A safety auxiliary supervision and inspection method and system applied to a coal mine

Abstract

This application relates to the field of coal mine safety monitoring technology, and in particular to a method and system for auxiliary safety supervision and inspection applied in coal mines. The method includes: determining predicted hazard events and predicted hazard levels based on basic alarm events and basic monitoring parameters; determining the predicted impact range based on the predicted hazard events, and determining the personnel affected based on the predicted impact range and the predicted evolution and diffusion rate of the predicted hazard events; identifying key personnel based on the historical behavioral response information of each affected person and the predicted hazard events; determining standard response measures corresponding to the predicted hazard events based on their characteristics, and generating a broadcast warning voice command based on the standard response measures and the predicted impact range; and feeding back the broadcast warning voice command to the terminal devices of the key personnel to remind them to provide guidance. This application facilitates the accurate and timely identification of coal mine hazards and the implementation of appropriate countermeasures.

Description

Technical Field

[0001] This application relates to the field of coal mine safety monitoring technology, and in particular to a safety auxiliary supervision and inspection method and system applied to coal mines. Background Technology

[0002] As a core pillar of my country's energy supply, the safe production of coal directly relates to the lives of its employees and the sustainable development of the industry. It is also a crucial cornerstone for ensuring a stable energy supply and maintaining the balance of the industrial ecosystem. However, the underground working environment in coal mines is characterized by its confined space, variable geological conditions, dense equipment, and complex operating conditions. It has long faced multiple safety hazards, including personnel violations, equipment malfunctions, and abnormal environmental parameters. These hazards are generally characterized by their high degree of concealment, rapid evolution, and wide-ranging impact. If not handled promptly or properly, they can easily lead to major safety accidents, causing casualties and huge property losses.

[0003] Current conventional methods of coal mine safety supervision and inspection mostly rely on single-threshold trigger alarm mechanisms. That is, they can only issue warnings when actual hazards occur or approach a critical state, lacking the ability to proactively predict the evolution trend of hazards and failing to identify potential future risk events and their potential impact in advance. If countermeasures are only taken after a hazard has occurred, the response window is often too narrow and preparations are insufficient to quickly contain the spread of the hazard. Ultimately, this causes irreversible damage to the lives of underground workers and the stable operation of critical production equipment, severely hindering the improvement of coal mine safety production levels. Summary of the Invention

[0004] In order to facilitate the accurate and proactive identification of potential safety hazards in coal mines and the timely implementation of countermeasures, thereby improving the level of safe production in coal mines, this application provides a safety auxiliary supervision and inspection method and system for coal mines.

[0005] Firstly, this application provides a safety auxiliary supervision and inspection method for coal mines, employing the following technical solution: A method for auxiliary safety supervision and inspection applied in coal mines includes: Acquire basic alarm events and basic monitoring parameters, and determine predicted potential hazard events and predicted hazard levels based on the basic alarm events and basic monitoring parameters; The predicted impact range is determined based on the predicted potential hazard event, and the predicted affected personnel are determined based on the predicted impact range and the predicted evolution and diffusion rate of the predicted potential hazard event. Obtain historical behavioral response information for each predicted affected person, and based on the historical behavioral response information of each predicted affected person and the predicted potential event, identify core personnel from all predicted affected personnel; determine a standard response measure corresponding to the predicted hidden danger event according to a predicted hidden danger feature corresponding to the predicted hidden danger event, and generate a broadcast warning voice instruction based on the standard response measure and the predicted range of influence; feed back the broadcast warning voice instruction to a terminal device of the core personnel to remind the core personnel to guide broadcast to other predicted range of influence personnel according to the broadcast warning voice instruction.

[0006] By adopting the above technical solutions, multi-source data complementary analysis is carried out by integrating the basic alarm event and the basic monitoring parameter, which facilitates accurate prediction of hidden danger events that may occur in the future period of time, effectively avoids the risk of misjudgment triggered by single data, significantly improves the accuracy and forward-looking nature of the prediction result, and quantifies the prediction result as a prediction hidden danger grade, which facilitates intuitive risk grade that may be faced in the future period of time, so as to reserve sufficient response time for underground personnel. By accurately locking the predicted range of influence and the range of influence personnel, the core personnel are selected and matched according to the historical behavior response information, so as to ensure that the hidden danger disposal is dominated by personnel with matching ability. In addition, by accurately matching the exclusive standard response measure based on the prediction hidden danger feature, the randomness and non-standardization of experiential decision-making are avoided, and the disposal action is ensured to be scientific and compliant, thereby facilitating accurate realization of the advanced identification of coal mine hidden dangers and timely taking of response measures, and further facilitating improvement of the safety production level of coal mines.

[0007] In a possible implementation manner, the determination of the predicted range of influence based on the predicted hidden danger event comprises: determining an initial range of influence according to the predicted hidden danger event and the predicted hidden danger grade; identifying a predicted event feature corresponding to the predicted hidden danger event, and determining a plurality of predicted hidden danger routes based on the predicted event feature, each predicted hidden danger route matching at least one predicted event feature; determining a route intersection parameter by performing intersection between each predicted hidden danger route and the initial range of influence, determining a route influence weight of each predicted hidden danger route based on the route intersection parameter, and superimposing each predicted hidden danger route and the initial range of influence based on the route influence weight of each predicted hidden danger route to determine the predicted range of influence corresponding to the predicted hidden danger event.

[0008] By adopting the technical scheme, the initial spread range is determined by combining the predicted hazard event type and grade, a basic boundary is defined for hazard space influence, blind and random range determination is avoided, the predicted event characteristics are identified and the corresponding predicted hazard route is matched, the hazard propagation path is accurately matched with the actual underground space topology, the problem that the traditional range determination ignores the hazard propagation law is solved, in addition, the route intersection parameter of the predicted hazard route and the initial spread range is calculated, the spatial correlation degree of the two is quantified, objective data support is provided for route influence weight determination, subjective experience deviation in the weight allocation process is avoided, finally, the predicted hazard route and the initial spread range are superimposed based on the route influence weight, dynamic optimization and accurate expansion of the spread range are realized, key areas where hazards may spread are ensured to be covered, and waste of emergency resources caused by excessive range expansion is avoided.

[0009] In a possible implementation manner, the determining, based on the route intersection parameter, of the route influence weight of each predicted hazard route comprises: identifying, from the route intersection parameter, an intersection section between each predicted hazard route and the initial spread range, and comparing the intersection section with an original section of each predicted hazard route to determine an intersection proportion corresponding to each predicted hazard route; identifying a predicted hazard trend of each predicted hazard route, and determining an evolution fitting degree corresponding to each predicted hazard route based on a predicted evolution trend corresponding to each predicted hazard trend and the initial spread range; determining the route influence weight of each predicted hazard route based on the intersection proportion and the evolution fitting degree corresponding to each predicted hazard route.

[0010] By adopting the technical scheme, the intersection section of the predicted hazard route and the initial spread range is accurately identified from the route intersection parameter, the intersection proportion corresponding to each predicted hazard route is determined, objective and quantifiable spatial correlation basis is provided for route influence weight determination, in addition, the predicted hazard trend of each predicted hazard route is identified, and the predicted evolution trend corresponding to the initial spread range is matched and analyzed, the weight calculation is fully matched with the actual hazard propagation law, finally, the route influence weight is calculated based on the dual-dimension fusion of the intersection proportion and the evolution fitting degree, multi-factor collaborative calibration of weight assignment is realized, the high-correlation area of hazards is covered, and the risk transmission intensity difference of different routes is accurately distinguished.

[0011] In a possible implementation manner, when the route influence weight of the predicted hazard route is greater than a preset weight threshold, the method further comprises: determining, as a concerned hazard route, the predicted hazard route whose route influence weight is greater than the preset weight threshold, and identifying concerned section coordinates of a concerned intersection section corresponding to the concerned hazard route. identify intersection hazard routes intersecting with the concerned hazard route from other non-concerned hazard routes based on the route intersection parameter, the other non-concerned hazard routes being other predicted hazard routes except the concerned hazard route, and identify a total number of route superimpositions of all intersection hazard routes; identify intersection section coordinates of each intersection hazard route, compare each intersection section coordinate with the concerned section coordinate, determine an intersection type between each intersection hazard route and the concerned intersection section, and determine a proportion of the intersection type corresponding to the concerned hazard route based on the intersection type between each intersection hazard route and the concerned intersection section of the concerned hazard route, the intersection type including upstream intersection and downstream intersection; determine a weight adjustment value of the concerned hazard route based on the total number of route superimpositions and the proportion of the intersection type, and adjust a route influence weight of the concerned hazard route based on the weight adjustment value.

[0012] By adopting the above technical solution, the predicted hazard route with a route influence weight greater than a preset threshold is defined as a concerned hazard route, the high-risk transmission path is accurately focused, the intersection hazard route intersecting with the concerned hazard route is screened from the non-concerned hazard route, and the total number of route superimpositions is counted, so as to quantitatively determine the associated transmission strength of the high-risk route, the upstream intersection and downstream intersection types are distinguished by comparing the intersection section coordinates, and the weight adjustment is fitted to the actual transmission direction characteristics of the hazard by combining the proportion of the intersection type, finally, the weight adjustment value is calculated based on the total number of route superimpositions and the proportion of the intersection type, so as to realize the dynamic calibration of the weight of the concerned hazard route, and avoid the weight deviation caused by single-dimensional judgment.

[0013] In a possible implementation manner, the core personnel is determined from all the predicted affected personnel based on the historical behavior response information of each predicted affected personnel and the predicted hazard event, including: identify a response skill dimension corresponding to the predicted hazard event, and determine a predicted response ability value of each predicted affected personnel in the face of the predicted hazard event based on the response skill dimension and the historical behavior response information of each predicted affected personnel; identify an associated communication affected personnel in an associated communication range corresponding to each predicted affected personnel, and an associated predicted response ability value of each associated communication affected personnel, and determine an associated communication response value of each predicted affected personnel based on an associated communication quantity of the associated communication affected personnel corresponding to each predicted affected personnel and an associated response average value of the associated predicted response ability value of all associated communication affected personnel; divide the predicted affected range based on an event position of the predicted hazard event in the predicted affected range to obtain a plurality of division regions, each division region corresponding to different response priorities; determine a hidden danger response score of each predicted affected person based on the predicted response capability value corresponding to each predicted affected person and the associated communication response value, and a response priority of the divided area where each predicted affected person is located, and determine the predicted affected person with the highest hidden danger response score as the core person.

[0014] By adopting the technical solutions described above, the corresponding response skill dimension of the predicted hidden danger event is accurately identified, the predicted response capability value is calculated in combination with the historical behavior response information of the predicted affected person, the accurate adaptation of the personnel handling capability to the hidden danger type is facilitated, the number of associated communications of the predicted affected person and the associated predicted response capability mean value of the associated person are counted, the person with strong self-capability and capable of effectively driving the surrounding personnel to cooperatively handle is screened out, the hidden danger handling mode of the coal mine underground team cooperation is facilitated, thereby the limitation that the traditional handling process only focuses on the individual capability and ignores the cooperation efficiency is solved, the position of the predicted hidden danger event and the divided area with different response priorities are divided, the screening process of the core person is facilitated to consider the capability adaptability, and the spatial accessibility and response timeliness are taken into account, thereby the core person screened out is facilitated to quickly arrive at the hidden danger site to handle.

[0015] In a possible implementation manner, the method further includes: When the core person guides and broadcasts to other predicted affected persons according to the broadcast warning voice instruction, a state parameter of the core person in a preset analysis time period is acquired, and a current state score of the core person is determined based on the state parameter; An execution parameter of other predicted affected persons is determined based on the standard response measure, and a response effect score corresponding to other predicted affected persons is determined based on the execution parameter, the execution parameter including an execution rate and an execution completion degree; A guiding broadcast score value of the core person is determined based on the current state score and the response effect score, when the guiding broadcast score value is lower than a preset score threshold value, a low execution area is determined based on the response effect score corresponding to other predicted affected persons in the low execution area; An auxiliary person is determined based on the response effect score of each other predicted affected person in the low execution area, and the broadcast warning voice instruction is fed back to a terminal device of the auxiliary person to remind the auxiliary person to guide and broadcast to other predicted affected persons in the low execution area according to the broadcast warning voice instruction, the auxiliary person being the other predicted affected person with the highest response effect score in the low execution area.

[0016] By adopting the technical scheme, the state parameters of the core personnel in a preset analysis time period are acquired in real time, the current state score is quantitatively determined, the input degree and the professionalism of the core personnel in guiding broadcasting are objectively evaluated, the execution parameters of other predicted affected personnel are analyzed, the response effect score is accurately calculated, the execution result is quantitatively and closed-loop evaluated, the guiding broadcasting score is determined by fusing the current state score and the response effect score, the low execution area is timely and accurately locked, the auxiliary personnel are identified from the low execution area to assist the core personnel in guiding broadcasting, the guiding gap in the low execution area is accurately made up, the collaborative disposal mode of overall planning of the core personnel and deep cultivation of the auxiliary personnel in the area is formed, the guiding inefficiency problem caused by wide coverage and limited communication of a single core personnel is avoided, and therefore the balance and effectiveness of the overall hidden danger disposal are improved.

[0017] In a second aspect, the application provides a supervision and inspection system, which adopts the following technical scheme: A supervision and inspection system, comprising: at least one processor; a memory; at least one application program, wherein the at least one application program is stored in the memory and is configured to be executed by the at least one processor, and the at least one application program is configured to implement the above-mentioned safety auxiliary supervision and inspection method applied to a coal mine.

[0018] In a third aspect, the application provides a computer-readable storage medium, which adopts the following technical scheme: A computer-readable storage medium, comprising a computer program capable of being loaded and executed by a processor to implement the above-mentioned safety auxiliary supervision and inspection method applied to a coal mine.

[0019] In a fourth aspect, the application provides a computer program product, which adopts the following technical scheme: A computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the above-mentioned safety auxiliary supervision and inspection method applied to a coal mine.

[0020] In summary, the application has at least one of the following beneficial technical effects: By integrating the basic alarm events and the basic monitoring parameters for multi-source data complementary analysis, it is convenient to accurately predict potential hazard events that may occur in a period of time in the future, effectively avoid the misjudgment risk triggered by single data, significantly improve the accuracy and forward-looking of the prediction results, and by quantifying the prediction results into a prediction hazard level, it is convenient to intuitively know the risk level that may be faced in a period of time in the future, so as to reserve sufficient response time for underground personnel, accurately lock the prediction range and the affected personnel, and select and adapt the core personnel according to the historical behavior response information of the personnel, so as to ensure that the hazard disposal is dominated by the personnel with matching ability, in addition, by accurately matching the exclusive standard response measures based on the prediction hazard characteristics, the randomness and non-standardization of experiential decision-making are avoided, and the disposal action is ensured to be scientific and compliant, thereby conveniently realizing the advanced identification of coal mine hazards and timely taking response measures, and further conveniently improving the safety production level of coal mines.

[0021] By accurately identifying the intersection section of the prediction hazard route and the initial range of influence from the route intersection parameters, the intersection proportion corresponding to each prediction hazard route is determined, which provides objective and quantifiable spatial correlation basis for route influence weight determination, in addition, by identifying the prediction hazard trend of each prediction hazard route and matching analysis with the prediction evolution trend corresponding to the initial range of influence, it is convenient to make the weight calculation fully conform to the actual hazard propagation law, and finally, based on the dual-dimension fusion of intersection proportion and evolution fitting degree, the route influence weight is calculated, which is convenient for realizing the multi-factor collaborative calibration of weight assignment, ensuring to cover the high correlation area of hazards, and at the same time, it is convenient to accurately distinguish the risk transmission intensity difference of different routes. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is a flowchart of a safety auxiliary supervision and inspection method applied to coal mines in the embodiments of the present application; Figure 2 is a flowchart of determining the route influence weight of the prediction hazard route in the embodiments of the present application; Figure 3 is a structural diagram of a supervision and inspection system in the embodiments of the present application. DETAILED DESCRIPTION

[0023] The following will be described in detail in combination with the accompanying Figures 1 to 3 The present application will be further described in detail.

[0024] Those skilled in the art can make modifications to the embodiments of the present application without creative contribution after reading the present specification, but as long as the modifications are within the scope of the claims of the present application, they are protected by the patent law.

[0025] To make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0026] It should be noted that, in the optional embodiments of the present application, the data related to the object information and the like needs to be obtained with the permission or consent of the object when the embodiments of the present application are applied to specific products or technologies, and the collection, use, and processing of the related data need to comply with the relevant laws, regulations, and standards of the country and region. That is, if the embodiments of the present application involve data related to the object, the data needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant department, and compliance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the consent of the individual needs to be obtained for the acquisition of all personal information, and the separate consent of the information subject needs to be obtained for the acquisition of sensitive information, and the embodiments also need to be implemented with the authorization and consent of the object.

[0027] Specifically, the embodiments of the present application provide a safety auxiliary supervision and inspection method applied to a coal mine, which is executed by a supervision and inspection system. The supervision and inspection system can be a server or a terminal device. The server can be a stand-alone physical server, a server cluster composed of multiple physical servers, or a distributed system, and can also be a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, and the like, but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication, and the embodiments of the present application do not limit this.

[0028] Reference Figure 1 , Figure 1 is a flowchart of a safety auxiliary supervision and inspection method applied to a coal mine in the embodiments of the present application. The method comprises steps S110-S150, wherein: Step S110: acquiring a basic alarm event and a basic monitoring parameter, and determining a predicted hidden danger event and a predicted hidden danger level based on the basic alarm event and the basic monitoring parameter.

[0029] Specifically, the supervision and inspection system integrates video recognition analysis, industrial linkage control and other functions, uses a general digital camera, a mine intrinsically safe camera, an intelligent analysis device and the like to form an intelligent, multifunctional and all-weather dynamic video intelligent recognition system, realizes the combination of video machine vision recognition and industrial control, can realize the recognition of personnel behavior, and can also realize the recognition of mine environment and the state of articles (equipment), etc. Among them, the equipment can be deployed at the perception layer: high-definition cameras (for example, Hikvision DS-2CD3T86FWDV2-I5) are deployed in the ground main shaft winch room and auxiliary shaft winch room, and mine intrinsically safe cameras are deployed in the main rail middle station and the east rail one department anti-running device; the network can be built at the transmission layer: a gigabit switch is deployed to connect the ground camera, the underground camera (through the underground industrial Ethernet ring network) and the video analysis device, and a firewall is configured to limit non-platform ports (for example, only 80, 443 and the like are opened); the software can be installed at the platform layer: a coal mine AI video intelligent management client software is installed, a message middleware, a distributed database and a streaming media forwarding service are deployed; the function can be debugged at the application layer: a plurality of recognition algorithms are input to cover personnel behavior, equipment state, environmental risk and other multi-dimensional supervision scenarios, for example, a personnel area intrusion recognition algorithm can identify the violation of personnel entering the dangerous area according to the delineation of the prohibited personnel entering area, give an on-site voice alarm, and take pictures and record videos after identifying the violation to form a basic alarm event; a personnel off-duty recognition algorithm can identify the violation of personnel leaving the work post area for more than a specified time, identify the violation of personnel sleeping during on-duty, take pictures and record videos after identifying the violation to form a basic alarm event, and at least 25 recognition algorithms including a belt conveyor warning line personnel intrusion, personnel crossing the belt, belt deviation recognition, coal stacking recognition, fire recognition and the like can be flexibly configured according to the actual supervision needs of the coal mine, and the specific recognition algorithm types are not limited in the embodiments of the present application.

[0030] The basic monitoring parameters include but are not limited to environmental monitoring parameters (gas concentration, dust concentration, water depth, etc.), equipment operation parameters (motor current, vibration frequency, belt tension), real-time personnel position and the like, which can be collected by the mine intrinsically safe environmental sensor, the underground high-definition infrared camera and the intrinsically safe wireless camera and the like already deployed in the coal mine, and the collection results are uploaded to the supervision and inspection system.

[0031] The abnormal phenomenon can be determined through the basic alarm event, and the development trend of the abnormal phenomenon can be predicted and analyzed through analysis of the basic monitoring parameter. The preset association rule base can be used to determine the prediction hidden danger event corresponding to the basic alarm event and the basic monitoring parameter. The preset association rule base stores a plurality of development hidden dangers corresponding to a plurality of basic alarm events under the influence of different basic monitoring parameters. For example, if the basic alarm event is personnel area intrusion, and the basic monitoring parameter shows that the gas concentration in the area has been rising for nearly 10 minutes, and the ventilator current is lower than the normal threshold, it can be determined that the corresponding prediction hidden danger event of the area is gas accumulation area personnel intrusion violation. If the basic alarm event is belt deviation, and the basic monitoring parameter shows that the deviation angle of the area has increased by ≥0.5 / minute in the last 5 minutes, and the roller vibration frequency is ≥30 Hz, it can be determined that the corresponding prediction hidden danger event of the area is belt tearing risk. The specific meaning of the preset association rule base is not limited in the embodiments of the present application.

[0032] In determining the prediction hidden danger level of the prediction hidden danger event, the corresponding basic monitoring parameter can be quantitatively converted to obtain a quantitative monitoring score, and the corresponding region of the basic alarm event, the basic alarm level and the basic alarm frequency can be quantitatively converted to obtain a basic alarm score. Different regions correspond to different region levels. The prediction hidden danger score is obtained by summing the quantitative monitoring score and the basic alarm score. The higher the prediction hidden danger score, the higher the corresponding prediction hidden danger level. The prediction hidden danger level can be determined by the preset hidden danger level mapping relationship. The preset hidden danger level mapping relationship is the corresponding relationship between the prediction hidden danger score and the prediction hidden danger level. The specific content is limited in the embodiments of the present application.

[0033] Step S120: determining the prediction spread range based on the prediction hidden danger event, and determining the prediction spread personnel based on the prediction spread range and the prediction evolution and diffusion rate of the prediction hidden danger event.

[0034] Specifically, the hidden danger characteristics corresponding to the prediction hidden danger event can be identified first, and then the corresponding prediction evolution law can be determined based on the hidden danger characteristics. The prediction evolution law, the basic alarm event and the basic monitoring parameter are introduced into the simulation underground model to simulate the area that can be reached by the prediction hidden danger event in a future period of time to obtain the prediction spread range. The simulation underground model can be constructed by the actual underground space topological relationship, ventilation network, device link and real-time personnel distribution. The specific construction process of the model is not limited in the embodiments of the present application, as long as the model can accurately restore the physical environment, device association, air flow propagation and personnel distribution characteristics of the underground coal mine, and provide a simulation carrier that fits the actual scene for the evolution and diffusion of the prediction hidden danger event.

[0035] The simulation process of the simulation model under the mine can be visualized to obtain a simulation evolution image, and an edge information of a predicted swept range in the simulation evolution image is identified according to a preset feature recognition algorithm, a predicted evolution rate of the predicted hidden trouble event is determined by analyzing a change of the edge information of the predicted swept range in a unit time, and the specific preset feature recognition algorithm is not specifically limited in the embodiments of the present application. Further, in order to improve the accuracy of determining the predicted swept range, the method provided in the embodiments of the present application can specifically include the following steps when determining the predicted swept range based on the predicted hidden trouble event: determining an initial swept range according to the predicted hidden trouble event and the predicted hidden trouble level; identifying a predicted event feature corresponding to the predicted hidden trouble event, and determining a plurality of predicted hidden trouble routes based on the predicted event feature, each of the predicted hidden trouble routes matching at least one predicted event feature; determining a route intersection parameter by performing an intersection operation on each of the predicted hidden trouble routes and the initial swept range, and determining a route influence weight of each of the predicted hidden trouble routes based on the route intersection parameter; and superimposing each of the predicted hidden trouble routes and the initial swept range based on the route influence weight of each of the predicted hidden trouble routes, to determine a predicted swept range corresponding to the predicted hidden trouble event.

[0036] Specifically, a center point of the event corresponding to the predicted hidden trouble event can be identified first, and then a swept distance corresponding to the predicted hidden trouble level is determined according to a preset swept distance mapping relationship, wherein the preset swept distance mapping relationship is a corresponding relationship between the predicted hidden trouble level and the swept distance, and the specific content is not specifically limited in the embodiments of the present application, and finally a circular initial swept range is determined with the center point of the event as the center and the swept distance as the radius. The corresponding predicted event feature can be identified from the basic monitoring parameters corresponding to the predicted hidden trouble event, the predicted event feature is a core attribute that is strongly associated with the predicted hidden trouble event, can reflect the diffusion law of the predicted hidden trouble event, and affects the path, for example, when the predicted hidden trouble event is a belt tearing, the corresponding predicted event feature includes but is not limited to structural failure, belt running speed 2 m / s, main track central yard belt conveyor, and roller linkage relationship. The predicted hidden trouble route corresponding to the predicted event feature can be determined based on a preset feature path mapping relationship, the preset feature path mapping relationship is a corresponding relationship between the predicted event feature and a route generation rule, and the key data (such as pump station coordinate, roadway slope trend, and car stopping facility position) is read from the simulation evolution image based on the route generation rule, and the predicted hidden trouble route is determined according to the rule. The way of determining the predicted hidden trouble route is not specifically limited in the embodiments of the present application. For example, the predicted hidden trouble route matched with the predicted event feature can be an upstream and downstream extension path of the belt conveyor (matching the “belt running speed” feature), a roller fault associated path (matching the “roller linkage relationship” feature), and a transfer point conduction path (matching the “main track central yard belt conveyor” feature), each of the predicted hidden trouble routes needs to match at least one predicted event feature, and the predicted hidden trouble route can be a production line or a passing route.

[0037] After all the predicted hidden danger routes are determined, the predicted hidden danger routes can be intersected with the initial spread range, and the route influence weight of each predicted hidden danger route, i.e., the influence of the predicted hidden danger route on the initial spread range after the predicted hidden danger route occurs, is determined according to parameters such as intersection degree and intersection position. Finally, the range of the initial spread range that needs to be expanded by each predicted hidden danger route, i.e., the newly added expansion range, is determined based on each predicted hidden danger route and the route influence weight, and the final predicted spread range is obtained after all the newly added expansion ranges are superimposed with the initial spread range, so as to realize dynamic optimization and accurate expansion of the spread range, which not only ensures to cover the key area where the hidden danger may spread, but also avoids waste of emergency resources caused by excessive expansion of the range.

[0038] The predicted spread personnel are the workers in the predicted spread range. The predicted spread personnel can be determined by face feature recognition.

[0039] Step S130: Obtain the historical behavior response information of each predicted spread personnel, and determine the core personnel from all the predicted spread personnel based on the historical behavior response information of each predicted spread personnel and the predicted hidden danger event.

[0040] Specifically, the historical behavior response information of each predicted spread personnel in a historical working time period can be called from the supervision and inspection system according to the work number of each predicted spread personnel. The historical working time period can be a period of time before the current time, and the corresponding historical time length can be 5 days or 7 days. The specific time length is not limited in the embodiments of the present application. The historical behavior response information includes but is not limited to hidden danger disposal experience, special skill level, cooperation ability, and compliance operation record, etc. Each predicted spread personnel can be scored and evaluated by analyzing the historical behavior response information of each predicted spread personnel, and the core personnel can be determined from all the predicted spread personnel according to the scoring and evaluation result. Further, in order to improve the accuracy of determining the core personnel, when the core personnel is determined from all the predicted spread personnel based on the historical behavior response information of each predicted spread personnel and the predicted hidden danger event, it can specifically include: The prediction hazard event corresponding response skill dimension is identified, and the prediction response ability value of each prediction spread personnel when facing the prediction hazard event is determined based on the response skill dimension and the historical behavior response information of each prediction spread personnel. The associated communication spread personnel in the associated communication range corresponding to each prediction spread personnel is identified, and the associated prediction response ability value of each associated communication spread personnel is determined. The associated communication response value of each prediction spread personnel is determined based on the associated communication quantity of the associated communication spread personnel corresponding to each prediction spread personnel and the associated response average value of the associated prediction response ability value of all associated communication spread personnel. The prediction spread range is divided based on the event position of the prediction hazard event in the prediction spread range to obtain a plurality of division regions, and the response priority of each division region is different. The hazard response score of each prediction spread personnel is determined based on the prediction response ability value and the associated communication response value corresponding to each prediction spread personnel and the response priority of the division region in which the prediction spread personnel is located, and the prediction spread personnel with the highest hazard response score is determined as the core personnel.

[0041] Specifically, for any prediction spread personnel, the response skill dimension related to the prediction hazard event can be determined based on a preset feature recognition algorithm and a preset skill dimension mapping relationship. The dimension historical response information related to the response skill dimension is extracted from the historical behavior response information of the prediction spread personnel based on the identified response skill dimension. Finally, all dimension historical response information is quantitatively converted into the prediction response ability value of the prediction spread personnel when facing the prediction hazard event. Different prediction hazard events correspond to different response skill dimensions, that is, different contents need to be investigated and analyzed when facing different prediction hazard events. The preset skill dimension mapping relationship is the corresponding relationship between the prediction hazard event and the response skill dimension, and the specific content is not limited in the embodiments of the present application. The prediction response ability value is an evaluation value determined based on the historical performance of the prediction spread personnel.

[0042] The associated communication range of the prediction spread personnel is the range that can directly or online communicate with the prediction spread personnel, which is related to the communication range of the terminal device carried by the prediction spread personnel. The associated communication spread personnel in the associated communication range corresponding to the prediction spread personnel is identified, and the associated communication quantity of all associated communication spread personnel in the associated communication range is counted. The associated prediction response ability value of each associated communication spread personnel is extracted, and the average value of the associated prediction response ability value of all associated communication spread personnel is calculated to obtain the associated response average value. Finally, the associated communication quantity corresponding to the prediction spread personnel and the associated response average value are quantitatively converted to obtain the associated communication response value. The associated communication response value can be used to evaluate the team coordination support ability of the prediction spread personnel, that is, whether the prediction spread personnel can rely on the associated communication spread personnel that can directly or online communicate to form an efficient disposal team.

[0043] The event location can be divided into multiple divisional wave distances based on the event location and the wave distance between the event location and the edge point of the predicted wave range, and the predicted wave range is divided based on each divisional wave distance, for example, a first divisional wave distance (for example, a range of 30 meters in radius) is a first wave range with the highest response priority, a second divisional wave distance (for example, a range of 50 meters outside the first wave range) is a second wave range with medium response priority, and a third divisional wave distance (for example, a range of 100 meters outside the second wave range) is a third wave range with lower response priority.

[0044] The response weight corresponding to the predicted wave range where the predicted wave person is located is determined according to the response priority, and the higher the response priority, the higher the corresponding response weight. Finally, the predicted response capability value and the associated communication response value are weighted and operated based on the response weight, for example, the response weight is X, the predicted response capability value is A, and the associated communication response value is B. At this time, the hidden danger response score of the predicted wave person is X*(A+B). The hidden danger response score of each predicted wave person is determined based on the above method, and the predicted wave person with the highest hidden danger response score is determined as the core person.

[0045] By accurately identifying the response skill dimension corresponding to the predicted hidden danger event, and combining the historical behavior response information of the predicted wave person to calculate the predicted response capability value, the accurate adaptation of personnel handling capability and hidden danger type is facilitated. By counting the number of associated communications of the predicted wave person and the associated predicted response capability mean of the associated personnel, personnel with strong ability and effective driving of surrounding personnel for collaborative disposal are screened out, which is convenient for the hidden danger disposal mode of coal mine underground team cooperation, so as to solve the limitation of only paying attention to individual ability and ignoring cooperation efficiency in the traditional processing process. By dividing the location and level of the predicted hidden danger event into different response priority divisional areas, the screening process of the core person is considered in terms of ability adaptability, spatial accessibility and response timeliness, so as to ensure that the selected core person can quickly arrive at the hidden danger site for disposal.

[0046] Step S140: determining the standard response measure corresponding to the predicted hidden danger event according to the predicted hidden danger characteristic corresponding to the predicted hidden danger event, and generating a broadcast warning voice instruction based on the standard response measure and the predicted wave range.

[0047] Step S150: feeding back the broadcast warning voice instruction to the terminal device of the core person to remind the core person to guide and broadcast to other predicted wave persons according to the broadcast warning voice instruction.

[0048] Specifically, the standard response measures corresponding to each predicted hidden danger event are stored in advance in the supervision and inspection system, and can be retrieved from the supervision and inspection system database based on the predicted hidden danger characteristics after the predicted hidden danger characteristics corresponding to the predicted hidden danger event are identified. The extracted standard response measures are generally structured text, at which time the structured text needs to be transmitted to a voice synthesis module to generate a standard broadcast warning voice instruction (for example, in MP3 / WAV format, adapted to the underground communication terminal) using clear speech (moderate speech speed, key word re-reading) supported by the mine intrinsic safety terminal.

[0049] The core personnel ID is extracted, the real-time GIS coordinates of the core personnel at the current time are obtained through the personnel positioning module, it is confirmed that the core personnel is in the safety area within the predicted range, and the main channel + backup channel double-pushing mechanism is adopted relying on the voice intercom module and the underground communication network to ensure that the instruction is delivered: The main channel is the real-time pushing of the voice intercom module: automatically dialing the voice intercom number of the core personnel terminal, directly playing the broadcast warning voice instruction after connection, and displaying the instruction text on the terminal screen; The backup channel is an alarm pop-up window + voice reminder: if the main channel is not connected (such as weak signal), an alarm pop-up window (containing an instruction abstract) is pushed through the personnel positioning terminal, and a sound and light alarm of the terminal is triggered. The core personnel can play the voice instruction by clicking the pop-up window.

[0050] For the embodiments of the present application, by integrating the basic alarm events and the basic monitoring parameters for multi-source data complementary analysis, it is convenient to accurately predict the hidden danger events that may occur in the future period of time, effectively avoid the misjudgment risk triggered by single data, significantly improve the accuracy and forward-looking of the prediction results, and by quantifying the prediction results as a prediction hidden danger level, it is convenient to intuitively know the risk level that may be faced in the future period of time, so as to reserve sufficient response time for underground personnel. By accurately locking the prediction range and the affected personnel, and selecting the core personnel matched with the historical behavior response information, it is convenient to ensure that the hidden danger disposal is dominated by the personnel with matched ability. In addition, by accurately matching the exclusive standard response measures based on the prediction hidden danger characteristics, the randomness and non-standardization of experiential decision-making are avoided, and the disposal action is ensured to be scientific and compliant, so as to accurately realize the advanced identification of the coal mine hidden danger and timely take the response measures, and further improve the safety production level of the coal mine.

[0051] Further, in order to accurately distinguish the risk transmission intensity difference of different routes, the method provided by the embodiments of the present application can specifically include steps S210-S230 when determining the route influence weight of each predicted hidden danger route based on the route intersection parameter, as shown in Figure 2 ​Step S210: identifying the intersection section between each predicted hidden danger route and the initial spread range from the route intersection parameters, and comparing the intersection section with the original road section of each predicted hidden danger route to determine the intersection proportion corresponding to each predicted hidden danger route.

[0052] Specifically, the original road section coordinate sequence of each predicted hidden danger route can be retrieved from the simulation evolution image, and the GIS coordinates of the starting point, passing nodes and ending point corresponding to the original road section are determined. Meanwhile, the total length of the original road section can be calculated by accumulating the distance between two points in space. Similarly, the initial boundary coordinate set of the initial spread range is identified from the simulation evolution image, and the original road section coordinate sequence of each predicted hidden danger route is traversed. Whether the road section segment formed by each passing node and the adjacent node falls within the spatial boundary of the initial spread range is determined one by one by using a preset node judgment rule or a road section segment judgment rule. The coordinate sub-sequence of all coordinates within the range is integrated to form the intersection road section corresponding to the predicted hidden danger route, and the coordinate set of the intersection road section is determined. The length of the coordinate sub-sequence of the intersection road section is accumulated by using the same spatial distance formula as the total length of the original road section, and the total length of the intersection road section is obtained. For example, the road section length corresponding to the coordinate sub-sequence within the initial spread range (radius 30 m) in the belt conveyor extension route is 30 m. Finally, the intersection proportion corresponding to each predicted hidden danger route is determined according to the intersection proportion calculation formula, and the intersection proportion calculation formula is intersection proportion = (intersection road section length / total length of original road section) x 100%.

[0053] Step S220: identifying the predicted hidden danger trend of each predicted hidden danger route, and determining the evolution fitting degree corresponding to each predicted hidden danger route based on the predicted evolution trend corresponding to each predicted hidden danger trend and the initial spread range.

[0054] Specifically, the linear fitting algorithm can be used to fit the original road section coordinate sequence of each predicted hidden danger route to determine the predicted hidden danger trend corresponding to each predicted hidden danger route. The semantic segmentation algorithm can be used to segment the hidden danger core area (such as the high concentration area of gas and the water covering area) from each frame of simulation evolution image to generate a binary mask image (the hidden danger area is foreground and the background is black). Then, the center point coordinates of the hidden danger core area in each frame of image are calculated based on the mask image, and the center point time sequence trajectory is formed by converting the GIS coordinates of the actual underground into the actual GIS coordinates through the pixel-three-dimensional coordinate mapping relationship of the GIS mine map. Finally, the center point time sequence trajectory is linearly fitted, and the predicted evolution trend corresponding to the initial spread range is calculated by using the least square method. The specific way of determining the predicted hidden danger trend corresponding to each predicted hidden danger route and determining the predicted evolution trend corresponding to the initial spread range is not limited in the embodiments of the present application.

[0055] The predicted hazard trend corresponding to each predicted hazard route is fitted with the predicted evolution trend, a fitting angle between the predicted hazard trend corresponding to each predicted hazard route and the predicted evolution trend is determined, and the fitting angle is quantified as an evolution fitting degree corresponding to each predicted hazard route. The smaller the fitting angle is, the higher the evolution fitting degree is.

[0056] Step S230: determining a route influence weight of each predicted hazard route based on the intersection proportion and the evolution fitting degree corresponding to each predicted hazard route.

[0057] Specifically, the intersection proportion and the evolution fitting degree corresponding to each predicted hazard route are normalized and quantified, and the route influence weight of each predicted hazard route can be obtained. The larger the intersection proportion is and the higher the evolution fitting degree is, the higher the route influence weight is, which also represents that the impact degree of the corresponding predicted hazard route on the initial impact range after the abnormality occurs is greater.

[0058] For the embodiments of the present application, the intersection section of the predicted hazard route and the initial impact range is accurately identified from the route intersection parameter, the intersection proportion corresponding to each predicted hazard route is determined, which provides an objective and quantifiable spatial correlation basis for route influence weight determination. In addition, the predicted hazard trend of each predicted hazard route is identified, and the predicted evolution trend corresponding to the initial impact range is matched and analyzed, which facilitates the weight calculation to fully conform to the actual hazard propagation law. Finally, the route influence weight is calculated based on the dual-dimension fusion of the intersection proportion and the evolution fitting degree, which facilitates the multi-factor collaborative calibration of weight assignment, ensures the coverage of high correlation areas of hazards, and facilitates the accurate differentiation of risk transmission intensity differences of different routes.

[0059] Further, when the route influence weight of the predicted hazard route is greater than a preset weight threshold, the method provided by the embodiments of the present application can further include: The predicted hidden danger route with a route influence weight greater than the preset weight threshold is determined as a hidden danger route of interest, and hidden danger route of interest corresponding intersection road segment coordinates are identified; intersection hidden danger routes intersecting with the hidden danger route of interest are identified from other non-hidden danger routes of interest based on route intersection parameters, and a total number of route overlaps of all intersection hidden danger routes is identified, the other non-hidden danger routes of interest being other predicted hidden danger routes except the hidden danger route of interest; intersection road segment coordinates of each intersection hidden danger route are identified, each intersection road segment coordinate is compared with the hidden danger route of interest corresponding intersection road segment coordinate, an intersection type between each intersection hidden danger route and the hidden danger route of interest corresponding intersection road segment is determined, and a proportion of the intersection type corresponding to the hidden danger route of interest is determined according to the intersection type between each intersection hidden danger route and the hidden danger route of interest corresponding intersection road segment, the intersection type including upstream intersection and downstream intersection; a weight adjustment value of the hidden danger route of interest is determined based on the total number of route overlaps and the proportion of the intersection type, and the route influence weight of the hidden danger route of interest is adjusted based on the weight adjustment value.

[0060] Specifically, when the route influence weight of the predicted hidden danger route is greater than the preset weight threshold, it is indicated that the predicted hidden danger route may have a greater impact on the initial scope of influence after an abnormality occurs, therefore, the predicted hidden danger route with the route influence weight greater than the preset weight threshold is determined as the hidden danger route of interest, the hidden danger route of interest is further analyzed, the corresponding route influence weight is adjusted, so as to more accurately optimize the final predicted scope of influence, and provide a more targeted basis for core personnel matching and standard response measure formulation. The specific value of the preset weight threshold is not limited in the embodiments of the present application.

[0061] For convenience of description, the predicted hidden danger route with the route influence weight greater than the preset weight threshold can be determined as the hidden danger route of interest, and the intersection road corresponding to the hidden danger route of interest can be determined as the hidden danger route of interest, and the coordinate subsequence of the hidden danger route of interest can be integrated as the hidden danger route of interest. Taking the hidden danger route of interest as a reference, spatial intersection judgment is performed on all other non-hidden danger routes of interest one by one, intersection hidden danger routes intersecting with the hidden danger route of interest are identified, if any two line segments satisfy that there is a common point in the three-dimensional space or there is an overlapping segment in the two-dimensional plane and the Z coordinate range overlaps, it is determined that the two routes intersect, the other non-hidden danger routes of interest intersecting with the hidden danger route of interest are determined as the intersection hidden danger routes, and the total number of route overlaps of all intersection hidden danger routes is counted.

[0062] Based on the predicted hazard direction of the routes of concern and the coordinates of the concerned road segments, the intersection of the concerned road segments is divided into two segments, which can be based on the midpoint of the intersection of the concerned road segments. These two segments can be clearly defined as an upstream segment (deviating from the predicted hazard direction) and a downstream segment (following the predicted hazard direction). The coordinates of the intersection point between each intersection of the hazard routes and the concerned road segment are determined. If the intersection point falls within the upstream segment, the intersection type between the hazard route and the corresponding concerned intersection segment of the concerned hazard route is determined as an upstream intersection; if the intersection point falls within the downstream segment, the intersection type is determined as a downstream intersection. Based on the intersection types of multiple intersections of the concerned hazard routes, the proportion of each intersection type is determined.

[0063] Finally, based on the preset weight adjustment value mapping relationship, the total number of overlapping routes, and the proportion of intersection types, the weight adjustment value corresponding to the route with potential hazards is determined. The preset weight adjustment value mapping relationship is the correspondence between the parameter combination of the total number of overlapping routes and the proportion of intersection types and the weight adjustment value. The specific content is not specifically limited in this embodiment. The weight adjustment value is calculated collaboratively based on the total number of overlapping routes and the proportion of intersection types, which facilitates the dynamic calibration of the weight of the route with potential hazards and avoids weight deviation caused by single-dimensional judgment.

[0064] Furthermore, to facilitate improving the balance and effectiveness of overall hazard mitigation, the method provided in this application embodiment may further include: When core personnel provide guidance to other predicted affected personnel based on the broadcast warning voice commands, the system acquires the core personnel's status parameters within a preset analysis time period and determines their current status score based on these parameters. It then determines the execution parameters for other predicted affected personnel based on standard response measures and their corresponding response effectiveness scores, including execution rate and completion rate. Based on the current status score and response effectiveness score, the system determines the core personnel's guidance broadcast score. When the guidance broadcast score is below a preset threshold, a low-execution zone is identified based on the response effectiveness scores of other predicted affected personnel. Finally, based on the response effectiveness scores of each other predicted affected personnel within the low-execution zone, auxiliary personnel are identified, and the broadcast warning voice commands are fed back to their terminal devices to remind them to provide auxiliary guidance to other predicted affected personnel within the low-execution zone. The auxiliary personnel are the other predicted affected personnel with the highest response effectiveness scores within the low-execution zone.

[0065] Specifically, the preset analysis time period is a period of time after the core personnel guides and broadcasts to other predicted affected personnel according to the broadcast warning voice instruction. The preset analysis time period can correspond to a time length of 2 minutes or 3 minutes, and the specific time length is not limited in the embodiments of the present application. The state parameters include, but are not limited to, instruction broadcast time length, voice intelligibility, terminal online time length, position movement frequency, etc., which can be collected through personnel positioning terminals (viewing position trajectory, online state), voice intercom modules (collecting broadcast recording time length, volume / noise detection), and terminal operation logs (recording instruction viewing times). The current state score of the core personnel can be determined based on the preset state scoring formula and the state parameters, wherein the preset state scoring formula is: current state score = broadcast effective time length ratio × 30% + voice intelligibility × 20% + terminal online time length ratio × 30% + position movement frequency adaptation degree × 20%. For example, the broadcast effective time length ratio of a certain core personnel is 80%, the voice intelligibility is 90%, the online time length ratio is 100%, and the movement frequency adaptation degree is 80%, then the current state score of the core personnel = 80 × 0.3 + 90 × 0.2 + 100 × 0.3 + 80 × 0.2 = 88 points.

[0066] The execution behavior information of the other predicted affected personnel is obtained, and the execution rate and the execution completion degree of the other predicted affected personnel in the execution of the standard response measures are determined based on the execution behavior information, wherein the execution rate is used to represent the reaction rate of the other predicted affected personnel in executing the corresponding standard response measures after the core personnel guides and broadcasts, and the execution completion degree is used to represent the difference between the actual execution measures and the standard response measures. The response effect score of the other predicted affected personnel can be determined based on the preset response effect scoring formula and the execution parameters, wherein the preset response effect scoring formula is: response effect score = execution rate × 40% + execution completion degree × 60%.

[0067] The current state score and the response effect score are summed to obtain the guidance broadcast score of the core personnel. When the guidance broadcast score is not less than the preset score threshold, it represents that the guidance broadcast behavior of the core personnel is effective, the execution response of the other predicted affected personnel to the standard response measures reaches the expected standard, and the instruction transmission and landing execution of the current hidden danger disposal is in a controllable state. When the guidance broadcast score is less than the preset score threshold, it represents that the guidance broadcast behavior of the core personnel does not reach the preset effective standard, and the execution response of the other predicted affected personnel to the standard response measures has a significant deviation, and the instruction transmission and landing execution of the current hidden danger disposal is in an out-of-control or weakly controlled state, and the supplementary guidance broadcast mechanism needs to be started immediately.

[0068] The area can be divided based on the response effect score corresponding to each other predicted wave and personnel, a plurality of response division areas are obtained, the score difference before the response effect scores corresponding to any two other predicted wave and personnel in each response division area is lower than a preset difference threshold, the average response score of the response effect scores of all other predicted wave and personnel in each response division area is calculated, and the response division area with the lowest average response score is determined as a low execution area, the other predicted wave and personnel with the highest response effect score in the low execution area are selected as auxiliary personnel, and the broadcast warning voice instruction is fed back to the terminal device of the auxiliary personnel to remind the auxiliary personnel to assist and guide broadcast in other predicted wave and personnel in the low execution area according to the broadcast warning voice instruction.

[0069] By identifying the auxiliary personnel from the low execution area in time to assist the core personnel in guiding broadcast, the guiding gap of the low execution area can be accurately made up, a collaborative disposal mode of overall planning of the core personnel and deep cultivation of the auxiliary personnel in the area is formed, the guiding inefficiency problem caused by wide coverage and limited communication of a single core personnel is avoided, and therefore the balance and effectiveness of the overall hidden danger disposal can be improved.

[0070] The application embodiment provides a supervision and monitoring system, as shown in Figure 3 as shown in Figure 3 The supervision and monitoring system 300 shown in the drawings includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the supervision and monitoring system 300 can also include a transceiver 304. It should be noted that in actual application, the transceiver 304 is not limited to one, and the structure of the supervision and monitoring system 300 does not constitute a limitation on the application embodiments.

[0071] The processor 301 can be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can realize or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure content. The processor 301 can also be a combination of computing functions, such as one or more microprocessor combinations, combinations of DSP and microprocessor, etc.

[0072] The bus 302 can include a path that transmits information between the above-mentioned components. The bus 302 can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 302 can be divided into an address bus, a data bus, a control bus, and the like. For convenience of representation, Figure 3 Only one line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0073] The memory 303 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this.

[0074] The memory 303 is used to store application program codes for implementing the scheme of the present application, and is controlled by the processor 301 to execute. The processor 301 is used to execute the application program codes stored in the memory 303 to realize the content shown in the foregoing method embodiments.

[0075] The supervisory monitoring system includes, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Personal Computers), PMPs (Portable Multimedia Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. It can also be a server or the like. Figure 3 The supervisory monitoring system shown is only an example and should not bring any limitation to the functions and use range of the embodiments of the present application.

[0076] The embodiments of the present application provide a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program runs on a computer, the computer can execute the corresponding content in the foregoing method embodiments.

[0077] The embodiment of the present application provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to realize the method in any of the above embodiments.

[0078] It should be understood that, although each step in the flowchart of the accompanying drawings is shown in sequence according to the indication of the arrow, these steps are not necessarily executed in sequence according to the indication of the arrow. Unless explicitly stated herein, the execution of these steps is not strictly limited in sequence, and they can be executed in other sequences. Moreover, at least part of the steps in the flowchart of the accompanying drawings can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or sub-steps or stages of other steps.

[0079] The above only describes some embodiments of the present application, and it should be pointed out that, for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be regarded as the protection scope of the present application.

Claims

1. A method for auxiliary safety supervision and inspection applied in coal mines, characterized in that, include: Acquire basic alarm events and basic monitoring parameters, and determine predicted potential hazard events and predicted hazard levels based on the basic alarm events and basic monitoring parameters; The predicted impact range is determined based on the predicted potential hazard event, and the predicted affected personnel are determined based on the predicted impact range and the predicted evolution and diffusion rate of the predicted potential hazard event. Obtain historical behavioral response information for each predicted affected person, and based on the historical behavioral response information of each predicted affected person and the predicted potential event, identify core personnel from all predicted affected personnel; Based on the predicted hazard characteristics corresponding to the predicted hazard event, the standard response measures corresponding to the predicted hazard event are determined, and a broadcast warning voice command is generated based on the standard response measures and the predicted impact range. The broadcast warning voice command is fed back to the terminal device of the core personnel to remind them to guide other predicted affected personnel to broadcast the warning according to the broadcast warning voice command.

2. The method for auxiliary safety supervision and inspection applied to coal mines according to claim 1, characterized in that, The determination of the predicted impact range based on the predicted potential hazard event includes: The initial impact range is determined based on the predicted potential hazards and the predicted hazard levels. Identify the predicted event features corresponding to the predicted potential hazard events, and determine multiple predicted hazard routes based on the predicted event features, with each predicted hazard route matching at least one predicted event feature; The intersection of each predicted hazard route with the initial affected area is used to determine the route intersection parameter. Based on the route intersection parameter, the route influence weight of each predicted hazard route is determined. Based on the route influence weight of each predicted hazard route, each predicted hazard route is superimposed with the initial affected area to determine the predicted affected area corresponding to the predicted hazard event.

3. The method for auxiliary safety supervision and inspection applied to coal mines according to claim 2, characterized in that, The determination of the route influence weight for each predicted hazard route based on the route intersection parameters includes: Identify the intersection segment between each predicted hazard route and the initial affected area from the route intersection parameters, and compare the intersection segment with the original segment of each predicted hazard route to determine the intersection ratio corresponding to each predicted hazard route; Identify the predicted hazard trajectory of each predicted hazard route, and determine the evolution fit degree corresponding to each predicted hazard route based on the predicted evolution trajectory corresponding to the initial affected range. Based on the intersection ratio and evolution fit degree of each predicted hazard route, the route influence weight of each predicted hazard route is determined.

4. The safety auxiliary supervision and inspection method for coal mines according to claim 3, characterized in that, When the route impact weight of the predicted hazard route is greater than a preset weight threshold, it also includes: The predicted hazard routes with a route influence weight greater than a preset weight threshold are identified as hazard routes of concern, and the coordinates of the concern road segments corresponding to the intersection of the hazard routes of concern are identified. Based on the route intersection parameters, the intersection hazard routes that intersect with the hazard routes of concern are identified from other non-concerned hazard routes, and the total number of route superpositions of all intersection hazard routes is identified. The other non-concerned hazard routes are other predicted hazard routes besides the hazard routes of concern. Identify the coordinates of the intersection segments of each intersection hazard route, compare the coordinates of each intersection segment with the coordinates of the concerned segment, determine the intersection type between each intersection hazard route and the concerned intersection segment, and determine the proportion of the intersection type corresponding to the concerned hazard route based on the intersection type between each intersection hazard route and the concerned intersection segment corresponding to the concerned hazard route. The intersection type includes upstream intersection and downstream intersection. Based on the total number of overlapping routes and the proportion of intersection types, the weight adjustment value of the routes with potential hazards is determined, and the route influence weight of the routes with potential hazards is adjusted based on the weight adjustment value.

5. The method for auxiliary safety supervision and inspection applied to coal mines according to claim 1, characterized in that, Based on the historical behavioral response information of each predicted affected person and the predicted potential event, core personnel are identified from all predicted affected persons, including: Identify the coping skills dimension corresponding to the predicted potential event, and based on the coping skills dimension and the historical behavioral coping information of each predicted affected person, determine the predicted coping ability value of each predicted affected person when facing the predicted potential event; Identify the related communication affected persons within the scope of each predicted affected person's communication, and the associated predicted response capability value of each related communication affected person. Based on the number of related communications of each predicted affected person's related communication affected persons and the average associated response capability value of all related communication affected persons, determine the associated communication response value of each predicted affected person. Based on the location of the predicted potential hazard event within the predicted impact range, the predicted impact range is divided into multiple regions, each with a different response priority. Based on the predicted response capability value and the associated communication response value corresponding to each predicted affected person, as well as the response priority of the divided area, the hidden danger response score of each predicted affected person is determined, and the predicted affected person with the highest hidden danger response score is determined as the core personnel.

6. The method for auxiliary safety supervision and inspection applied to coal mines according to claim 5, characterized in that, Also includes: When the core personnel provide guidance to other predicted affected personnel based on the broadcast warning voice instructions, the status parameters of the core personnel within a preset analysis time period are obtained, and the current status score of the core personnel is determined based on the status parameters. Based on the standard response measures, the execution parameters for other predicted affected personnel are determined, and the response effectiveness scores for other predicted affected personnel are determined based on the execution parameters. The execution parameters include execution rate and execution completion rate. The guidance broadcast score of the core personnel is determined based on the current status score and the response effect score. When the guidance broadcast score is lower than the preset score threshold, the low execution area is determined based on the response effect scores of other predicted affected personnel. Based on the response performance score of each other predicted affected person in the low execution area, an assistant is identified, and the broadcast warning voice command is fed back to the assistant's terminal device to remind the assistant to provide auxiliary guidance to other predicted affected persons in the low execution area according to the broadcast warning voice command. The assistant is the other predicted affected person with the highest response performance score in the low execution area.

7. A regulatory monitoring system, characterized in that, The regulatory oversight system includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform a safety auxiliary supervision and monitoring method for coal mines according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, include: The system stores a computer program capable of being loaded by a processor and executed as described in any one of claims 1-6, which is an auxiliary safety supervision and monitoring method for coal mines.

9. A computer program product, characterized in that, The method includes a computer program that, when executed by a processor, implements the steps of any one of claims 1-6 for a safety auxiliary supervision and monitoring method applied to a coal mine.

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