CN113033393B - Thermal power station personnel operation safety monitoring system and method based on machine vision - Google Patents
Thermal power station personnel operation safety monitoring system and method based on machine vision Download PDFInfo
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- CN113033393B CN113033393B CN202110314798.7A CN202110314798A CN113033393B CN 113033393 B CN113033393 B CN 113033393B CN 202110314798 A CN202110314798 A CN 202110314798A CN 113033393 B CN113033393 B CN 113033393B
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Abstract
The invention discloses a thermal power station personnel operation safety monitoring system and method based on machine vision. The method comprises the following steps: acquiring an operation behavior image; processing the operation behavior image to obtain a background characteristic image; processing the operation behavior image to obtain an operation behavior characteristic image; determining a job scene type corresponding to the background characteristic image according to the mapping relation between the job scene type and the job scene image set; judging whether the maximum value of the matching value of the operation behavior characteristic image and each image in a front violation operation behavior image set corresponding to the determined operation scene type exceeds a preset threshold value, and if so, outputting a violation level corresponding to the corresponding front violation operation behavior image; and outputting an early warning instruction of a corresponding grade according to the violation grade. The system comprises all functional modules which realize the steps in a one-to-one correspondence mode. According to the invention, the problem that the existing thermal power enterprise personnel operation safety monitoring system cannot perform early warning in advance can be solved.
Description
Technical Field
The invention belongs to the field of safety monitoring, and particularly relates to a thermal power station personnel operation safety monitoring system and method based on machine vision.
Background
The thermal power enterprises are responsible for electric energy production and transmission, and provide basic energy for national economic development and daily work and study of people. The safe production of the thermal power enterprise relates to the events of economic loss and social negative influence caused by casualties, equipment damage, unplanned power failure, power quality reduction and the like in the whole production process. The safety production plays a very important role in thermal power enterprises and is a foundation stone for enterprise management. As a high-risk industry, a certain loss is caused to a power grid system in any link or personnel safety accidents in the production process in the thermal power industry. In many factors causing accidents of thermal power enterprises, human safety factors play a main role, and particularly, due to the fact that personal safety awareness is weak, and the number of illegal operation phenomena is large, many potential safety hazards appear in the production process of some employees. Therefore, safety management needs to be performed on thermal power enterprise employees, the passive situation of the conventional safety management is improved, and the controllability of thermal power production is realized. The staff safety monitoring system is required to be established through behavior recognition technology by enhancing education and improving staff safety awareness, the defects of the traditional management method are overcome, the staff position condition is mastered in real time through modern technical means, the staff can be guaranteed to be self-restrained, and the safety management level of thermal power enterprises is improved.
At present, the existing thermal power enterprise personnel operation safety monitoring system is generally implemented based on an image recognition technology, and the thermal power enterprise personnel operation safety monitoring system compares an obtained operation behavior image with an illegal operation behavior image in an illegal operation behavior image library one by one to determine whether the current operation behavior belongs to a specified illegal operation behavior or not, so that safety monitoring is implemented. However, the personnel operation safety monitoring system for the thermal power enterprises can only realize in-service monitoring and cannot realize advance early warning.
Disclosure of Invention
The invention aims to solve the problem that the existing thermal power enterprise personnel operation safety monitoring system cannot realize early warning in advance.
In order to achieve the purpose, the invention provides a thermal power station personnel operation safety monitoring system and method based on machine vision.
According to a first aspect of the invention, a thermal power station personnel operation safety monitoring system based on machine vision is provided, and comprises the following functional modules:
the system comprises a front-mounted violation behavior database, a front-mounted violation behavior database and a front-mounted violation behavior image processing module, wherein the front-mounted violation behavior database comprises a job scene type, a job scene image set, a mapping relation between a front-mounted violation behavior image set and a violation level corresponding to each front-mounted violation behavior image in the set, and the front-mounted violation behavior image is a front-mounted image on a time domain of the corresponding violation behavior image;
the operation behavior image acquisition module is used for acquiring an operation behavior image;
the first image processing module is used for carrying out preset processing operation on the acquired operation behavior image to obtain a background characteristic image;
the second image processing module is used for carrying out preset processing operation on the acquired operation behavior image to obtain an operation behavior characteristic image;
the operation scene determining module is used for determining the operation scene type corresponding to the background characteristic image according to the mapping relation between the operation scene type and the operation scene image set;
the behavior judgment module is used for judging whether the maximum value of the matching value of each image in the operation behavior feature image and the preset violation operation behavior image set corresponding to the determined job scene type exceeds a preset threshold value or not, and if yes, outputting the violation level corresponding to the preset violation operation behavior image with the highest matching degree with the operation behavior feature image;
and the violation operation behavior early warning module is used for outputting an early warning instruction of a corresponding level according to the violation level corresponding to the preposed violation operation behavior image with the highest matching degree with the operation behavior characteristic image.
Preferably, the violation level corresponding to the pre-violation behavior image is determined based on an overall risk value of the corresponding pre-violation behavior, where the overall risk value of the pre-violation behavior is a product of a risk value of the job scene type, a time-domain distance between the pre-violation behavior image and the corresponding violation behavior image, and a risk value of the violation behavior corresponding to the corresponding violation behavior image.
Preferably, the operation behavior image acquisition module performs image acquisition in response to a moving object within a field of view thereof.
Preferably, the specific manner of determining the job scene type corresponding to the background feature image by the job scene determination module is as follows:
acquiring a matching value of the background characteristic image and each job scene image in each job scene image set;
and taking the job scene type corresponding to the job scene image set in which the job scene image with the highest matching degree with the background characteristic image is positioned as the job scene type corresponding to the background characteristic image.
Preferably, the thermal power station personnel operation safety monitoring system further comprises:
and the early warning execution module is used for executing early warning actions based on a preset early warning strategy according to the received early warning instruction.
Preferably, the illegal operation behavior corresponding to the illegal operation behavior image includes: the method comprises the following steps of carrying out illegal operation on production equipment by staff, carrying out necessary safety protection measures, carrying out operation by using hands instead of tools, not storing used appliances at specified positions, entering dangerous areas without permission, crossing guardrails or climbing in an unsafe environment, stopping behaviors in a hoisting environment, improper maintenance behaviors of equipment, attention-deficit behaviors, unsafe behaviors of loading staff and improper behaviors of handling flammable and explosive materials.
Preferably, the processing operations of the first image processing module include graying, geometric transformation, image enhancement, and feature extraction.
Preferably, the processing operations of the second image processing module include graying, geometric transformation, image enhancement, and feature extraction.
Preferably, the behavior determination module is implemented based on a neural network model.
According to a second aspect of the invention, a thermal power station personnel operation safety monitoring method based on machine vision is provided, and is realized based on a preposed violation behavior database, wherein the database comprises a job scene type, a job scene image set, a preposed violation behavior image set and a mapping relation of violation levels corresponding to each preposed violation behavior image in the set, and the preposed violation behavior image is a preposed image on a time domain of a corresponding violation behavior image;
the thermal power station personnel operation safety monitoring method comprises the following steps:
acquiring an operation behavior image;
performing preset processing operation on the acquired operation behavior image to obtain a background characteristic image;
performing preset processing operation on the acquired operation behavior image to obtain an operation behavior characteristic image;
determining a job scene type corresponding to the background characteristic image according to the mapping relation between the job scene type and the job scene image set;
judging whether the maximum value of the matching value of the operation behavior characteristic image and each image in a front violation operation behavior image set corresponding to the determined operation scene type exceeds a preset threshold value, and if so, outputting a violation level corresponding to the front violation operation behavior image with the highest matching degree with the operation behavior characteristic image;
and outputting early warning instructions of corresponding levels according to the violation levels corresponding to the prepositive violation behavior images with the highest matching degree with the operation behavior characteristic images.
The invention has the beneficial effects that:
the thermal power station personnel operation safety monitoring system based on machine vision acquires an operation behavior image through an operation behavior image acquisition module, performs preset processing operation on the acquired operation behavior image through a first image processing module to obtain a background characteristic image, performs preset processing operation on the acquired operation behavior image through a second image processing module to obtain an operation behavior characteristic image, determines an operation scene type corresponding to the background characteristic image through an operation scene determination module according to the mapping relation between the operation scene type and an operation scene image set, judges whether the maximum value of the matching value of each image in a front violation operation behavior image set corresponding to the operation behavior characteristic image and the determined operation scene type exceeds a preset threshold value through a behavior judgment module, and outputs a violation operation behavior image corresponding to the front violation operation behavior image with the highest matching degree with the operation behavior characteristic image if the maximum value exceeds the preset threshold value And the level is that an early warning instruction of the corresponding level is output through an illegal operation behavior early warning module according to the illegal level corresponding to the preposed illegal operation behavior image with the highest matching degree with the operation behavior characteristic image.
Compared with the existing thermal power enterprise personnel operation safety monitoring system, the thermal power station personnel operation safety monitoring system based on machine vision realizes early warning in advance by introducing the concept of preposed illegal operation behaviors.
The thermal power station personnel operation safety monitoring method based on the machine vision and the thermal power station personnel operation safety monitoring system based on the machine vision belong to a general invention concept, so the thermal power station personnel operation safety monitoring method based on the machine vision has the same beneficial effects as the thermal power station personnel operation safety monitoring system based on the machine vision.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
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The above and other objects, features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings, wherein like reference numerals generally represent like parts in the exemplary embodiments of the present invention.
FIG. 1 shows a block diagram of a thermal power station personnel operation safety monitoring system based on machine vision according to an embodiment of the invention;
fig. 2 shows a flow chart of implementation of a thermal power station personnel operation safety monitoring method based on machine vision according to an embodiment of the invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Example (b): fig. 1 shows a block diagram of a thermal power station personnel operation safety monitoring system based on machine vision according to an embodiment of the invention. Referring to fig. 1, the thermal power station personnel operation safety monitoring system based on machine vision of the embodiment includes the following functional modules:
the system comprises a front-mounted violation behavior database, a front-mounted violation behavior database and a front-mounted violation behavior image processing module, wherein the front-mounted violation behavior database comprises a job scene type, a job scene image set, a mapping relation between a front-mounted violation behavior image set and a violation level corresponding to each front-mounted violation behavior image in the set, and the front-mounted violation behavior image is a front-mounted image on a time domain of the corresponding violation behavior image;
the operation behavior image acquisition module is used for acquiring an operation behavior image;
the first image processing module is used for carrying out preset processing operation on the acquired operation behavior image to obtain a background characteristic image;
the second image processing module is used for carrying out preset processing operation on the acquired operation behavior image to obtain an operation behavior characteristic image;
the operation scene determining module is used for determining the operation scene type corresponding to the background characteristic image according to the mapping relation between the operation scene type and the operation scene image set;
the behavior judgment module is used for judging whether the maximum value of the matching value of each image in the operation behavior feature image and the preset violation operation behavior image set corresponding to the determined job scene type exceeds a preset threshold value or not, and if yes, outputting the violation level corresponding to the preset violation operation behavior image with the highest matching degree with the operation behavior feature image;
and the violation operation behavior early warning module is used for outputting an early warning instruction of a corresponding level according to the violation level corresponding to the preposed violation operation behavior image with the highest matching degree with the operation behavior characteristic image.
In this embodiment, the violation level corresponding to the pre-violation-operation-behavior image is determined based on the overall risk value of the corresponding pre-violation-operation behavior, where the overall risk value of the pre-violation-behavior is a product of the risk value of the job scene type, the time-domain distance between the pre-violation-behavior image and the corresponding violation-operation-behavior image, and the risk value of the violation-operation behavior corresponding to the corresponding violation-operation-behavior image.
In this embodiment, the operation behavior image acquisition module acquires an image in response to a moving object within a viewing range of the operation behavior image acquisition module.
In this embodiment, the specific manner of determining the job scene type corresponding to the background feature image by the job scene determining module is as follows:
acquiring a matching value of the background feature image and each operation scene image in each operation scene image set;
and taking the job scene type corresponding to the job scene image set in which the job scene image with the highest matching degree with the background characteristic image is positioned as the job scene type corresponding to the background characteristic image.
The thermal power station personnel operation safety monitoring system of this embodiment still includes:
and the early warning execution module is used for executing early warning actions based on a preset early warning strategy according to the received early warning instruction.
In this embodiment, the illegal operation behavior corresponding to the illegal operation behavior image includes: the method comprises the following steps of carrying out illegal operation on production equipment by staff, carrying out necessary safety protection measures, carrying out operation by using hands instead of tools, not storing used appliances at specified positions, entering dangerous areas without permission, crossing guardrails or climbing in an unsafe environment, stopping behaviors in a hoisting environment, improper maintenance behaviors of equipment, attention-deficit behaviors, unsafe behaviors of loading staff and improper behaviors of handling flammable and explosive materials.
In this embodiment, the processing operation of the second image processing module includes graying, geometric transformation, image enhancement, and feature extraction.
In this embodiment, the behavior determination module is implemented based on a neural network model.
Fig. 2 shows a flow chart of implementation of a thermal power station personnel operation safety monitoring method based on machine vision according to an embodiment of the invention. Referring to fig. 2, the thermal power station personnel operation safety monitoring method based on machine vision of the embodiment is implemented based on a pre-violation behavior database, the database includes a mapping relationship between a job scene type, a job scene image set, a pre-violation behavior image set and violation levels corresponding to each pre-violation behavior image in the set, and the pre-violation behavior images are pre-images of corresponding violation behavior images in a time domain;
the thermal power station personnel operation safety monitoring method comprises the following steps:
s100, acquiring an operation behavior image;
step S200, performing preset processing operation on the acquired operation behavior image to obtain a background characteristic image;
step S300, performing preset processing operation on the acquired operation behavior image to obtain an operation behavior characteristic image;
s400, determining a job scene type corresponding to the background characteristic image according to the mapping relation between the job scene type and the job scene image set;
step S500, judging whether the maximum value of the matching value of the operation behavior characteristic image and each image in a front violation operation behavior image set corresponding to the determined job scene type exceeds a preset threshold value, and if yes, outputting a violation level corresponding to the front violation operation behavior image with the highest matching degree with the operation behavior characteristic image;
and S600, outputting early warning instructions of corresponding levels according to the violation level corresponding to the preposed violation operation behavior image with the highest matching degree with the operation behavior feature image.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.
Claims (10)
1. Thermal power station personnel operation safety monitoring system based on machine vision, its characterized in that includes:
the system comprises a front-mounted violation behavior database, a front-mounted violation behavior database and a front-mounted violation behavior image processing module, wherein the front-mounted violation behavior database comprises a job scene type, a job scene image set, a mapping relation between a front-mounted violation behavior image set and a violation level corresponding to each front-mounted violation behavior image in the set, and the front-mounted violation behavior image is a front-mounted image on a time domain of the corresponding violation behavior image;
the operation behavior image acquisition module is used for acquiring an operation behavior image;
the first image processing module is used for carrying out preset processing operation on the acquired operation behavior image to obtain a background characteristic image;
the second image processing module is used for carrying out preset processing operation on the acquired operation behavior image to obtain an operation behavior characteristic image;
the operation scene determining module is used for determining the operation scene type corresponding to the background characteristic image according to the mapping relation between the operation scene type and the operation scene image set;
the behavior judgment module is used for judging whether the maximum value of the matching value of each image in the operation behavior feature image and the preset violation operation behavior image set corresponding to the determined job scene type exceeds a preset threshold value or not, and if yes, outputting the violation level corresponding to the preset violation operation behavior image with the highest matching degree with the operation behavior feature image;
and the violation operation behavior early warning module is used for outputting an early warning instruction of a corresponding level according to the violation level corresponding to the prepositive violation operation behavior image with the highest matching degree with the operation behavior characteristic image.
2. The thermal power station personnel operation safety monitoring system according to claim 1, wherein the violation level corresponding to the pre-violation behavior image is determined based on a corresponding overall risk value of the pre-violation behavior, and the overall risk value of the pre-violation behavior is a product of a risk value of a job scene type, a time-domain distance between the pre-violation behavior image and the corresponding violation behavior image, and a risk value of the violation behavior corresponding to the corresponding violation behavior image.
3. The thermal power station personnel operation safety monitoring system according to claim 1, wherein the operation behavior image acquisition module performs image acquisition in response to a moving object within a viewing range of the operation behavior image acquisition module.
4. The thermal power station personnel operation safety monitoring system according to claim 1, wherein the specific manner of determining the operation scene type corresponding to the background characteristic image by the operation scene determining module is as follows:
acquiring a matching value of the background characteristic image and each job scene image in each job scene image set;
and taking the job scene type corresponding to the job scene image set in which the job scene image with the highest matching degree with the background characteristic image is positioned as the job scene type corresponding to the background characteristic image.
5. The thermal power station personnel operation safety monitoring system of claim 1, further comprising:
and the early warning execution module is used for executing early warning actions based on a preset early warning strategy according to the received early warning instruction.
6. The thermal power station personnel operation safety monitoring system according to claim 1, wherein the illegal operation behavior corresponding to the illegal operation behavior image comprises: the method comprises the following steps of carrying out illegal operation on production equipment by staff, carrying out necessary safety protection measures, carrying out operation by using hands instead of tools, not storing used appliances at specified positions, entering dangerous areas without permission, crossing guardrails or climbing in an unsafe environment, stopping behaviors in a hoisting environment, improper maintenance behaviors of equipment, attention-deficit behaviors, unsafe behaviors of loading staff and improper behaviors of handling flammable and explosive materials.
7. The thermal power station personnel operation safety monitoring system according to claim 1, wherein the processing operation of the first image processing module comprises graying, geometric transformation, image enhancement and feature extraction.
8. The thermal power station personnel operation safety monitoring system according to claim 1, wherein the processing operations of the second image processing module comprise graying, geometric transformation, image enhancement and feature extraction.
9. The thermal power station personnel operation safety monitoring system of claim 1, characterized in that the behavior judgment module is implemented based on a neural network model.
10. The thermal power station personnel operation safety monitoring method based on machine vision is characterized by being realized based on a preposed violation behavior database, wherein the database comprises a mapping relation among a job scene type, a job scene image set, a preposed violation behavior image set and violation levels corresponding to all preposed violation behavior images in the set, and the preposed violation behavior images are preposed images of corresponding violation behavior images in a time domain;
the thermal power station personnel operation safety monitoring method comprises the following steps:
acquiring an operation behavior image;
performing predetermined processing operation on the acquired operation behavior image to obtain a background characteristic image;
performing preset processing operation on the acquired operation behavior image to obtain an operation behavior characteristic image;
determining a job scene type corresponding to the background characteristic image according to the mapping relation between the job scene type and the job scene image set;
judging whether the maximum value of the matching value of the operation behavior feature image and each image in a front illegal operation behavior image set corresponding to the determined operation scene type exceeds a preset threshold value, and if so, outputting an illegal level corresponding to the front illegal operation behavior image with the highest matching degree with the operation behavior feature image;
and outputting early warning instructions of corresponding levels according to the violation level corresponding to the preposed violation operation behavior image with the highest matching degree with the operation behavior characteristic image.
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| CN114021969B (en) * | 2021-11-04 | 2022-06-07 | 中国安全生产科学研究院 | Agricultural enterprise safety production risk index analysis system |
| CN113792373B (en) * | 2021-11-17 | 2022-02-22 | 中化学建设投资集团北京科贸有限公司 | Personnel behavior monitoring emergency disposal method based on machine vision |
| CN117557201B (en) * | 2024-01-12 | 2024-04-12 | 国网山东省电力公司菏泽供电公司 | Intelligent warehouse safety management system and method based on artificial intelligence |
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