set is extracted, wherein the network model can determine the type and the position of the power equipment, then the proportion of the power equipment in the images and the position of the power equipment in the images are calculated based on the number and the position of pixel points in the area where the power equipment is located, the images are further subjected to quality analysis, model analysis results are output, the standard image set is subjected to unified reading analysis through OpenCV computer vision software, the reading analysis results are output, the model analysis results are verified through the reading analysis results, and the verified output results are used as the final output results of the network model, and finishing the construction of the power image quality analysis model.
Referring to fig. 2, based on the power image quality analysis model, the step of screening the initial image set is as follows:
s1: converting the images in the initial image set into images with the same size;
s2: randomly selecting an image from the initial image set, and acquiring the attribute of the selected image as a first attribute group;
s3: randomly selecting an image from the initial image set, obtaining the attribute of the selected image to compare with the attribute group, if the comparison is passed, dividing the selected image into the attribute group which is passed by the comparison, and if the comparison is not passed, taking the attribute of the selected image as a new attribute group;
s4: repeating the step S3 until all the images in the initial image set are compared;
s5: and selecting the attribute group with the largest number of pictures as a correct image, and screening out error images in other attribute groups to complete the screening of the initial image set.
In this embodiment, image target detection is performed, and an initial image set needs to be screened to delete an error image therein. Specifically, all images in an initial image set are converted into the same size, then an image is randomly selected from the initial image set, the attribute of the selected image is obtained as a first attribute group, wherein the image attributes include image name, image format, image resolution, image size, image color channel, etc., then selecting an image to compare with the existing attribute group in order, if the attributes are the same, dividing the graph into the existing attribute groups, if the comparison is not passed, dividing the image into new attribute groups, sequentially selecting images from the initial image set for attribute comparison, obtaining a plurality of attribute groups after the comparison of all the images in the initial image set is completed, selecting the attribute group with the largest number of images as a standard attribute group, and screening out error images in the other attribute groups, wherein the images in the standard attribute group are the standard image set.
Based on the power image quality analysis model, the specific analysis process of the model analysis result is as follows:
extracting the power equipment in the image by adopting a network model;
if the power equipment in the image is extracted, acquiring the number of pixel points occupied by the power equipment, and calculating the ratio of the number of pixel points occupied by the power equipment to the total number of pixel points of the image;
if the ratio is within the preset threshold range, representing the image pixel points through two-dimensional coordinates, and calculating the distance between the power equipment and the image edge;
if the distance between the power equipment and the edge of the image accords with the preset distance, acquiring edge pixel points of the power equipment to describe the shape of the power equipment, and calculating the similarity between the shape of the power equipment in the image and a preset template;
and if the similarity meets the requirement, outputting a model analysis result.
Referring to fig. 3, in this embodiment, a network model is used to extract the electrical devices in the image, specifically, an input channel of the network model includes a first branch entry and a second branch entry, the image is input into the first branch entry, and the network model identifies the types of the electrical devices in the image and outputs a first result; inputting the image into a second branch inlet, setting three prediction frames by the network model to extract the position of the electric power equipment, and outputting a second result; and splicing the first result and the second result to extract the power equipment in the image. If the power equipment in the image is extracted, acquiring the number of pixel points occupied by the power equipment, calculating the ratio of the number of pixel points occupied by the power equipment to the total number of pixel points of the image, determining the size of the power equipment in the image, if the ratio is within a preset threshold range, representing the image pixel points through two-dimensional coordinates, acquiring the position of the power equipment in the image, wherein the threshold range is 0.3-0.6 in the embodiment, if the position of the power equipment and the edge of the image accords with a preset distance, acquiring edge pixel points of the power equipment to describe the shape of the power equipment, calculating the similarity between the shape of the power equipment in the image and a preset template, calculating the closest distance between the center point of the power equipment and the edge of the image according with the preset distance, and if the calculated distance L is more than or equal to 0.5S +0.1M, then according with the preset distance, the method comprises the steps of obtaining the outline shape of the power equipment, calculating the similarity between the outline shape of the power equipment and the power equipment of the same type in a preset template, judging the integrity of the image of the power equipment, wherein S represents the side length of the power equipment, M represents the side length of the image, then calculating the similarity between the outline shape of the power equipment and the power equipment of the same type in the preset template, in the embodiment, the similarity is larger than 0.7, outputting a model analysis result of the image after the judgment is passed, and if any one of the conditions is not met, ending the analysis process and obtaining the image again.
Based on the power image quality analysis model, the specific process of uniformly reading and analyzing the standard image set by adopting the OpenCV computer vision software is as follows:
storing the standard image set in a unified directory, and numbering sample images in the standard image set in sequence;
sequentially reading sample images based on the sample image numbers, carrying out feature analysis, and classifying the sample images according to analysis results to obtain a sample classification set;
numbering the sample classification sets, specifying the number of sample images of each sample classification set, and stopping putting samples into the sample classification sets when the number of the sample images reaches a specified value;
and taking the image characteristics corresponding to the final classification set of the sample image as a reading analysis result.
In this embodiment, the standard image set is subjected to unified reading analysis by OpenCV computer vision software, so as to obtain a reading analysis result. Specifically, a standard image set is stored in a unified directory, the storage range of sample images is limited, reading by OpenCV computer vision software is facilitated, then the sample images in the standard image set are numbered in sequence, analysis results correspond to the sample images one by one, subsequent statistics of quantity is facilitated, the sample images are subjected to analysis results to obtain sample classification sets, each sample classification set corresponds to one image feature, the quantity of the sample images in the sample classification sets is specified, when the quantity of the sample images reaches a specified value, the samples are stopped being put into the sample classification sets, and the image features corresponding to the finally obtained sample classification sets are used as reading analysis results.
Based on the method, the image quality analysis result comprises: whether the image comprises the power equipment, whether the power equipment in the image is complete, the state of the power equipment in the image and the type of the power equipment in the image.
Further, the above-mentioned judging whether the image to be detected accords with the preset quality standard includes:
reading a quality analysis result of an image to be detected, and judging whether the image analysis result comprises all information;
if the image analysis result does not include all image information, acquiring the image to be detected again;
if the image analysis result comprises all image information, judging that the image information meets the preset standard;
if the image information does not meet the preset standard, acquiring the image to be detected again;
and if the image information meets the preset standard, inputting the image to be detected into a cloud server to perform fault detection on the metering equipment in the low-voltage distribution area in the power industry, and sending a fault analysis result to the mobile terminal.
In this embodiment, the subsequent operation on the image to be detected is determined by determining whether the image meets the preset quality standard. Specifically, reading a quality analysis result of an image to be detected, and judging whether the image analysis result includes all image information, wherein the image quality analysis result includes: whether the image comprises the power equipment, whether the power equipment in the image is complete, the state of the power equipment in the image and the type of the power equipment in the image. If the quality analysis result of the image to be detected does not contain all image information, the image to be detected is obtained again, otherwise, whether the image information of the image to be detected meets the preset standard or not is judged, in the embodiment, whether the image power equipment has defects or not and whether the power equipment needs to be maintained or not is judged through manual judgment. If the image information of the image to be detected does not accord with the preset standard, the image to be detected is obtained again, otherwise, the image to be detected is input into the cloud server to carry out fault detection on the metering equipment in the low-voltage distribution area in the power industry, and a fault analysis result is sent to the mobile terminal.
The embodiment of the invention provides an image verification system for low-voltage distribution room metering equipment in the power industry, which comprises:
the image acquisition module is used for acquiring an image to be detected of the metering equipment in the low-voltage transformer area in the power industry;
the image analysis module is used for inputting the image to be detected of the metering equipment in the low-voltage transformer area of the power industry into the power image quality analysis model for quality analysis and outputting an image quality analysis result;
the result detection module is used for judging whether the image to be detected meets a preset quality standard or not based on the image quality analysis result;
and if the quality meets the preset quality standard, cloud identification is carried out on the image to be detected.
The image verification system for the low-voltage distribution room metering device in the power industry provided by the embodiment and the embodiment of the image verification method for the low-voltage distribution room metering device in the power industry provided by the embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment and is not described herein again.
The embodiment of the invention provides a terminal which comprises a processor and a memory, wherein at least one program code is stored in the memory, and the at least one program code is loaded and executed by the processor to realize the image verification method for the metering equipment in the low-voltage transformer area in the power industry.
The terminal includes: at least one processor, memory, a user interface, and at least one network interface. The various components in the terminal are coupled together by a bus system. It will be appreciated that a bus system is used to enable the connection communication between these components.
The embodiment of the invention provides a computer-readable storage medium, wherein at least one program code is stored in the storage medium, and the at least one program code is loaded and executed by a processor to realize the image verification method for the metering equipment in the low-voltage distribution area in the power industry.
It will be appreciated that the memory can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The memory in the embodiments of the present invention can store data to support the operation of the terminal. Examples of such data include: any computer program for operating on a terminal, such as an operating system and application programs. The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application program may include various application programs.
The present invention is not limited to the above-described embodiments, and those skilled in the art will be able to make various modifications without creative efforts from the above-described conception, and fall within the scope of the present invention.
Claims (10)
1. An image verification method for metering equipment in a low-voltage distribution area in the power industry is characterized by comprising the following steps:
acquiring an image to be detected of low-voltage transformer area metering equipment in the power industry;
inputting an image to be detected of the metering equipment in the low-voltage distribution room of the power industry into the power image quality analysis model for quality analysis, and outputting an image quality analysis result;
judging whether the image to be detected meets a preset quality standard or not based on the image quality analysis result;
and if the quality meets the preset quality standard, cloud identification is carried out on the image to be detected.
2. The method of claim 1, wherein the power image quality analysis model comprises:
acquiring an initial image set of low-voltage transformer area metering equipment in the power industry;
screening out error images in the initial image set, and forming the residual images into a standard image set;
inputting the standard image set into a network model for image target detection, and extracting power equipment in the standard image set;
calculating the number of pixel points occupied by the electric power equipment and the positions of the pixel points based on the electric power equipment in the extracted standard image set;
performing quality analysis on the image based on the number of the pixel points occupied by the power equipment and the positions of the pixel points, and outputting a model analysis result;
adopting OpenCV computer vision software to carry out uniform reading analysis on the standard data set and outputting a reading analysis result;
and combining the model training result and the reading analysis result into the final output of the power image quality analysis model.
3. The method of claim 2, wherein the step of screening the initial image set comprises:
s1: converting the images in the initial image set into images of the same size;
s2: randomly selecting an image from the initial image set, and acquiring the attribute of the selected image as a first attribute group;
s3: randomly selecting an image from the initial image set, obtaining the attribute of the selected image to compare with the attribute group, if the comparison is passed, dividing the selected image into the attribute group which is passed by the comparison, and if the comparison is not passed, taking the attribute of the selected image as a new attribute group;
s4: repeating the step S3 until all the images in the initial image set are compared;
s5: and selecting the attribute group with the largest number of pictures as a correct image, and screening out error images in other attribute groups to complete the screening of the initial image set.
4. The method of claim 2, wherein the specific analysis process of the model analysis result is as follows:
extracting the power equipment in the image by adopting a network model;
if the power equipment in the image is extracted, acquiring the number of pixel points occupied by the power equipment, and calculating the ratio of the number of pixel points occupied by the power equipment to the total number of pixel points of the image;
if the ratio is within the preset threshold range, representing the image pixel point through a two-position coordinate to obtain the position of the power equipment in the image;
if the positions of the power equipment and the image edge accord with the preset distance, acquiring edge pixel points of the power equipment to describe the shape of the power equipment, and calculating the similarity between the shape of the power equipment in the image and a preset template;
and if the similarity meets the requirement, outputting a model analysis result.
5. The method of claim 2, wherein the unified reading analysis of the standard image set by the OpenCV computer vision software is as follows:
storing the standard image set in a unified directory, and numbering sample images in the standard image set in sequence;
sequentially reading sample images based on the sample image numbers, carrying out feature analysis, and classifying the sample images according to analysis results to obtain a sample classification set;
numbering the sample classification sets, specifying the number of sample images of each sample classification set, and stopping putting samples into the sample classification sets when the number of the sample images reaches a specified value;
and taking the image characteristics corresponding to the final classification set of the sample image as a reading analysis result.
6. The method of claim 1, wherein the image quality analysis results comprise: whether the image comprises the power equipment, whether the power equipment in the image is complete, the state of the power equipment in the image and the type of the power equipment in the image.
7. The method of claim 1, wherein the determining whether the image to be detected meets the predetermined quality standard comprises:
reading a quality analysis result of an image to be detected, and judging whether the image analysis result comprises all information;
if the image analysis result does not include all image information, acquiring the image to be detected again;
if the image analysis result comprises all image information, judging that the image information meets the preset standard;
if the image information does not meet the preset standard, acquiring the image to be detected again;
and if the image information meets the preset standard, inputting the image to be detected into a cloud server to perform fault detection on the metering equipment in the low-voltage distribution area in the power industry, and sending a fault analysis result to the mobile terminal.
8. An image verification system for metering equipment in a low-voltage transformer area in the power industry is characterized by comprising:
the image acquisition module is used for acquiring an image to be detected of the metering equipment in the low-voltage transformer area in the power industry;
the image analysis module is used for inputting an image to be detected of the metering equipment in the low-voltage distribution area of the power industry into the power image quality analysis model for quality analysis and outputting an image quality analysis result;
the result detection module is used for judging whether the image to be detected meets a preset quality standard or not based on the image quality analysis result;
and if the quality meets the preset quality standard, cloud identification is carried out on the image to be detected.
9. A terminal comprising a processor and a memory, wherein the memory has stored therein at least one program code, the at least one program code being loaded into and executed by the processor to implement a power industry low voltage area metering device image verification method according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein at least one program code is stored in the storage medium, and the at least one program code is loaded into and executed by a processor to implement a power industry low voltage station area metering device image verification method according to any one of claims 1 to 7.
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|---|---|---|---|---|
| CN115150929A (en) * | 2022-05-30 | 2022-10-04 | 荣耀终端有限公司 | Antenna power adjusting method and device and readable storage medium |
| CN118153971A (en) * | 2024-05-11 | 2024-06-07 | 国网信通亿力科技有限责任公司 | Power consumption safety supervision method and system based on image recognition |
-
2021
- 2021-08-31 CN CN202111012230.6A patent/CN113947564A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115150929A (en) * | 2022-05-30 | 2022-10-04 | 荣耀终端有限公司 | Antenna power adjusting method and device and readable storage medium |
| CN118153971A (en) * | 2024-05-11 | 2024-06-07 | 国网信通亿力科技有限责任公司 | Power consumption safety supervision method and system based on image recognition |
| CN118153971B (en) * | 2024-05-11 | 2024-08-27 | 国网信通亿力科技有限责任公司 | Power consumption safety supervision method and system based on image recognition |
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