Coal mine safety risk analysis, research and judgment method, equipment and medium

Abstract

The invention relates to the field of coal mine safety risk analysis, in particular to a coal mine safety risk analysis research and judgment method, equipment and a medium. The method comprises the steps of obtaining a first risk source corresponding to first historical security risk information in a historical security risk information database, and determining a dangerous case state when a risk occurs and a state after the dangerous case is eliminated according to risk recording time corresponding to the first risk source; determining a data updating mode according to a data acquisition mode corresponding to the dangerous case state; determining a real-time state and a historical state of the first risk source by using a data updating mode, wherein the historical state is generated based on the data updating mode, and a generated event is later than a time point of danger elimination; and determining whether the current security risk level of the risk source is degraded or not based on the real-time state and the historical state of the first risk source. In this way, the problems of mine hidden danger troubleshooting and safety risk re-occurrence are solved.

Description

Technical Field

[0001] The present invention relates to the field of coal mine safety risk analysis, and in particular to a method, device and medium for analyzing and judging coal mine safety risks. Background Art

[0002] The coal mining industry is a high-risk industry. Although China has increased the intensity of coal mine safety management in recent years and the number of coal mine safety accidents across the country has shown a significant downward trend, the total number of accidents is still large. According to incomplete statistics of relevant departments, among coal mine safety accidents, safety hazards left over from history and the recurrence safety risks in the same area account for a large proportion.

[0003] In the prior art, the investigation of mine safety hazards often stays on surface problems such as equipment aging, support structure, mine car route and mine dust, and pays less attention to the relevance of various problems, resulting in incomplete investigation of hazards and recurrence safety risk problems in the places that have been investigated. Summary of the Invention

[0004] To solve the problems of mine hazard investigation and recurrence safety risks, at least one aspect and advantage of the present invention will be partially described in the following description, or will be obvious from the description, or can be obtained by practicing the subject matter of the present disclosure.

[0005] According to a first aspect of the present invention, a method for analyzing and judging coal mine safety risks, the method includes: Obtain the first risk source corresponding to the first historical safety risk information in the historical safety risk information database, and determine the danger situation state and the state after the danger situation is eliminated when the risk occurs according to the risk record time corresponding to the first risk source; Determine the data update method according to the data collection method corresponding to the danger situation state; Use the data update method to determine the real-time state and historical state of the first risk source, the historical state is generated based on the data update method and the generation event is later than the time point when the danger situation is eliminated, and the historical state is obtained by sampling the historical data of the first risk source, and the sampling window is determined according to the distribution information of the recurrence of safety risks; Determine whether the current safety risk level of the risk source deteriorates based on the real-time state and historical state of the first risk source.

[0006] According to an embodiment of the present invention, the historical safety risk information database is constructed in the following manner; Conduct a risk factor analysis on penalty cases to construct historical safety risk information; Annotate the correlation relationship and risk categories of risk factors formed in the accident evolution process for penalty cases, determine the level, risk source, danger state, danger elimination state of historical safety risk information, and the data source used to judge safety risks, and perform hot zone annotation corresponding to the danger state and the state after danger elimination, where the hot zone annotation is used to prompt the risk rectification result or safety risk; Verify the data source used to judge safety risks; Include historical safety risk information into the database.

[0007] According to an embodiment of the present invention, the data update method is determined as follows: According to the data source used to judge safety risks corresponding to the first historical safety risk information, determine the type of the data source and the spatial position of the risk source; Determine the Internet of Things devices arranged in the roadway where the risk source is located according to the spatial position of the first risk source and the type of the data source, and the output of the Internet of Things devices meets the configuration of the data source used to judge safety risks; Determine the data update method based on the Internet of Things devices.

[0008] According to an embodiment of the present invention, determine the re-occurring safety risk information associated with the historical safety risk information according to the correlation relationship of risk factors.

[0009] According to an embodiment of the present invention, the determination process of the re-occurring safety risk information includes: According to the correlation relationship of risk factors corresponding to the first historical safety risk information, determine the second risk category associated with the risk category to which the first historical safety risk belongs; Obtain the historical safety risk information whose risk occurrence time is after the danger elimination of the first historical safety risk information and whose risk category includes the second risk category as the re-occurring safety risk information.

[0010] According to an embodiment of the present invention, the data update method is determined as follows: Determine the type of the data source according to the type corresponding to the historical safety risk information; Determine the roadway where the risk source is located according to the risk source corresponding to the historical safety risk information; Select the Internet of Things devices according to the output results of the Internet of Things devices in the roadway where the risk source is located, and the output of the Internet of Things devices covers the risk source; Determine the data update method based on the Internet of Things devices.

[0011] According to an embodiment of the present invention, the sampling window is determined as follows; Obtain the risk category to which the historical safety risk information belongs, and determine the first time interval according to the average occurrence frequency of the safety risk after the danger is eliminated under this risk category; Obtain the risk source corresponding to the historical safety risk information, and determine the second time interval according to the time when the safety risk first occurs after the danger is eliminated for this risk source; Take the smaller value of the first time interval and the second time interval as the sampling window.

[0012] According to an embodiment of the present invention, when calculating the second time interval, the risk level of the safety risk that first occurs is not higher than the risk level of the first historical safety risk information.

[0013] According to a second aspect of the present invention, an electronic device includes a processor and a memory; the memory is used to store a program; the processor executes the program to implement the coal mine safety risk analysis and judgment method described in the first aspect.

[0014] According to a third aspect of the present invention, a computer-readable storage medium stores a program, and the program is executed by a processor to implement the coal mine safety risk analysis and judgment method described in the first aspect.

[0015] The beneficial effects of the present invention are as follows: Through the above-mentioned coal mine safety risk analysis and judgment method, a more comprehensive investigation or a more refined method can be selected according to the specific situation. Based on the analysis of various risk factors and the correlation relationships of the risk factors, the safety risk hidden dangers of the mine can be effectively investigated, and the probability of the recurrence of safety risks can be determined, thereby reducing the occurrence of safety accidents and the probability of the recurrence of safety risks. Protect the personal safety of the staff and avoid the economic losses and hazards brought by accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Shows the flowchart of the coal mine safety risk analysis and judgment method. DETAILED DESCRIPTION

[0017] Now the content of the present disclosure will be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those of ordinary skill in the art to better understand and thus implement the content of the present disclosure, rather than implying any limitation on the scope of the present disclosure.

[0018] As used herein, the term "comprising" and its variants are to be construed as open-ended terms meaning "including but not limited to". The term "based on" is to be construed as "at least partially based on". The terms "one embodiment" and "an embodiment" are to be construed as "at least one embodiment". The term "another embodiment" is to be construed as "at least one other embodiment". The orientation or positional relationships indicated by the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "vertical", "horizontal", "lateral", "longitudinal", etc. are based on the orientation or positional relationships shown in the drawings. These terms are mainly used to better describe the present application and its embodiments, and are not used to limit that the indicated devices, elements or components must have a specific orientation, or be constructed and operated in a specific orientation. Also, in addition to being used to represent orientation or positional relationships, some of the above terms may also be used to represent other meanings. For example, the term "upper" may also be used to represent a certain attachment relationship or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in the present application can be understood according to specific circumstances. In addition, the terms "installed", "set", "provided with", "connected", "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral structure; it may be a mechanical connection or an electrical connection; it may be directly connected, or indirectly connected through an intermediate medium, or there may be internal communication between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, the meaning of "a plurality of" is two or more.

[0019] According to one embodiment of the present invention, a method for analyzing and judging coal mine safety risks, the method comprising the following steps: Obtain the first risk source corresponding to the first historical safety risk information in the historical safety risk information database, and determine the danger state at the time of risk occurrence and the state after the danger is eliminated according to the risk record time corresponding to the first risk source; Determine the data update method according to the data collection method corresponding to the danger state; Use the data update method to determine the real-time state and historical state of the first risk source, where the historical state is generated based on the data update method and the generation event is later than the time point when the danger is eliminated, and the historical state is obtained by sampling the historical data of the first risk source, and the sampling window is determined according to the distribution information of the recurrence of safety risks; Determine whether the current safety risk level of the risk source deteriorates based on the real-time status and historical status of the first risk source.

[0020] The coal mine safety risk analysis and judgment method of the present invention includes several modules. To better understand the coal mine safety risk analysis and judgment method of the present invention, the system of the platform is briefly introduced in advance.

[0021] Basic information module: Responsible for collecting relevant information of the mine and storing the data into the mine information database through the data interface. Information collection includes: collecting mine dynamic information from the mine report information system through the mine-end safety risk analysis and judgment system management tool or mobile terminal and collecting basic fixed information from the single-line electronic ledger system, and collecting relevant data from the comprehensive display module, risk grading module, hidden danger investigation and management module, auxiliary statistical analysis module, and auxiliary query function module, including: collecting data uploaded by underground Internet of Things devices and collecting manually filled data. Data storage module: Responsible for collecting the data uploaded by the basic information module and other modules, and storing the collected data into the mine information database after structured arrangement, and classifying and summarizing the relevant data entered and collected; the mine information database includes: mine structure information database, mine basic information database, mine Internet of Things device information database, mine organization information database, mine professional type of work information database, underground Internet of Things device upload database, and manually filled data information database. Comprehensive display module: Includes a large screen display function, and the displayed content includes: mine basic information, mine personnel information, mine risk situation, mine hidden danger information, mine monitoring data, underground roadway ventilation oxygen content, underground gas concentration, and comprehensive alarm data. Risk grading module: Classify the mine risks to achieve mine risk early warning; classify the risks through the comprehensive display module and the mine report information system, and display them. Adopt three-level risk analysis and control for risk grading; achieve multiple hazard source linkage early warning for high-risk areas, hidden dangers, and accidents. Hidden danger investigation and management module: Includes hidden danger closed-loop management, realizes hidden danger analysis, hidden danger risk control, hidden danger investigation, reporting, handling, rectification, and archiving management; realizes the collection, classification, statistics, treatment, monitoring, and query of hidden dangers. Auxiliary statistical function module: Statistically analyze various risks, hidden dangers, personnel locations, entry times, entry frequencies, underground vehicles, and facilities in the mine according to the data of the risk grading module and the hidden danger investigation and management module, and display the information and data in real time. Auxiliary query function module: Realize the query of mine report information, mine hidden danger investigation and management information, fully mechanized mining and heading face mining replacement plan information, underground vehicle information, underground roadway information, underground equipment location information, above-ground organization information, and underground professional type of work personnel. Data Association Module: Through data analysis, it combines the mine business system with the coal mine safety risk analysis and judgment system, associates the safety risk analysis and judgment system with data, and realizes risk early warning and control, hidden danger closed-loop management, and real-time information analysis and display; Permission Management Module: Manages all functions in the coal mine safety risk analysis and judgment system through login and log functions; Function permissions are assigned to the mine level and section level, including: viewing, filling, analyzing, querying, etc.; Personal permissions are set to the team level and individuals, including viewing, analyzing, querying; When personal permissions are assigned, permissions are bound to users at the mine level and section level, and permissions for teams and below are dynamically generated; Personal permissions include: viewing, analyzing, querying.

[0022] In this embodiment, the coal mine safety risk analysis and judgment method is applied in multiple modules, including the following steps. First, obtain the first historical safety risk source from the safety risk information database, and divide the danger situation state when the risk occurs and the danger situation state after the risk is eliminated according to the time corresponding to the first risk source; Secondly, determine the update method of the information data in the safety risk information database according to the data collection method corresponding to the danger situation state; Thirdly, determine the real-time state and historical state of the first risk source according to the data update method; Finally, determine whether the current safety level deteriorates based on the real-time state and historical state of the first risk source, that is, determine whether the risk source has a higher risk.

[0023] Specifically, the coal mine safety risk analysis and judgment method of the present invention can effectively identify the current state of the risk source that has experienced a safety risk event by collecting and sorting out the information on the investigation and treatment of mine hidden dangers, determine the current safety level of the risk source, and predict the probability of the current risk source having a safety risk event again, serving as the information basis for formulating prevention strategies.

[0024] Specifically, the safety risk information database is stored in the data storage module. The database collects data information of mines that have experienced safety risks in history, including at least mine location coordinate information, safety risk occurrence time, safety risk level, Internet of Things device information of the mine, etc. Obtain the first risk source according to the demand, and the first risk source is the source of the risk corresponding to the first historical safety risk information. Then, according to the corresponding records of the first risk source, such as the risk occurrence time, risk category, danger situation state when the risk occurs, and the state after the danger situation is eliminated, etc. For example: when the danger situation is a fire, the relevant risk source records should at least include factors related to the fire such as the occurrence time, occurrence location, fire level, fire affected area, dust concentration in the roadway, cable condition (aging degree), combustible material condition, fire extinguishing equipment condition, electrical equipment condition, etc., and use these factors as the parameters of the danger situation state when the risk occurs.

[0025] Specifically, the data update method means that for different risk sources, their roadway positions are different, and the IoT devices used to collect safety risk-related data are also different. Correspondingly, there will be different information transmission methods and different data update methods. In addition, the update of hardware devices will also cause interface changes, thus causing changes in input sources. Therefore, when determining the data update method, manual intervention may sometimes be required for screening, so there will be different methods for determining data updates.

[0026] Specifically, the real-time status and historical status of the first risk source are determined according to the data update method. The historical status is obtained by sampling the historical data of the first risk source according to the data update method, and the generation time of this historical event is later than the time when the danger is eliminated, and the sampling window is determined according to the distribution information of the recurrence of safety risks. To more clearly show the historical status of the first risk source, clarify the occurrence entity, occurrence time, data sampling time, etc. of the historical status.

[0027] Specifically, the branch comparison between the real-time status and the historical status is determined according to the method preset by the system, and then combined with the historical trend to determine whether the risk source has deteriorated, that is, to determine whether the risk source has improved after treatment after the event occurs, and whether the probability of recurrence of the risk has decreased, etc.

[0028] According to an embodiment of the present invention, the historical safety risk information database is constructed as follows; Analyze the risk factors of the penalty cases to construct historical safety risk information; Mark the correlation relationship and risk category of the risk factors formed during the accident evolution process of the penalty cases, determine the level, risk source, danger state, danger elimination state of the historical safety risk information, and the data source used to judge the safety risk, and perform hot zone marking corresponding to the danger state and the state after danger elimination. The hot zone marking is used to prompt the risk rectification result or safety risk; Verify the data source used to judge the safety risk; Include the historical safety risk information into the database.

[0029] In this embodiment, the construction method of the safety risk information database is introduced. First, the risk factors of penalty cases are analyzed to form historical safety risk information. Secondly, the correlation relationships and risk categories of risk factors formed during the evolution process of penalty cases are described. The level, risk source, danger situation status, danger elimination status, and data sources used to judge safety risks of historical safety risk information are determined through the correlation relationships between different risk factors and the categories to which the risk factors belong; and hot zone markings are made based on the status during the occurrence of danger situations in the same area and the status after the danger situations are eliminated. Finally, the data sources used to judge safety risks are verified. If the data sources meet the system requirements, the historical safety risk information is put into the database.

[0030] Specifically, the correlation relationship of risk factors refers to the correlation relationships between different risk factors. For example, if the fire extinguisher is not inspected properly during vehicle inspection, it may cause a fire; if there is a mechanical equipment failure that causes the gas outlet pipe of the biological pond to be blocked, it may cause a sudden increase in the content of combustible gas in the area; if a safety helmet is forgotten to be worn, it may cause falling gravel to injure the head, etc. When determining information such as the level, risk source, and danger situation status of safety risk information, the correlation relationships of risk factors need to be considered. For example, if a risk factor is associated with many other risk factors, its risk level should be increased accordingly. Another example is that if a risk factor is associated with another risk factor with a very high risk level, its risk level should also be increased accordingly. In addition, the correlation relationship of risk factors will also directly affect the danger situation status when a danger situation occurs.

[0031] Specifically, penalty cases refer to existing safety incidents. On a small scale, such as not wearing a safety helmet resulting in personal injuries, entering a dangerous area without taking corresponding protective measures, and not conducting corresponding inspections before work. On a large scale, such as fires, gas explosions, and equipment operation problems resulting in serious injuries to personnel, etc.

[0032] Specifically, hot zone markings are used to prompt the results of risk rectification or safety risks. That is, by comparing the danger situation status of the area where a danger situation occurs with the status of the same area after the danger situation is eliminated, the areas where danger situations may occur again are concerned, that is, the hot zones, to prompt that there are certain safety risks in this area and safety rectification is required.

[0033] According to an embodiment of the present invention, the data update method is determined as follows: According to the data sources used to judge safety risks corresponding to the first historical safety risk information, determine the type of data source and the spatial location of the risk source; According to the spatial location of the first risk source and the type of data source, determine the Internet of Things devices arranged in the roadway where the risk source is located, and the output of the Internet of Things devices meets the configuration of the data sources used to judge safety risks; Based on the Internet of Things devices, determine the data update method.

[0034] In this embodiment, a method for determining the data update method is introduced. First, according to the data source used to judge the safety risk, the type of the data source and the spatial location of the risk source are determined. Secondly, according to the spatial location of the first risk source and the type of the data source, the Internet of Things devices in the roadway where the first risk source is located are determined. Finally, based on the Internet of Things devices, the data update method is determined.

[0035] Specifically, there are many types of Internet of Things devices applied to mine safety risk investigation, such as roadway inspection robots, substation inspection robots, inspection drones, high-definition cameras, dust concentration sensors, gas detection devices, fluorescent marking devices, etc. According to the differences of the Internet of Things devices, the data transmission and update methods will also be different. Some devices transmit data through wired cables, including transmission methods such as cables and optical fibers. Some devices perform regular data transmission through wireless communication, and some devices collect regular data through drone inspections, etc. Therefore, through the type of the data source and the spatial location of the data source, the Internet of Things devices in the roadway can be determined.

[0036] Specifically, the output of the Internet of Things device meets the configuration of the data source used to judge the safety risk. The Internet of Things devices in the roadway are not unique, and some Internet of Things devices whose output does not meet the conditions need to be excluded.

[0037] Specifically, the key to determining the data update method by this method lies in determining the Internet of Things device. By judging the type of the data source and the spatial location of the risk source used by the safety risk, and using it to match with the Internet of Things device, the Internet of Things device corresponding to the risk source can be more accurately located.

[0038] According to an embodiment of the present invention, the re-occurring safety risk information associated with the historical safety risk information is determined according to the association relationship of the risk factors. According to an embodiment of the present invention, the determination process of the re-occurring safety risk information includes: According to the association relationship of the risk factors corresponding to the first historical safety risk information, determine the second risk category associated with the risk category to which the first historical safety risk belongs; Obtain the historical safety risk information whose risk occurrence time is after the danger of the first historical safety risk information is eliminated and whose risk category includes the second risk category as the re-occurring safety risk information.

[0039] In this embodiment, the determination process of the re-occurring safety risk information is introduced. According to the association relationship of the risk factors corresponding to the first historical safety risk information, determine the second risk category associated with the risk category to which the risk event belongs. Then, take the risk event whose danger occurs after the risk event and whose risk category includes the second risk category as the re-occurring safety risk information.

[0040] Specifically, the reoccurring safety risk information is associated with historical safety risk information and is confirmed based on the association relationship of risk factors. The reoccurring safety risk information needs to meet two conditions. One is that its occurrence time needs to be after the elimination of the danger situation of the historical safety risk information, and the other is that its risk category includes the second risk category.

[0041] Specifically, the second risk category is determined according to the risk category of the first historical safety risk information and the association relationship of the risk factors corresponding to the first historical safety risk information.

[0042] Specifically, by determining the reoccurring safety risk information through the above method, targeted preventive measures can be formulated based on the determined reoccurring safety risk information, thereby reducing the likelihood and severity of risk occurrence. It is also possible to continuously monitor the reoccurring safety risk information, promptly discover changes in new risk factors or risk categories, and incorporate the data into the historical database to enrich the types of database safety risk information.

[0043] According to an embodiment of the present invention, the update method of the data is determined as follows: Determine the type of data source according to the type corresponding to the historical safety risk information; Determine the roadway where the risk source is located according to the risk source corresponding to the historical safety risk information; Select the Internet of Things device according to the output result of the Internet of Things device in the roadway where the risk source is located, and the output of the Internet of Things device covers the risk source; Determine the update method of the data based on the Internet of Things device.

[0044] In this embodiment, another method for determining the update method of the data is introduced. First, determine the type of data source according to the type corresponding to the historical safety information; second, determine the roadway where the risk source is located according to the risk source corresponding to the historical safety information; finally, select the Internet of Things device according to the output result of the Internet of Things device in the roadway where the risk source is located, and determine the update method of the data based on the Internet of Things device.

[0045] Specifically, in the method for determining the update method of the data in this embodiment, the roadway where the data source is located is determined through the historical safety risk information, and then the output result of the Internet of Things device in this roadway is matched with the type of the data source to determine the Internet of Things device corresponding to the historical safety risk information, and the update method of the data can be determined according to the Internet of Things device.

[0046] Specifically, in the case of hardware device updates or replacements, the updated hardware device cannot be determined directly through the original data type and the location of the device. Therefore, manual screening needs to be carried out first to obtain the data source type of the new hardware device and the information of the roadway where it is located before the update method of the data can be determined.

[0047] Specifically, when selecting Internet of Things devices, the output of the selected Internet of Things devices should also cover the risk sources.

[0048] Specifically, the method for determining the data update method in this embodiment is more universal. For the historical security risk information in the database, it is used to determine the type of data source and the location of the risk source, filter out the corresponding Internet of Things devices based on the location, and then use the data source type for matching, which can screen the Internet of Things devices more comprehensively and avoid omissions.

[0049] According to an embodiment of the present invention, the sampling window is determined in the following manner; Obtain the risk category to which the historical security risk information belongs, and determine the first time interval according to the average occurrence frequency of the security risk after the danger is eliminated under this risk category; Obtain the risk source corresponding to the historical security risk information, and determine the second time interval according to the time when the security risk first occurs after the danger is eliminated for this risk source; Take the smaller value of the first time interval and the second time interval as the sampling window.

[0050] According to an embodiment of the present invention, when calculating the second time interval, the risk level of the first-occurring security risk is not higher than the risk level of the first historical security risk information.

[0051] In this embodiment, the determination method of the sampling window is introduced. First, obtain the category to which the historical security risk information belongs, and determine the first time interval according to the average occurrence frequency of the security risk after the danger is eliminated for the risk of this category; then, obtain the risk source corresponding to the historical security risk information, and determine the second time interval according to the time when the security risk first occurs after the danger is eliminated for this risk source; finally, compare the magnitudes of the first interval time and the second interval time, and take the smaller value as the sampling window.

[0052] Specifically, the amount of data underground in the mine is huge, the screening work is difficult, and continuous screening consumes resources, and it is easier to miss the screening. Therefore, it is particularly important to reasonably set the sampling window for cost control.

[0053] Specifically, in most cases, the risk level is lower when the risk recurs at the same location after the serious risk is eliminated. If only considering not less than the first historical security risk information, omissions may occur. Therefore, it is necessary to compare with the first interval time determined by the average occurrence frequency of this type of risk.

[0054] In addition, by selecting the smaller value of the first time interval and the second time interval, it is also possible to ensure the integrity of a sampling period to the greatest extent, avoid being interrupted by various unexpected situations, and thus reduce the cost generated by sampling while ensuring the integrity of the data source. Specifically, the first time interval is determined by the average occurrence frequency of safety risks after the danger of a certain type of risk source is eliminated, and the second time interval is the time interval between the first occurrence of a safety risk after the danger of the risk source is eliminated and the previous time. By taking the minimum frequency of this type of risk source and the time interval between the last occurrence of the danger of this risk source, and taking the smaller value of the two, it is possible to minimize the effective time of the sampling window, so as to ensure as much as possible that no time point where a danger may occur is missed.

[0055] According to the second aspect of the present invention, an electronic device includes a processor and a memory; the memory is used to store a program; the processor executes the program to implement the coal mine safety risk analysis and judgment method described in the first aspect.

[0056] According to the third aspect of the present invention, a computer-readable storage medium stores a program, and the program is executed by a processor to implement the coal mine safety risk analysis and judgment method described in the first aspect.

[0057] The beneficial effects of the present invention are as follows: Through the above-mentioned coal mine safety risk analysis and judgment method, a more comprehensive investigation or a more refined method can be selected according to specific circumstances. Based on the analysis of various risk factors and the correlation relationships between risk factors, the safety risk hidden dangers in the mine can be effectively investigated, and the probability of re-occurrence of safety risks can be determined, thereby reducing the occurrence of safety accidents and the probability of re-occurrence of safety risks. The personal safety of the staff is protected, and the economic losses and hazards caused by accidents are avoided.

[0058] The above description is only a preferred embodiment of the present application and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) disclosed in the present application that have similar functions.

[0059] It should be understood that the magnitudes of the sequence numbers of the steps in the summary of the invention and the embodiments of the present invention do not absolutely imply the sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention. For purposes of illustration and description, the foregoing description of the implementation of the present disclosure has been given. The foregoing description is not exhaustive nor is it intended to limit the present disclosure to the exact form disclosed. Various variations and modifications may be possible in light of the above teachings, or various variations and modifications may be obtained from the practice of the present disclosure. These embodiments are selected and described to illustrate the principles of the present disclosure and its practical applications, so that those skilled in the art can utilize the present disclosure in various embodiments and various modifications suitable for the specific purposes contemplated. Those of ordinary skill in the art can understand that the above embodiments are specific examples for implementing the present disclosure, and in practical applications, various changes can be made in form and details without departing from the spirit and scope of the present disclosure.

Claims

1. A method for analyzing and judging coal mine safety risks, characterized in that, The method includes: Obtaining a first risk source corresponding to first historical safety risk information in a historical safety risk information database, and determining the danger situation state at the time of risk occurrence and the state after the danger situation is eliminated according to the risk record time corresponding to the first risk source; Determining the data update method according to the data collection method corresponding to the danger situation state; Using the data update method to determine the real-time state and historical state of the first risk source, where the historical state is generated based on the data update method and the generation event is later than the time point when the danger situation is eliminated, and the historical state is obtained by sampling the historical data of the first risk source, and the sampling window is determined according to the distribution information of the recurrence of safety risks; Determining whether the current safety risk level of the risk source deteriorates based on the real-time state and historical state of the first risk source.

2. The coal mine safety risk analysis and judgment method according to claim 1, characterized in that The historical safety risk information database is constructed as follows; Conducting a risk factor analysis on penalty cases to construct historical safety risk information; Marking the correlation relationship and risk category of risk factors formed during the accident evolution process of penalty cases, determining the level, risk source, danger situation state, danger situation elimination state of historical safety risk information, and the data source used to judge safety risks, and performing hot zone marking corresponding to the danger situation state and the state after the danger situation is eliminated, where the hot zone marking is used to prompt the risk rectification result or safety risk; Verifying the data source used to judge safety risks; Including the historical safety risk information into the database.

3. The coal mine safety risk analysis and judgment method according to claim 2, wherein The data update method is determined as follows: Determining the type of the data source and the spatial location of the risk source according to the data source used to judge safety risks corresponding to the first historical safety risk information; Determining the Internet of Things devices installed in the roadway where the risk source is located according to the spatial location of the first risk source and the type of the data source, and the output of the Internet of Things devices meets the configuration of the data source used to judge safety risks; Determining the data update method based on the Internet of Things devices.

4. The coal mine safety risk analysis and judgment method according to claim 2, wherein Determining the recurrence safety risk information associated with the historical safety risk information according to the correlation relationship of risk factors.

5. The coal mine safety risk analysis and judgment method according to claim 4, wherein The process of determining the recurrence safety risk information includes: Determining a second risk category associated with the risk category to which the first historical safety risk belongs according to the correlation relationship of risk factors corresponding to the first historical safety risk information; Obtaining historical safety risk information whose risk occurrence time is after the elimination of the danger situation of the first historical safety risk information and whose risk category includes the second risk category as the recurrence safety risk information.

6. The coal mine safety risk analysis and judgment method according to claim 1, wherein The data update method is determined as follows: Determining the type of the data source according to the type of the historical safety risk information; Determining the roadway where the risk source is located according to the risk source corresponding to the historical safety risk information; Selecting Internet of Things devices according to the output results of the Internet of Things devices in the roadway where the risk source is located, and the output of the Internet of Things devices covers the risk source; Determining the data update method based on the Internet of Things devices.

7. The coal mine safety risk analysis and judgment method according to claim 1, wherein The sampling window is determined as follows; Obtaining the risk category to which the historical safety risk information belongs, and determining a first time interval according to the average occurrence frequency of safety risks after the elimination of the danger situation under this risk category; Obtain the risk source corresponding to the historical safety risk information, and determine the second time interval according to the time when the safety risk first occurs after the danger is eliminated for this risk source; Take the smaller value of the first time interval and the second time interval as the sampling window.

8. The coal mine safety risk analysis and judgment method according to claim 7, characterized in that When calculating the second time interval, the risk level of the safety risk that first occurs is not higher than the risk level of the first historical safety risk information.

9. An electronic device, characterized in that, It includes a processor and a memory; the memory is used to store programs; the processor executes the programs to implement the coal mine safety risk analysis and judgment method according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The storage medium stores a program, and the program is executed by a processor to implement the coal mine safety risk analysis and judgment method according to any one of claims 1-8.

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