Coal mine potential safety hazard evaluation method and system based on image data identification

Abstract

The invention discloses a coal mine potential safety hazard evaluation method and system based on image data recognition, and the method comprises the steps: determining a plurality of working processes of coal mine operation, obtaining the safety factor of each working process, and determining a key monitoring region according to the safety factors; collecting an area image of each key monitoring area, extracting a plurality of monitoring objects from the area image, and determining the current state of each monitoring object; determining a plurality of violation parameters based on the current state of each monitored object, and determining a potential safety hazard type according to the violation parameters; and determining a coal mine improvement direction according to the potential safety hazard type and generating and displaying an improvement plan. The method can effectively carry out the key monitoring of an area with a large number of potential safety hazards, and improves the monitoring efficiency. The monitoring object in the monitoring image and the current state of the monitoring object are automatically judged, and then the violation parameters are determined to evaluate the potential safety hazard type, so that each safety threat factor in the monitoring vision can be intelligently monitored to ensure the safety to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine safety early warning, and in particular to a method and system for evaluating coal mine safety hazards based on image data recognition. Background Art

[0002] At present, the coal mining industry is restricted and affected by the geological environment. The working environment of mines is harsh and complex. The safety management level in the coal mining industry is insufficient. The overall quality of employees varies. The coal industry has always been a high-incidence area for accidents. The safety production situation is extremely severe. Safety production is the eternal theme of coal mining enterprises and a prerequisite for achieving high-quality and sustainable development of enterprises. Coal mine safety production is greatly constrained by natural conditions. The geological structure and coal seam conditions determine that different development and mining methods must be adopted, and many natural disasters are brought about, such as gas, coal dust explosions, mine fires, roof collapse, mine water seepage, etc. These hidden dangers with coal mine attributes have become potential factors for accidents. The current safety monitoring system usually monitors all areas in the coal mine manually, which not only wastes a lot of manpower costs but also monitors unimportant areas, reducing monitoring efficiency. At the same time, the final hidden danger assessment results are subjective and cannot guarantee objectivity. Summary of the invention

[0003] In response to the above-mentioned problems, the present invention provides a coal mine safety hazard evaluation method and system based on image data recognition to solve the problem mentioned in the background technology that the current safety monitoring system usually performs manual monitoring of all areas in the coal mine, which not only wastes a lot of manpower costs but also monitors unimportant areas, reducing the monitoring efficiency. At the same time, the final hazard assessment results are subjective and cannot guarantee objectivity.

[0004] A method for evaluating safety hazards in coal mines based on image data recognition comprises the following steps:

[0005] Identify multiple work processes of coal mine operations, obtain the safety factors of each work process, and determine the key monitoring areas based on the safety factors;

[0006] Collecting a regional image of each key monitoring area, extracting multiple monitoring objects from the regional image and determining the current state of each monitoring object;

[0007] Determine multiple violation parameters based on the current status of each monitored object, and determine the type of potential safety hazard based on the violation parameters;

[0008] Determine the direction of coal mine improvement based on the type of safety hazard and generate an improvement plan for display.

[0009] Preferably, the determining of multiple work processes of coal mine operations, obtaining safety factors of each work process, and determining key monitoring areas according to the safety factors include:

[0010] Determine multiple operation areas of the coal mine, obtain the operation attributes of each operation area, and determine multiple work processes of the coal mine operation according to the operation attributes;

[0011] Obtain the personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters of each workflow;

[0012] Conduct safety risk assessment for each workflow based on personnel demand parameters, equipment demand parameters, scene environment demand parameters, and operation demand parameters, and determine the hazard sources in each workflow based on the assessment results;

[0013] Determine the safety factors in each workflow based on the hazard sources, and take the target operation area corresponding to the target workflow where the number of safety factors is greater than or equal to the preset threshold as the key monitoring area.

[0014] Preferably, the collecting of the regional image of each key monitoring area, extracting multiple monitoring objects from the regional image and determining the current state of each monitoring object includes:

[0015] Determine the regional boundaries and monitoring equipment layout of each key monitoring area, and determine the monitoring coverage index of each key monitoring area based on the regional boundaries and camera layout;

[0016] The monitoring equipment of each key monitoring area is optimized according to the monitoring coverage index. After the optimization is completed, multiple regional images of each key monitoring area at different angles are collected;

[0017] Determine multiple object types from the regional image, and extract multiple monitoring objects from the regional image according to the object types by feature matching, wherein the monitoring objects include: personnel, machines, and instruments and equipment;

[0018] The regional image is scanned to determine the independent working state and the cyclic working state of each monitored object.

[0019] Preferably, the determining of a plurality of violation parameters based on the current state of each monitored object and determining the type of potential safety hazard according to the violation parameters include:

[0020] Determine a plurality of abnormal features according to the current state of each monitored object, wherein the abnormal features include: abnormal wearing features, abnormal running features, and abnormal operation features;

[0021] Compare multiple abnormal features with standard features, determine the deviation between the abnormal features and the standard features based on the comparison results, and judge whether the current state of each monitored object meets the violation standard based on the deviation;

[0022] If so, obtain the state description parameters corresponding to the current state, and determine the object violation parameters according to the state description parameters and the standard state parameters;

[0023] Determine the associated mapping risk keywords of the illegal parameters, and determine the potential security risk type according to the associated mapping risk keywords.

[0024] Preferably, determining the improvement direction of the coal mine according to the type of potential safety hazard and generating an improvement plan for display includes:

[0025] Determine the starting condition parameters of the safety hazard type, and determine the improvement direction for each safety hazard type based on the starting condition parameters;

[0026] Determine multiple improvement-related entities according to the improvement direction, and generate an improvement plan for each improvement-related entity;

[0027] Combine the improvement plans of each improvement-related subject to generate an improvement plan for each type of safety hazard;

[0028] Organize the improvement plans, obtain user improvement requirements, screen the improvement plans according to the improvement requirements, and display the screened contents in a predetermined form.

[0029] A coal mine safety hazard evaluation system based on image data recognition, the system comprising:

[0030] The first determination module is used to determine multiple work processes of coal mine operations, obtain the safety factors of each work process, and determine the key monitoring areas according to the safety factors;

[0031] A second determination module is used to collect a regional image of each key monitoring area, extract multiple monitoring objects from the regional image and determine the current state of each monitoring object;

[0032] A third determination module is used to determine a plurality of violation parameters based on the current state of each monitored object, and determine the type of potential safety hazard according to the violation parameters;

[0033] The generation module is used to determine the improvement direction of the coal mine according to the type of safety hazards and generate improvement plans for display.

[0034] Preferably, the first determining module includes:

[0035] The first determination submodule is used to determine multiple operation areas of the coal mine, obtain the operation attributes of each operation area, and determine multiple work processes of the coal mine operation according to the operation attributes;

[0036] The acquisition submodule is used to obtain the personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters of each workflow;

[0037] The assessment submodule is used to conduct a safety risk assessment for each workflow based on personnel demand parameters, equipment demand parameters, scene environment demand parameters, and operation demand parameters, and determine the hazard source in each workflow based on the assessment results;

[0038] The second determination submodule is used to determine the safety factors in each workflow according to the hazard source, and to take the target operation area corresponding to the target workflow with the number of safety factors greater than or equal to a preset threshold as the key monitoring area.

[0039] Preferably, the second determining module includes:

[0040] The third determination submodule is used to determine the regional boundaries and monitoring equipment layout of each key monitoring area, and determine the monitoring coverage index of each key monitoring area according to the regional boundaries and camera layout;

[0041] The acquisition submodule is used to optimize the monitoring equipment of each key monitoring area according to the monitoring coverage index. After the optimization is completed, multiple regional images of each key monitoring area at different angles are collected;

[0042] An extraction submodule, used to determine multiple object types from the regional image, and extract multiple monitoring objects from the regional image according to the object types by feature matching, wherein the monitoring objects include: personnel, machines, and instruments and equipment;

[0043] The fourth determination submodule is used to scan the regional image to determine the independent working state and the cyclic working state of each monitored object.

[0044] Preferably, the third determination module includes:

[0045] A fifth determination submodule is used to determine a plurality of abnormal features according to the current state of each monitored object, wherein the abnormal features include: abnormal wearing features, abnormal running features, and abnormal operation features;

[0046] The judgment submodule is used to compare multiple abnormal features with standard features, determine the deviation between the abnormal features and the standard features according to the comparison results, and judge whether the current state of each monitored object meets the violation standard according to the deviation;

[0047] A sixth determination submodule, for, if yes, obtaining a state description parameter corresponding to the current state, and determining the object violation parameter according to the state description parameter and the standard state parameter;

[0048] The seventh determination submodule is used to determine the associated mapping hidden danger keywords of the illegal parameters, and determine the potential safety hidden danger type according to the associated mapping hidden danger keywords.

[0049] Preferably, the generating module comprises:

[0050] An eighth determination submodule is used to determine the departure condition parameters of the safety hazard type, and determine the improvement direction for each safety hazard type according to the departure condition parameters;

[0051] The first generation submodule is used to determine multiple improvement-related subjects according to the improvement direction and generate an improvement plan for each improvement-related subject;

[0052] The second generation submodule is used to combine the improvement plans of each improvement-related subject to generate an improvement plan for each safety hazard type;

[0053] The screening submodule is used to organize the improvement plans, obtain the user's improvement requirements, screen the improvement plans according to the improvement requirements, and display the screened contents in a predetermined form.

[0054] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0055] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0057] Figure 1 A workflow diagram of a method for evaluating coal mine safety hazards based on image data recognition provided by the present invention;

[0058] Figure 2 Another work flow chart of a method for evaluating safety hazards in coal mines based on image data recognition provided by the present invention;

[0059] Figure 3 A schematic diagram of the structure of a coal mine safety hazard evaluation system based on image data recognition provided by the present invention;

[0060] Figure 4 This is a structural schematic diagram of a first determination module in a coal mine safety hazard assessment system based on image data recognition provided by the present invention. DETAILED DESCRIPTION

[0061] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0062] At present, the coal mining industry is restricted and affected by the geological environment, the working environment of the mine is harsh and complex, the safety management level in the coal mining industry is insufficient, and the overall quality of the employees is uneven. The coal industry has always been a high-incidence area of ​​accidents, and the safety production situation is extremely severe. Safety production is the eternal theme of coal mining enterprises and a prerequisite for achieving high-quality and sustainable development of enterprises; coal mine safety production is greatly constrained by natural conditions. The geological structure and coal seam occurrence conditions determine that different development and mining methods must be adopted, and at the same time, many natural disasters are brought about, such as gas, coal dust explosions, mine fires, roof collapse, mine water seepage, etc. These hidden dangers with coal mine attributes become potential factors for accidents. The current safety monitoring system usually monitors all areas in the coal mine manually, which not only wastes a lot of manpower costs but also monitors unimportant areas, reducing the monitoring efficiency. At the same time, the final hidden danger assessment results are subjective and cannot guarantee objectivity. In order to solve the above problems, this embodiment discloses a coal mine safety hazard evaluation method based on image data recognition.

[0063] A coal mine safety hazard evaluation method based on image data recognition, such as Figure 1 As shown, the following steps are included:

[0064] Step S101, determining multiple work processes of coal mine operations, obtaining safety factors of each work process, and determining key monitoring areas according to the safety factors;

[0065] Step S102: collecting a regional image of each key monitoring area, extracting multiple monitoring objects from the regional image and determining the current state of each monitoring object;

[0066] Step S103: determining a plurality of violation parameters based on the current state of each monitored object, and determining the type of potential safety hazard according to the violation parameters;

[0067] Step S104: determine the improvement direction of the coal mine according to the type of safety hazard and generate an improvement plan for display.

[0068] In this embodiment, the multiple work processes are represented as work processes composed of multiple work systems of coal mine operations, such as: underground operation system, ventilation system, transportation system, electrical system, etc.

[0069] In this embodiment, the safety factors are represented as factors that affect operational safety during the work process, such as: adequate employee quality training, adequate equipment maintenance, process improvement and environmental management, etc.;

[0070] In this embodiment, the monitoring object is represented by the attributes of the object to be monitored, such as personnel, equipment, or environment;

[0071] In this embodiment, the current state is represented by the current performance state or current parameter state of the monitored object, for example, the working performance of the equipment or the parameter state of the ambient temperature and humidity.

[0072] The working principle of the above technical solution is: determine multiple work processes of coal mine operations, obtain the safety factors of each work process, and determine the key monitoring areas based on the safety factors; collect regional images of each key monitoring area, extract multiple monitoring objects from the regional images and determine the current status of each monitoring object; determine multiple violation parameters based on the current status of each monitoring object, and determine the type of potential safety hazard based on the violation parameters; determine the improvement direction of the coal mine based on the type of safety hazard and generate an improvement plan for display.

[0073] The beneficial effects of the above technical solution are as follows: by evaluating the key monitoring areas according to the safety factors, it is possible to effectively focus on monitoring the areas with more safety hazards, thereby improving the monitoring efficiency. Furthermore, by automatically determining the monitoring object and its current state in the monitoring image and then determining the violation parameters to evaluate the potential safety hazard type, each safety threat factor in the monitoring vision can be intelligently monitored to maximize safety without the need for manual evaluation, which improves the intelligence while also ensuring the objectivity and accuracy of the evaluation results. This solves the problem mentioned in the prior art that the current safety monitoring system usually performs manual monitoring of all areas in the coal mine, which not only wastes a lot of manpower costs but also monitors unimportant areas, reducing the monitoring efficiency. At the same time, the final hazard evaluation results are subjective and cannot guarantee objectivity.

[0074] In one embodiment, Figure 2 As shown, the method of determining multiple work processes of coal mine operations, obtaining safety factors of each work process, and determining key monitoring areas according to the safety factors includes:

[0075] Step S201, determining multiple operation areas of a coal mine, obtaining operation attributes of each operation area, and determining multiple work processes of coal mine operations according to the operation attributes;

[0076] Step S202: Obtaining personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters, and operation requirement parameters of each workflow;

[0077] Step S203: Perform safety risk assessment on each workflow according to personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters, and determine the risk source in each workflow according to the assessment result;

[0078] Step S204: determine the safety factors in each workflow according to the hazard source, and take the target operation area corresponding to the target workflow with the number of safety factors greater than or equal to a preset threshold as the key monitoring area;

[0079] In this embodiment, the operation attributes are represented by the operation flow attributes of each operation area in the coal mine;

[0080] In this embodiment, the hazard source may be factors such as human error, equipment failure, and poor working environment;

[0081] In this embodiment, the preset threshold may be 1;

[0082] In this embodiment, safety factors include: personnel training, equipment maintenance, process improvement and environmental management, etc.

[0083] The beneficial effects of the above technical scheme are: obtaining multiple parameters of multiple work processes in a coal mine, conducting safety risk assessment on each work process based on these parameters, determining the hazard sources in each work process, determining the safety factors in each work process based on the hazard sources, and determining the key monitoring areas of the target operation area based on the number of safety factors. The key monitoring areas can be determined in a targeted manner, thereby ensuring the focus of safety work and improving the monitoring level.

[0084] In one embodiment, the collecting of the regional image of each key monitoring area, extracting multiple monitoring objects from the regional image and determining the current state of each monitoring object includes:

[0085] Determine the regional boundaries and monitoring equipment layout of each key monitoring area, and determine the monitoring coverage index of each key monitoring area based on the regional boundaries and camera layout;

[0086] The monitoring equipment of each key monitoring area is optimized according to the monitoring coverage index. After the optimization is completed, multiple regional images of each key monitoring area at different angles are collected;

[0087] Determine multiple object types from the regional image, and extract multiple monitoring objects from the regional image according to the object types by feature matching, wherein the monitoring objects include: personnel, machines, and instruments and equipment;

[0088] The regional image is scanned to determine the independent working state and the cyclic working state of each monitored object.

[0089] The beneficial effects of the above technical solution are: determining the monitoring coverage index of each key monitoring area, thereby optimizing the monitoring equipment, ensuring the monitoring coverage rate of each area, collecting multiple monitoring objects in multiple regional images of different angles of each key monitoring area, and determining the independent working status and cyclic working status of each monitoring object. By scanning the regional images in real time, the working status of each monitoring object can be understood, which facilitates the discovery of abnormalities and timely processing, thereby improving monitoring efficiency.

[0090] In one embodiment, the determining of a plurality of violation parameters based on the current state of each monitored object and determining the type of potential safety hazard according to the violation parameters include:

[0091] Determine a plurality of abnormal features according to the current state of each monitored object, wherein the abnormal features include: abnormal wearing features, abnormal running features, and abnormal operation features;

[0092] Compare multiple abnormal features with standard features, determine the deviation between the abnormal features and the standard features based on the comparison results, and judge whether the current state of each monitored object meets the violation standard based on the deviation;

[0093] If so, obtain the state description parameters corresponding to the current state, and determine the object violation parameters according to the state description parameters and the standard state parameters;

[0094] Determine the associated mapping risk keywords of the illegal parameters, and determine the potential security risk type according to the associated mapping risk keywords.

[0095] The beneficial effects of the above technical solution are: comparing multiple abnormal features with standard features, obtaining the degree of deviation, and judging whether the current state of each monitored object is in violation of the regulations based on the degree of deviation. By real-time monitoring of the state of the monitored object, possible violations can be discovered and warned in a timely manner. Furthermore, obtaining violation parameters and the associated mapping of violation parameters to hidden danger keywords and determining the types of potential safety hazards can accurately and comprehensively determine the potential safety hazards of coal mines, thereby improving the comprehensiveness and reliability of hazard assessment.

[0096] In one embodiment, determining the improvement direction of the coal mine according to the type of potential safety hazard and generating an improvement plan for display includes:

[0097] Determine the starting condition parameters of the safety hazard type, and determine the improvement direction for each safety hazard type based on the starting condition parameters;

[0098] Determine multiple improvement-related entities according to the improvement direction, and generate an improvement plan for each improvement-related entity;

[0099] Combine the improvement plans of each improvement-related subject to generate an improvement plan for each type of safety hazard;

[0100] Organize the improvement plans, obtain user improvement requirements, screen the improvement plans according to the improvement requirements, and display the screened contents in a predetermined form.

[0101] The beneficial effect of the above technical solution is: according to the improvement direction of the safety hazard type, an improvement plan for each improvement-related subject is generated, thereby generating and organizing improvement plans. By formulating and improving plans in a targeted manner, various types of safety hazards in coal mines can be more effectively identified, prevented and responded to, thereby improving overall safety. Furthermore, by screening according to improvement needs and displaying them in a predetermined form, information can be better presented, visualization is enhanced, and the user experience is improved.

[0102] In one embodiment, this embodiment also discloses a coal mine safety hazard evaluation system based on image data recognition, such as Figure 3 As shown, the system includes:

[0103] The first determination module 301 is used to determine multiple work processes of coal mine operations, obtain safety factors of each work process, and determine key monitoring areas according to the safety factors;

[0104] The second determination module 302 is used to collect a regional image of each key monitoring area, extract multiple monitoring objects from the regional image and determine the current state of each monitoring object;

[0105] The third determination module 303 is used to determine a plurality of violation parameters based on the current state of each monitored object, and determine the type of potential safety hazard according to the violation parameters;

[0106] The generation module 304 is used to determine the improvement direction of the coal mine according to the type of safety hazard and generate an improvement plan for display.

[0107] The working principle of the above technical solution is: first, based on the first determination module, multiple work processes of coal mine operations are determined, the safety factors of each work process are obtained, and the key monitoring areas are determined according to the safety factors; secondly, the second determination module is used to collect regional images of each key monitoring area, and multiple monitoring objects are extracted from the regional images and the current status of each monitoring object is determined; then, a third determination module is used to determine multiple violation parameters based on the current status of each monitoring object, and the type of potential safety hazard is determined according to the violation parameters; finally, the generation module is used to determine the improvement direction of the coal mine according to the type of safety hazard and generate an improvement plan for display.

[0108] The beneficial effects of the above technical solution are: by evaluating the key monitoring areas according to the security factors, it is possible to effectively focus on monitoring the areas with more potential safety hazards, thereby improving the monitoring efficiency. Furthermore, by automatically determining the monitored objects in the monitoring image and their current status and then determining the violation parameters to evaluate the types of potential safety hazards, each security threat factor within the monitoring vision can be intelligently monitored to maximize safety without the need for manual evaluation. This improves intelligence while also ensuring the objectivity and accuracy of the evaluation results.

[0109] In one embodiment, Figure 4 As shown, the first determining module 301 includes:

[0110] The first determination submodule 3011 is used to determine multiple operation areas of the coal mine, obtain the operation attributes of each operation area, and determine multiple work processes of the coal mine operation according to the operation attributes;

[0111] The acquisition submodule 3012 is used to acquire the personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters of each workflow;

[0112] The evaluation submodule 3013 is used to perform safety risk assessment on each workflow according to personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters, and determine the risk source in each workflow according to the evaluation results;

[0113] The second determination submodule 3014 is used to determine the safety factors in each workflow according to the hazard source, and to take the target operation area corresponding to the target workflow with the number of safety factors greater than or equal to a preset threshold as the key monitoring area.

[0114] The beneficial effects of the above technical scheme are: obtaining multiple parameters of multiple work processes in a coal mine, conducting safety risk assessment on each work process based on these parameters, determining the hazard sources in each work process, determining the safety factors in each work process based on the hazard sources, and determining the key monitoring areas of the target operation area based on the number of safety factors. The key monitoring areas can be determined in a targeted manner, thereby ensuring the focus of safety work and improving the monitoring level.

[0115] In one embodiment, the second determining module includes:

[0116] The third determination submodule is used to determine the regional boundaries and monitoring equipment layout of each key monitoring area, and determine the monitoring coverage index of each key monitoring area according to the regional boundaries and camera layout;

[0117] The acquisition submodule is used to optimize the monitoring equipment of each key monitoring area according to the monitoring coverage index. After the optimization is completed, multiple regional images of each key monitoring area at different angles are collected;

[0118] An extraction submodule, used to determine multiple object types from the regional image, and extract multiple monitoring objects from the regional image according to the object types by feature matching, wherein the monitoring objects include: personnel, machines, and instruments and equipment;

[0119] The fourth determination submodule is used to scan the regional image to determine the independent working state and the cyclic working state of each monitored object.

[0120] The beneficial effects of the above technical solution are: determining the monitoring coverage index of each key monitoring area, thereby optimizing the monitoring equipment, ensuring the monitoring coverage rate of each area, collecting multiple monitoring objects in multiple regional images of different angles of each key monitoring area, and determining the independent working status and cyclic working status of each monitoring object. By scanning the regional images in real time, the working status of each monitoring object can be understood, which facilitates the discovery of abnormalities and timely processing, thereby improving monitoring efficiency.

[0121] In one embodiment, the third determining module includes:

[0122] A fifth determination submodule is used to determine a plurality of abnormal features according to the current state of each monitored object, wherein the abnormal features include: abnormal wearing features, abnormal running features, and abnormal operation features;

[0123] The judgment submodule is used to compare multiple abnormal features with standard features, determine the deviation between the abnormal features and the standard features according to the comparison results, and judge whether the current state of each monitored object meets the violation standard according to the deviation;

[0124] A sixth determination submodule, for, if yes, obtaining a state description parameter corresponding to the current state, and determining the object violation parameter according to the state description parameter and the standard state parameter;

[0125] The seventh determination submodule is used to determine the associated mapping hidden danger keywords of the illegal parameters, and determine the potential safety hidden danger type according to the associated mapping hidden danger keywords.

[0126] The beneficial effects of the above technical solution are: comparing multiple abnormal features with standard features, obtaining the degree of deviation, and judging whether the current state of each monitored object is in violation of the regulations based on the degree of deviation. By real-time monitoring of the state of the monitored object, possible violations can be discovered and warned in a timely manner. Furthermore, obtaining violation parameters and the associated mapping of violation parameters to hidden danger keywords and determining the types of potential safety hazards can accurately and comprehensively determine the potential safety hazards of coal mines, thereby improving the comprehensiveness and reliability of hazard assessment.

[0127] In one embodiment, the generating module comprises:

[0128] An eighth determination submodule is used to determine the departure condition parameters of the safety hazard type, and determine the improvement direction for each safety hazard type according to the departure condition parameters;

[0129] The first generation submodule is used to determine multiple improvement-related subjects according to the improvement direction and generate an improvement plan for each improvement-related subject;

[0130] The second generation submodule is used to combine the improvement plans of each improvement-related subject to generate an improvement plan for each safety hazard type;

[0131] The screening submodule is used to organize the improvement plans, obtain the user's improvement requirements, screen the improvement plans according to the improvement requirements, and display the screened contents in a predetermined form.

[0132] The beneficial effect of the above technical solution is: according to the improvement direction of the safety hazard type, an improvement plan for each improvement-related subject is generated, thereby generating and organizing improvement plans. By formulating and improving plans in a targeted manner, various types of safety hazards in coal mines can be more effectively identified, prevented and responded to, thereby improving overall safety. Furthermore, by screening according to improvement needs and displaying them in a predetermined form, information can be better presented, visualization is enhanced, and the user experience is improved.

[0133] Those skilled in the art should understand that the first and second in the present invention merely refer to different application stages.

[0134] Other embodiments of the present disclosure will be readily apparent to those skilled in the art after considering the specification and practicing the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0135] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for evaluating safety hazards in coal mines based on image data recognition, characterized in that: The following steps are involved: Identify multiple work processes of coal mine operations, obtain the safety factors of each work process, and determine the key monitoring areas based on the safety factors; Collecting a regional image of each key monitoring area, extracting multiple monitoring objects from the regional image and determining the current state of each monitoring object; Determine multiple violation parameters based on the current status of each monitored object, and determine the type of potential safety hazard based on the violation parameters; Determine the direction of coal mine improvement based on the type of safety hazard and generate an improvement plan for display.

2. The method for evaluating safety hazards in coal mines based on image data recognition according to claim 1, characterized in that: The method of determining multiple work processes of coal mine operations, obtaining safety factors of each work process, and determining key monitoring areas according to the safety factors includes: Determine multiple operation areas of the coal mine, obtain the operation attributes of each operation area, and determine multiple work processes of the coal mine operation according to the operation attributes; Obtain the personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters of each workflow; Conduct safety risk assessment for each workflow based on personnel demand parameters, equipment demand parameters, scene environment demand parameters, and operation demand parameters, and determine the hazard sources in each workflow based on the assessment results; Determine the safety factors in each workflow based on the hazard sources, and take the target operation area corresponding to the target workflow where the number of safety factors is greater than or equal to the preset threshold as the key monitoring area.

3. The method for evaluating safety hazards in coal mines based on image data recognition according to claim 1, characterized in that: The collecting of the regional image of each key monitoring area, extracting multiple monitoring objects from the regional image and determining the current state of each monitoring object includes: Determine the regional boundaries and monitoring equipment layout of each key monitoring area, and determine the monitoring coverage index of each key monitoring area based on the regional boundaries and camera layout; The monitoring equipment of each key monitoring area is optimized according to the monitoring coverage index. After the optimization is completed, multiple regional images of each key monitoring area at different angles are collected; Determine multiple object types from the regional image, and extract multiple monitoring objects from the regional image according to the object types by feature matching, wherein the monitoring objects include: personnel, machines, and instruments and equipment; The regional image is scanned to determine the independent working state and the cyclic working state of each monitored object.

4. The method for evaluating safety hazards in coal mines based on image data recognition according to claim 1, characterized in that: Determining a plurality of violation parameters based on the current state of each monitored object and determining the type of potential safety hazard according to the violation parameters includes: Determine a plurality of abnormal features according to the current state of each monitored object, wherein the abnormal features include: abnormal wearing features, abnormal running features, and abnormal operation features; Compare multiple abnormal features with standard features, determine the deviation between the abnormal features and the standard features based on the comparison results, and judge whether the current state of each monitored object meets the violation standard based on the deviation; If so, obtain the state description parameters corresponding to the current state, and determine the object violation parameters according to the state description parameters and the standard state parameters; Determine the associated mapping risk keywords of the illegal parameters, and determine the potential security risk type according to the associated mapping risk keywords.

5. The method for evaluating safety hazards in coal mines based on image data recognition according to claim 1, characterized in that: Determining the improvement direction of the coal mine according to the type of potential safety hazard and generating an improvement plan for display includes: Determine the starting condition parameters of the safety hazard type, and determine the improvement direction for each safety hazard type based on the starting condition parameters; Determine multiple improvement-related subjects according to the improvement direction, and generate an improvement plan for each improvement-related subject; Combine the improvement plans of each improvement-related subject to generate an improvement plan for each type of safety hazard; Organize the improvement plans, obtain user improvement requirements, screen the improvement plans according to the improvement requirements, and display the screened contents in a predetermined form.

6. A coal mine safety hazard assessment system based on image data recognition, characterized in that: The system includes: The first determination module is used to determine multiple work processes of coal mine operations, obtain the safety factors of each work process, and determine the key monitoring area according to the safety factors; A second determination module is used to collect a regional image of each key monitoring area, extract multiple monitoring objects from the regional image and determine the current state of each monitoring object; A third determination module is used to determine a plurality of violation parameters based on the current state of each monitored object, and determine the type of potential safety hazard according to the violation parameters; The generation module is used to determine the improvement direction of the coal mine according to the type of safety hazards and generate improvement plans for display.

7. The coal mine safety hazard assessment system based on image data recognition according to claim 6 is characterized in that: The first determining module includes: The first determination submodule is used to determine multiple operation areas of the coal mine, obtain the operation attributes of each operation area, and determine multiple work processes of the coal mine operation according to the operation attributes; The acquisition submodule is used to obtain the personnel requirement parameters, equipment requirement parameters, scene environment requirement parameters and operation requirement parameters of each workflow; The assessment submodule is used to conduct a safety risk assessment for each workflow based on personnel demand parameters, equipment demand parameters, scene environment demand parameters, and operation demand parameters, and determine the hazard source in each workflow based on the assessment results; The second determination submodule is used to determine the safety factors in each workflow according to the hazard source, and to take the target operation area corresponding to the target workflow with the number of safety factors greater than or equal to a preset threshold as the key monitoring area.

8. The coal mine safety hazard evaluation system based on image data recognition according to claim 6 is characterized in that: The second determining module includes: The third determination submodule is used to determine the regional boundaries and monitoring equipment layout of each key monitoring area, and determine the monitoring coverage index of each key monitoring area according to the regional boundaries and camera layout; The acquisition submodule is used to optimize the monitoring equipment of each key monitoring area according to the monitoring coverage index. After the optimization is completed, multiple regional images of each key monitoring area at different angles are collected; An extraction submodule, used to determine multiple object types from the regional image, and extract multiple monitoring objects from the regional image according to the object types by feature matching, wherein the monitoring objects include: personnel, machines, and instruments and equipment; The fourth determination submodule is used to scan the regional image to determine the independent working state and the cyclic working state of each monitored object.

9. The coal mine safety hazard evaluation system based on image data recognition according to claim 6 is characterized in that: The third determining module comprises: A fifth determination submodule is used to determine a plurality of abnormal features according to the current state of each monitored object, wherein the abnormal features include: abnormal wearing features, abnormal running features, and abnormal operation features; The judgment submodule is used to compare multiple abnormal features with standard features, determine the deviation between the abnormal features and the standard features according to the comparison results, and judge whether the current state of each monitored object meets the violation standard according to the deviation; A sixth determination submodule, for, if yes, obtaining a state description parameter corresponding to the current state, and determining the object violation parameter according to the state description parameter and the standard state parameter; The seventh determination submodule is used to determine the associated mapping hidden danger keywords of the illegal parameters, and determine the potential safety hidden danger type according to the associated mapping hidden danger keywords.

10. The coal mine safety hazard evaluation system based on image data recognition according to claim 6, characterized in that: The generating module comprises: An eighth determination submodule is used to determine the departure condition parameters of the safety hazard type, and determine the improvement direction for each safety hazard type according to the departure condition parameters; The first generation submodule is used to determine multiple improvement-related subjects according to the improvement direction and generate an improvement plan for each improvement-related subject; The second generation submodule is used to combine the improvement plans of each improvement-related subject to generate an improvement plan for each safety hazard type; The screening submodule is used to organize the improvement plans, obtain the user's improvement requirements, screen the improvement plans according to the improvement requirements, and display the screened contents in a predetermined form.

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