CN113989711B - Power distribution construction safety tool use identification method and system - Google Patents
Power distribution construction safety tool use identification method and system Download PDFInfo
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Abstract
The invention provides a method and a system for identifying the use of a power distribution construction safety tool, and belongs to the technical field of computer vision identification. According to the invention, the electric power operation site is monitored in real time, the hand image information, the operating rod image information and the insulating glove image information of the operator are extracted from the monitoring video by utilizing a pre-trained target detection model, and then the wearing condition of the operator on the operating rod and the insulating glove is judged according to the hand image information, the operating rod image information and the hand image information and the insulating glove image information respectively. According to the invention, the power operation site is monitored in real time, and the monitoring video is analyzed, so that the use condition of tools and appliances of operators can be continuously detected. The problem that labor intensity is high and real-time inspection cannot be performed due to manual inspection is avoided.
Description
Technical Field
The invention belongs to the technical field of computer vision recognition, and particularly relates to a power distribution construction safety tool use recognition method and system.
Background
With the increasing demand of electricity energy for production and life, china has generated higher demand for electricity production. The occurrence frequency of the electric power production accidents in China is at a higher level under the influence of various factors, and the safety production of cities is threatened. Therefore, the comprehensive safe production concept must be introduced into the power production operation, so that a guarantee is provided for the normal operation of the power system, the process is complex in the power production operation process, high-voltage power equipment is contacted in the daily inspection and maintenance processes, and safety accidents are easy to occur if the operation is improper or protective equipment is not worn.
To sum up, in order to ensure that electric power staff adopts compliance protective measures and operation flow, improve staff safety protection consciousness, promote on-site safety operation level, traditional mode adopts manual inspection or each operation scene to stand on a supervisor, so that the intensity of labour of inspection staff is big, manufacturing cost is high, each operation scene is far away, most time of inspection staff is wasted on the way, the staff temporarily satisfies inspection staff's requirement, after inspection staff leaves, the staff covet is convenient, does not adopt compliance protective measures. In recent years, with the gradual maturity of computer vision and internet of things technologies, especially the rapid development of neural network technologies, deep learning technologies are beginning to be applied to various production environments. The detection of real-time compliance protective measures on construction sites by adopting deep learning related technology is the current mainstream research direction.
Disclosure of Invention
In view of the above, the invention aims to solve the problems that the labor intensity is high and real-time inspection cannot be performed in the prior art of manually inspecting the power production operation.
In order to solve the technical problems, the invention provides the following technical scheme:
In a first aspect, the invention provides a method for identifying the use of a safety tool for power distribution construction, which comprises the following steps:
acquiring an operation video image of an electric operation site through a camera rtsp, and decoding;
Preprocessing the decoded operation video image, and inputting the preprocessed operation video image into a pre-trained target detection model to obtain the category, rectangular frame coordinates and score of the target output by the target detection model;
Filtering target information output by the target detection model according to the set category and score threshold value to obtain rectangular frame coordinate information of the staff, the operating rod and the insulating glove;
intercepting a worker image area according to rectangular frame coordinate information of a worker, and acquiring hand coordinate information of the worker from the worker image area by utilizing a human body key point detection algorithm;
Intercepting an image area of the operating rod according to rectangular frame coordinate information of the operating rod, detecting the outline of the operating rod, and acquiring outline coordinate information of the operating rod;
And judging whether the worker wears the insulating glove and whether the worker holds the operating rod according to the hand coordinate information of the worker, the rectangular frame coordinate information of the insulating glove and the hand coordinate information of the worker and the outline coordinate information of the operating rod.
Further, preprocessing the decoded job video image specifically includes:
and detecting the quality of the decoded operation video image, and removing black screen, blurring, overexposure and jittering pictures in the operation video image.
Further, the preprocessed operation video image is input into a pre-trained target detection model, so that the category, rectangular frame coordinates and score of the target output by the target detection model are specifically:
And inputting the preprocessed operation video image into a target detection model trained based on the YOLO-v4 algorithm to obtain the category, rectangular frame coordinates and score of the target output by the target detection model.
Further, judging whether the worker wears the insulating glove according to the hand coordinate information of the worker and the rectangular frame coordinate information of the insulating glove specifically comprises:
Acquiring a hand region image and an insulating glove region image according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove;
Calculating the intersection of the hand region image and the insulating glove region image by using the bitwise and functional image and counting the number of white pixels in the intersection;
judging whether the staff wears the insulating glove according to the ratio of the number of the white pixels to the total number of pixels in the intersection.
Further, judging whether the operator holds the operation rod according to the hand coordinate information of the operator and the contour coordinate information of the operation rod specifically comprises:
acquiring a hand area image and an operating rod contour image according to the hand coordinate information of the staff and the contour coordinate information of the operating rod;
Calculating an intersection of the hand area image and the operating rod outline image by using the bitwise and functional image and counting the number of white pixels in the intersection;
Judging whether a worker holds the operating rod according to the ratio of the number of white pixels to the total number of pixels in the intersection.
In a second aspect, the present invention provides a power distribution construction safety tool use identification system, comprising:
the real-time monitoring unit is used for acquiring an operation video image of the electric power operation site through the camera rtsp and decoding the operation video image;
the target detection unit is used for preprocessing the decoded operation video image, and inputting the preprocessed operation video image into a pre-trained target detection model to obtain the category, rectangular frame coordinates and score of the target output by the target detection model;
The target identification unit is used for filtering target information output by the target detection model according to the set category and score threshold value to obtain rectangular frame coordinate information of the staff, the operating rod and the insulating glove;
the hand recognition unit is used for intercepting a worker image area according to the rectangular frame coordinate information of the worker and acquiring the hand coordinate information of the worker from the worker image area by utilizing a human body key point detection algorithm;
The operating rod identification unit is used for intercepting an operating rod image area according to rectangular frame coordinate information of the operating rod, detecting the outline of the operating rod and obtaining outline coordinate information of the operating rod;
The tool use identification unit is used for judging whether the worker wears the insulating glove and whether the worker holds the operating rod according to the hand coordinate information of the worker, the rectangular frame coordinate information of the insulating glove, the hand coordinate information of the worker and the outline coordinate information of the operating rod.
Further, the object detection unit includes: an image preprocessing unit;
the image preprocessing unit is used for detecting the quality of the decoded operation video image and eliminating black screen, blurring, overexposure and jittery pictures in the operation video image.
Further, the object detection unit further includes: an image recognition unit;
The image recognition unit is used for inputting the preprocessed operation video image into the target detection model trained based on the YOLO-v4 algorithm so as to obtain the category, rectangular frame coordinates and score of the target output by the target detection model.
Further, the tool use recognition unit includes: the insulating glove uses an identification unit;
the insulating glove use identification unit is used for acquiring a hand area image and an insulating glove area image according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove;
Calculating the intersection of the hand region image and the insulating glove region image by using the bitwise and functional image and counting the number of white pixels in the intersection;
judging whether the staff wears the insulating glove according to the ratio of the number of the white pixels to the total number of pixels in the intersection.
Further, the tool use recognition unit includes: an operation lever use recognition unit;
The operating rod use identification unit is used for acquiring a hand area image and an operating rod contour image according to the hand coordinate information of the staff and the contour coordinate information of the operating rod;
Calculating an intersection of the hand area image and the operating rod outline image by using the bitwise and functional image and counting the number of white pixels in the intersection;
Judging whether a worker holds the operating rod according to the ratio of the number of white pixels to the total number of pixels in the intersection.
In summary, the invention provides a method and a system for identifying the use of a power distribution construction safety tool, which are used for carrying out real-time monitoring on an electric power operation site, extracting hand image information, operating rod image information and insulating glove image information of an operator by utilizing a pre-trained target detection model on a monitoring video, and further judging the wearing condition of the operator on the operating rod and the insulating glove according to the hand image information, the operating rod image information, the hand image information and the insulating glove image information. According to the invention, the power operation site is monitored in real time, and the monitoring video is analyzed, so that the use condition of tools and appliances of operators can be continuously detected. The problem that labor intensity is high and real-time inspection cannot be performed due to manual inspection is avoided.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for identifying use of a safety tool for power distribution construction according to an embodiment of the present invention;
FIG. 2 is a training schematic diagram of a target detection model according to an embodiment of the present invention;
fig. 3 is a schematic diagram of wearing detection of an operation lever and an insulating glove according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions of 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 apparent that the embodiments described below are only some embodiments of the present invention, not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
With the increasing demand of electricity energy for production and life, china has generated higher demand for electricity production. The occurrence frequency of the electric power production accidents in China is at a higher level under the influence of various factors, and the safety production of cities is threatened. Therefore, the comprehensive safe production concept must be introduced into the power production operation, so that a guarantee is provided for the normal operation of the power system, the process is complex in the power production operation process, high-voltage power equipment is contacted in the daily inspection and maintenance processes, and safety accidents are easy to occur if the operation is improper or protective equipment is not worn.
To sum up, in order to ensure that electric power staff adopts compliance protective measures and operation flow, improve staff safety protection consciousness, promote on-site safety operation level, traditional mode adopts manual inspection or each operation scene to stand on a supervisor, so that the intensity of labour of inspection staff is big, manufacturing cost is high, each operation scene is far away, most time of inspection staff is wasted on the way, the staff temporarily satisfies inspection staff's requirement, after inspection staff leaves, the staff covet is convenient, does not adopt compliance protective measures. In recent years, with the gradual maturity of computer vision and internet of things technologies, especially the rapid development of neural network technologies, deep learning technologies are beginning to be applied to various production environments. The detection of real-time compliance protective measures on construction sites by adopting deep learning related technology is the current mainstream research direction.
Based on the above, the embodiment of the invention provides a power distribution construction safety tool use identification method and system, which are used for solving the problems that the labor intensity is high and real-time inspection cannot be performed when the conventional manual inspection is performed on power production operation.
The following is a detailed description of an embodiment of a method for identifying the use of a safety tool for power distribution construction.
Referring to fig. 1, the embodiment provides a method for identifying use of a safety tool for power distribution construction, which includes:
S100: and acquiring a working video image of the power working site through a camera rtsp, and decoding.
It should be noted that RTSP (REAL TIME STREAMING Protocol) is a real-time streaming Protocol.
And arranging cameras on the electric power operation site, and monitoring the operation site without dead angle coverage. And then the operation video image is obtained in real time through the camera rstp, so that the real-time inspection of operators is realized.
S200: preprocessing the decoded operation video image, and inputting the preprocessed operation video image into a pre-trained target detection model to obtain the category, rectangular frame coordinates and score of the target output by the target detection model.
The decoded image is preprocessed by opencv, and the image quality is detected, and the images of black screen, blurring, overexposure and dithering are removed to obtain the image with qualified quality; inputting the qualified image into a pre-trained target detection model, wherein the pre-trained target detection model can output the category, rectangular frame coordinates and score of the target; the goals required here are: an operator, an operating rod and an insulating glove.
The target detection model in this embodiment may be a target detection model trained based on the YOLO-v4 algorithm. The training process is shown in figure 2, namely, the field operation picture is collected; labeling the field operation pictures, wherein the labeling operation pictures comprise labeling operators, operation rods and insulating gloves; then, carrying out data enhancement processing on the image, including rotation, mirroring, noise increasing and other processing; dividing the processed picture into a training set and a testing set; and modifying the parameters of the YOLO-v4 network to train, and finally obtaining the target detection model based on the YOLO-v 4.
S300: and filtering target information output by the target detection model according to the set category and score threshold value to obtain rectangular frame coordinate information of the staff, the operating rod and the insulating glove.
It should be noted that, judging according to the set score threshold and class, filtering the target information returned by the target detection model, eliminating some suspected targets with scores lower than the score threshold, and finally obtaining rectangular frame coordinate information with classes of operators, operation levers and insulating gloves.
S400: and intercepting a worker image area according to the rectangular frame coordinate information of the worker, and acquiring the hand coordinate information of the worker from the worker image area by utilizing a human body key point detection algorithm.
After the rectangular frame coordinate information of the worker is obtained, the image area of the worker needs to be intercepted, the human body key point detection algorithm is called, the hand coordinate information of the worker is obtained, the obtained hand coordinate is relative to the local image area of the worker, and the hand coordinate relative to the whole image needs to be converted.
S400: and intercepting an image area of the operating rod according to the rectangular frame coordinate information of the operating rod, detecting the outline of the operating rod, and obtaining the outline coordinate information of the operating rod.
In addition, when the coordinate information of the operation lever is obtained, the image area of the operation lever is cut out according to the coordinate information. Because some operation levers are relatively long, when the operation levers are not in a use state, the image has the limitation of a two-dimensional view angle, and the operation levers can cross the human body area, so that an operator can simply consider that the operator holds the operation levers; in order to accurately judge whether an operator holds the operating rod, the contour coordinates of the operating rod need to be extracted, the contour is detected by using findcontours functions of opencv, the contour of the operating rod can be screened out according to a set contour perimeter threshold, and finally the contour coordinates of the operating rod are obtained.
S600: and judging whether the worker wears the insulating glove and whether the worker holds the operating rod according to the hand coordinate information of the worker, the rectangular frame coordinate information of the insulating glove and the hand coordinate information of the worker and the outline coordinate information of the operating rod.
As shown in fig. 3, the specific steps for detecting whether to wear the insulating glove are as follows:
Drawing a hand image of an operator on a blank image A according to the hand coordinates of the operator, drawing an image of the insulating glove on a blank image D according to the rectangular frame coordinates of the insulating glove, calling bitwise _and function of opencv according to the position and the position of the image, calculating the interaction between the image A and the image D to obtain an image E, counting white pixel points of the image E, and finally calculating the proportion of the white pixel points to total pixels of the overlapped image, if the proportion exceeds a set threshold value, judging that the operator wears the insulating glove, otherwise, judging that the operator does not wear the insulating glove, and warning information needs to be sent.
The specific steps of detecting whether to hold the operating lever are as follows:
Drawing a hand image of an operator on a blank image A according to hand coordinates of the operator, drawing an operation rod image on a blank image B according to outline coordinates of the operation rod, calling bitwise _and function of opencv by image bitwise and, calculating the intersection of the image A and the image B to obtain an image C, counting white pixel points of the image C, finally calculating the proportion of the white pixel points to the total pixels of the image, and judging that the operator holds the operation rod if the proportion exceeds a set threshold value, otherwise, judging that the operator does not hold the operation rod and needs to send alarm information.
The embodiment provides a power distribution construction safety tool use identification method, which is characterized in that an electric power operation site is monitored in real time, hand image information, operating rod image information and insulating glove image information of an operator are extracted from a monitoring video by utilizing a pre-trained target detection model, and then wearing conditions of the operator on the operating rod and the insulating glove are judged according to the hand image information, the operating rod image information and the insulating glove image information. According to the invention, the power operation site is monitored in real time, and the monitoring video is analyzed, so that the use condition of tools and appliances of operators can be continuously detected. The problem that labor intensity is high and real-time inspection cannot be performed due to manual inspection is avoided.
The above is a detailed description of an embodiment of a power distribution construction safety tool use identification method of the present invention, and the following is a detailed description of an embodiment of a power distribution construction safety tool use identification system of the present invention.
The embodiment provides a distribution construction safety tool uses identification system, includes: the device comprises a real-time monitoring unit, a target detection unit, an image recognition unit, a target recognition unit, a hand recognition unit, a control rod recognition unit and a tool use recognition unit.
In this embodiment, the real-time monitoring unit is configured to acquire an operation video image of the power operation site through the camera rtsp, and perform decoding;
In this embodiment, the target detection unit is configured to pre-process the decoded operation video image, and input the pre-processed operation video image into a pre-trained target detection model, so as to obtain a class, rectangular frame coordinates and a score of a target output by the target detection model.
It should be noted that the target detection unit further includes: an image recognition unit and an image preprocessing unit.
The image recognition unit is used for inputting the preprocessed operation video image into the target detection model trained based on the YOLO-v4 algorithm so as to obtain the category, rectangular frame coordinates and score of the target output by the target detection model.
The image preprocessing unit is used for detecting the quality of the decoded operation video image and eliminating black screen, blurring, overexposure and jittery pictures in the operation video image.
In this embodiment, the target recognition unit is configured to filter target information output by the target detection model according to the set category and the score threshold, to obtain rectangular frame coordinate information of the staff, the operation lever and the insulating glove;
In this embodiment, the hand recognition unit is configured to intercept a staff image area according to rectangular frame coordinate information of a staff, and acquire hand coordinate information of the staff from the staff image area by using a human body key point detection algorithm;
in this embodiment, the operation lever identification unit is configured to intercept an image area of the operation lever according to rectangular frame coordinate information of the operation lever, detect a contour of the operation lever, and obtain contour coordinate information of the operation lever;
In this embodiment, the tool use identification unit is used for judging whether the worker wears the insulating glove and whether the worker holds the operating lever according to the hand coordinate information of the worker and the rectangular frame coordinate information of the insulating glove and the hand coordinate information of the worker and the outline coordinate information of the operating lever.
The tool use recognition unit includes: the insulating glove use identification unit and the operating lever use identification unit.
The insulating glove use identification unit is used for acquiring a hand area image and an insulating glove area image according to hand coordinate information of a worker and rectangular frame coordinate information of the insulating glove; calculating the intersection of the hand region image and the insulating glove region image by using the bitwise and functional image and counting the number of white pixels in the intersection; judging whether the staff wears the insulating glove according to the ratio of the number of the white pixels to the total number of pixels in the intersection.
The operating rod use identification unit is used for acquiring a hand area image and an operating rod contour image according to the hand coordinate information of the staff and the contour coordinate information of the operating rod; calculating an intersection of the hand area image and the operating rod outline image by using the bitwise and functional image and counting the number of white pixels in the intersection; judging whether a worker holds the operating rod according to the ratio of the number of white pixels to the total number of pixels in the intersection.
The embodiment provides a distribution construction safety tool uses identification system, realizes the uninterrupted real-time supervision to electric power field operation through real-time supervision unit to still use identification unit to discernment control video through the action bars, automatic judgement operating personnel to the service condition of safety tool. The manpower inspection cost is saved, and the inspection efficiency is improved.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. The utility model provides a distribution construction safety tool uses identification method which characterized in that includes the following steps:
acquiring an operation video image of an electric operation site through a camera rtsp, and decoding;
preprocessing the decoded operation video image, and inputting the preprocessed operation video image into a pre-trained target detection model to obtain the category, rectangular frame coordinates and score of the target output by the target detection model;
Filtering target information output by the target detection model according to the set category and score threshold value to obtain rectangular frame coordinate information of staff, an operating rod and the insulating glove;
intercepting a worker image area according to rectangular frame coordinate information of a worker, and acquiring hand coordinate information of the worker from the worker image area by utilizing a human body key point detection algorithm;
Intercepting an image area of the operating rod according to rectangular frame coordinate information of the operating rod, detecting the outline of the operating rod, and acquiring outline coordinate information of the operating rod;
judging whether the staff wears the insulating glove or not and whether the staff holds the operating rod or not according to the hand coordinate information of the staff, the rectangular frame coordinate information of the insulating glove, the hand coordinate information of the staff and the outline coordinate information of the operating rod;
Inputting the preprocessed operation video image into a pre-trained target detection model to obtain the category, rectangular frame coordinates and score of the target output by the target detection model, wherein the category, rectangular frame coordinates and score are specifically as follows:
Inputting the preprocessed operation video image into a target detection model trained based on a YOLO-v4 algorithm to obtain the category, rectangular frame coordinates and score of a target output by the target detection model;
judging whether the staff wears the insulating glove according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove specifically comprises:
Acquiring a hand region image and an insulating glove region image according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove;
Calculating an intersection of the hand region image and the insulating glove region image by using the image bitwise and function, and counting white pixel points in the intersection;
Judging whether a worker wears insulating gloves or not according to the ratio of the number of the white pixels to the total number of pixels in the intersection;
judging whether the staff wears the insulating glove according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove specifically comprises:
Acquiring a hand region image and an insulating glove region image according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove;
Calculating an intersection of the hand region image and the insulating glove region image by using the image bitwise and function, and counting white pixel points in the intersection;
Judging whether a worker wears the insulating glove according to the ratio of the number of the white pixels to the total number of pixels in the intersection, wherein the image bit-wise AND function is bitwise _AND function of opencv.
2. The method for identifying the use of a safety tool for power distribution construction according to claim 1, wherein the preprocessing the decoded operation video image specifically comprises:
And detecting the quality of the decoded operation video image, and removing black screen, blurring, overexposure and jittery pictures in the operation video image.
3. A power distribution construction safety tool use identification system, comprising:
the real-time monitoring unit is used for acquiring an operation video image of the electric power operation site through the camera rtsp and decoding the operation video image;
The target detection unit is used for preprocessing the decoded operation video image, inputting the preprocessed operation video image into a pre-trained target detection model to obtain the category, rectangular frame coordinates and score of the target output by the target detection model;
The target identification unit is used for filtering target information output by the target detection model according to the set category and score threshold value to obtain rectangular frame coordinate information of the staff, the operating rod and the insulating glove;
The hand recognition unit is used for intercepting a worker image area according to rectangular frame coordinate information of the worker and acquiring hand coordinate information of the worker from the worker image area by utilizing a human body key point detection algorithm;
The operating rod identification unit is used for intercepting an operating rod image area according to rectangular frame coordinate information of the operating rod, detecting the outline of the operating rod and obtaining outline coordinate information of the operating rod;
The tool use identification unit is used for judging whether the worker wears the insulating glove or not and whether the worker holds the operating rod or not according to the hand coordinate information of the worker, the rectangular frame coordinate information of the insulating glove, the hand coordinate information of the worker and the outline coordinate information of the operating rod;
the object detection unit further includes: an image recognition unit;
the image recognition unit is used for inputting the preprocessed operation video image into a target detection model trained based on a YOLO-v4 algorithm so as to obtain the category, rectangular frame coordinates and score of the target output by the target detection model;
the tool use recognition unit includes: the insulating glove uses an identification unit;
the insulating glove use identification unit is used for acquiring a hand area image and an insulating glove area image according to the hand coordinate information of the staff and the rectangular frame coordinate information of the insulating glove;
Calculating an intersection of the hand region image and the insulating glove region image by using the image bitwise and function, and counting white pixel points in the intersection;
Judging whether a worker wears insulating gloves or not according to the ratio of the number of the white pixels to the total number of pixels in the intersection;
the tool use recognition unit includes: an operation lever use recognition unit;
The operating rod use identification unit is used for acquiring a hand area image and an operating rod contour image according to the hand coordinate information of the staff and the contour coordinate information of the operating rod;
Calculating an intersection of the hand area image and the operating rod outline image by using the bitwise and functional image and counting the number of white pixels in the intersection;
Judging whether a worker holds the operation rod according to the ratio of the number of the white pixels to the total number of pixels in the intersection, wherein the image bit-wise AND function is bitwise _AND function of opencv.
4. A power distribution construction safety tool use identification system according to claim 3, wherein the target detection unit comprises: an image preprocessing unit;
The image preprocessing unit is used for detecting the quality of the decoded operation video image and removing black screen, blurring, overexposure and jittery pictures in the operation video image.
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| CN114971983B (en) * | 2022-05-18 | 2024-06-04 | 国网安徽省电力有限公司安庆供电公司 | Electric power marketing operation scene management and control system based on intelligent helmet |
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| CN111222478A (en) * | 2020-01-11 | 2020-06-02 | 深圳奥腾光通系统有限公司 | Construction site safety protection detection method and system |
| CN113313186A (en) * | 2021-06-09 | 2021-08-27 | 广东电网有限责任公司 | Method and system for identifying non-standard wearing work clothes |
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