Coal mine safety early warning system and method based on edge computing

Abstract

The present invention discloses a coal mine safety early warning system and method based on edge computing, which relates to the field of coal mine safety early warning technology. The coal mine mining area is divided into a sub-working area and multiple sub-peripheral areas. The sub-working area is predicted to have an abnormality based on the comparison result of the working area abnormality score and the abnormality threshold. The sub-peripheral area is predicted to have an abnormality based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area abnormality prediction result and the sub-peripheral area abnormality prediction result, a corresponding management strategy is generated and sent to the coal mine management platform. The working area abnormality score and the peripheral area abnormality score are regularly analyzed through an evaluation model to determine whether the coal mine needs to be managed. The early warning system can perform multi-region and multi-source data fusion monitoring and early warning on coal mine mining, and regularly combine the monitoring results of multiple regions to evaluate whether the entire coal mine mining needs to be managed, greatly ensuring the safe mining of coal mines.

Description

Technical Field

[0001] The present invention relates to the field of coal mine safety early warning technology, and in particular to a coal mine safety early warning system and method based on edge computing. Background Art

[0002] The early warning system is established to improve the level of coal mine safety management and prevent mining accidents. As a high-risk industry, coal mines have many potential dangers such as gas explosions, landslides, and water disasters. Many serious mining accidents have occurred in history, causing significant casualties and property losses. Therefore, the establishment and improvement of the coal mine safety early warning system is particularly important.

[0003] The existing technology has the following deficiencies:

[0004] Existing early warning systems usually install a series of sensor equipment in the main working area of ​​a coal mine for monitoring and early warning. However, since coal mining will have a collateral impact on the surrounding areas (for example, the vibration generated during coal mining may cause the surrounding areas to collapse), if only the main working area is monitored and warned, when an abnormality occurs in the surrounding area, it will radiate to the main working area of ​​the coal mine (for example, the collapse of the surrounding area may cause the rock formation in the main working area to move and stress concentration, causing the main working area to collapse rapidly). At this time, even if the early warning system issues an early warning, it will cause the staff to be unable to move out of the mine in time, thereby failing to ensure the safe mining of the coal mine.

[0005] Based on this, the present invention proposes a coal mine safety early warning system and method based on edge computing, which can conduct multi-region and multi-source data fusion monitoring and early warning of coal mining, and regularly combine the monitoring results of multiple regions to evaluate whether the entire coal mining needs to be managed, greatly ensuring the safe mining of coal mines. Summary of the Invention

[0006] The purpose of the present invention is to provide a coal mine safety early warning system and method based on edge computing to address the shortcomings of the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a coal mine safety early warning method based on edge computing, the early warning method comprising the following steps:

[0008] The early warning system obtains coal mining area map information through the coal mine management platform, divides the coal mining area into a sub-working area and multiple sub-surrounding areas based on the map information, and generates a weight for each sub-surrounding area based on the distance between the multiple sub-surrounding areas and the sub-working area;

[0009] During the coal mining process, the real-time cumulative risk index and soil layer risk index of the sub-working area are obtained, and the work area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The sub-working area is predicted to have an anomaly based on the comparison result of the work area anomaly score and the anomaly threshold. The soil layer risk index of multiple sub-surrounding areas is obtained, and the sub-surrounding areas are predicted to have an anomaly based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction results and the sub-surrounding area anomaly prediction results, a corresponding management strategy is generated and sent to the coal mine management platform;

[0010] Regularly obtain the average working area anomaly score of the sub-working area and the average soil layer risk index of multiple sub-surrounding areas, and perform weighted calculation on the average soil layer risk index of multiple sub-surrounding areas to obtain the surrounding area anomaly score assignment. Analyze the average working area anomaly score and the surrounding area anomaly score assignment through the evaluation model to determine whether the coal mine needs to be managed, and send the judgment result to the coal mine management platform.

[0011] In a preferred embodiment, the coal mining area is divided into a sub-working area and a plurality of sub-surrounding areas based on map information, comprising the following steps:

[0012] Get the center position of the sub-work area and radius The first sub-surrounding area is a ring area that spreads outward from the sub-working area. The area around each child is The sub-peripheral area spreads outward to form a ring area, and the width of each sub-peripheral area is The same, for each sub-surrounding area, the boundaries are divided from the inside to the outside, and the inner radius of the i-th sub-surrounding area is , the outer radius is ,and .

[0013] In a preferred embodiment, generating a weight for each sub-peripheral area according to the distance between the plurality of sub-peripheral areas and the sub-working area includes the following steps:

[0014] Get the distance between each sub-surrounding area and the sub-working area. The expression is: , where is the distance between the boundary of the ith sub-surrounding area and the boundary of the sub-working area, represents the outer radius of the ith sub-surrounding area, represents the radius of the ith sub-surrounding area, and the weight of the ith sub-surrounding area is:

[0015]

[0016] Where, is the weight of the ith sub-surrounding area, represents the number of sub-surrounding areas, is the distance between the boundary of the ith sub-peripheral area and the boundary of the sub-working area.

[0017] In a preferred embodiment, during the coal mining process, obtaining the real-time cumulative risk index and soil layer risk index of the sub-working area includes the following steps:

[0018] The functional expression of the cumulative risk index is: , is the cumulative risk index, For time The gas concentration growth rate at time For time The coal dust concentration growth rate at the time, is the time range;

[0019] The logic for obtaining the soil layer risk index is as follows: the vibration amplitude and displacement of the soil layer in the sub-working area are obtained in real time through sensing equipment, the vibration amplitude and displacement are normalized, the value range of the vibration amplitude and displacement is mapped to [0, 1], the normalized value of the vibration amplitude and the normalized value of the displacement are obtained, and the soil layer risk index is obtained by summing the normalized values ​​of the vibration amplitude and the displacement.

[0020] In a preferred embodiment, a working area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index, and whether an anomaly will occur in a sub-working area is predicted based on the comparison result of the working area anomaly score and the anomaly threshold, including the following steps:

[0021] After the early warning system obtains the cumulative risk index and the soil layer risk index, it comprehensively calculates and obtains the abnormal score of the working area. The function expression is: , where Score the work area anomaly, is the cumulative risk index, is the soil risk index, 、 are the proportional coefficients of the cumulative risk index and the soil layer risk index, respectively, and 、 All greater than 0;

[0022] The obtained working area anomaly score is compared with the preset anomaly threshold. The anomaly threshold is used to predict whether anomalies will occur in the sub-working area during the coal mining process. If the working area anomaly score is less than or equal to the anomaly threshold, it is predicted that no anomalies will occur in the sub-working area during the coal mining process. If the working area anomaly score is greater than the anomaly threshold, it is predicted that anomalies will occur in the sub-working area during the coal mining process.

[0023] In a preferred embodiment, obtaining soil layer risk indexes of multiple sub-surrounding areas and predicting whether anomalies will occur in the sub-surrounding areas based on a comparison result of the soil layer risk indexes with an index threshold value include the following steps:

[0024] The soil layer risk index obtained for the sub-peripheral area is compared with the preset index threshold. The index threshold is used to predict whether anomalies will occur in the sub-peripheral area during the coal mining process. If the soil layer risk index is less than or equal to the index threshold, it is predicted that no anomalies will occur in the sub-peripheral area during the coal mining process. If the soil layer risk index is greater than the index threshold, it is predicted that anomalies will occur in the sub-peripheral area during the coal mining process.

[0025] In a preferred embodiment, the evaluation model is used to analyze the mean abnormality score of the working area and the abnormality score assignment of the surrounding area to determine whether the coal mine needs to be managed, including the following steps:

[0026] During multiple mining processes in a coal mine, if there are no abnormalities in the predictions for the sub-working area and the sub-surrounding area, the early warning system will obtain the abnormal scores of the working area multiple times at regular intervals to calculate the average abnormal score of the working area, and obtain the soil layer risk index of the sub-surrounding area multiple times to calculate the average soil layer risk index for each sub-surrounding area;

[0027] The soil layer risk index average of multiple sub-surrounding areas is weighted and calculated to obtain the surrounding area abnormality score assignment, which is expressed as:

[0028]

[0029] Where, Assign anomaly scores to the surrounding areas, is the weight of the ith sub-surrounding area, represents the number of sub-surrounding areas, represents the mean value of soil risk index of the ith sub-surrounding area;

[0030] The evaluation model is used to analyze the mean abnormality score of the working area and the abnormality score assignment of the surrounding area to determine whether the coal mine needs to be managed. The function expression of the evaluation model is:

[0031]

[0032] Where, For management value, is the mean abnormality score of the work area, Assign anomaly scores to the surrounding areas;

[0033] If the management value is greater than the management threshold, it is determined that the coal mine needs to be managed. If the management value is less than or equal to the management threshold, it is determined that the coal mine does not need to be managed.

[0034] In a preferred embodiment, the coal mine safety early warning system based on edge computing includes a regional division module, a regional anomaly prediction module, and a comprehensive evaluation module;

[0035] Area division module: obtains coal mining area map information through the coal mine management platform, divides the coal mining area into a sub-working area and multiple sub-surrounding areas based on the map information, and generates a weight for each sub-surrounding area based on the distance between the multiple sub-surrounding areas and the sub-working area;

[0036] Regional anomaly prediction module: During the coal mining process, the real-time cumulative risk index and soil layer risk index of the sub-working area are obtained, and the working area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The sub-working area is predicted to have an anomaly based on the comparison result of the working area anomaly score and the anomaly threshold. The soil layer risk index of multiple sub-surrounding areas is obtained, and the sub-surrounding areas are predicted to have an anomaly based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction results and the sub-surrounding area anomaly prediction results, the corresponding management strategy is generated and sent to the coal mine management platform;

[0037] Comprehensive evaluation module: Regularly obtain the average working area anomaly score of the sub-working area and the average soil layer risk index of multiple sub-surrounding areas, weightedly calculate the average soil layer risk index of multiple sub-surrounding areas to obtain the surrounding area anomaly score assignment, and use the evaluation model to analyze the average working area anomaly score and the surrounding area anomaly score assignment to determine whether the coal mine needs to be managed, and send the judgment result to the coal mine management platform.

[0038] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0039] 1. The present invention divides the coal mining area into a sub-working area and multiple sub-peripheral areas, obtains the real-time cumulative risk index and soil layer risk index of the sub-working area, and calculates the working area anomaly score based on the real-time cumulative risk index and soil layer risk index. It predicts whether the sub-working area will be abnormal based on the comparison result of the working area anomaly score and the anomaly threshold, and predicts whether the sub-peripheral area will be abnormal based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction result and the sub-peripheral area anomaly prediction result, a corresponding management strategy is generated and sent to the coal mine management platform. The working area anomaly score and the peripheral area anomaly score are regularly analyzed through the evaluation model to determine whether the coal mine needs to be managed. The early warning system can perform multi-region and multi-source data fusion monitoring and early warning on coal mining, and regularly combines the monitoring results of multiple regions to evaluate whether the entire coal mining needs to be managed, which greatly ensures the safe mining of coal mines;

[0040] 2. During multiple mining operations at a coal mine, if no abnormalities are predicted for the sub-working area and the sub-surrounding area, the early warning system obtains multiple abnormality scores for the working area at regular intervals to calculate the average abnormality score for the working area, obtains multiple soil layer risk indexes for the sub-surrounding areas to calculate the average soil layer risk index for each sub-surrounding area, and weights the average soil layer risk indexes of the multiple sub-surrounding areas to obtain an abnormality score for the surrounding area. The evaluation model analyzes the average abnormality score for the working area and the abnormality score for the surrounding area to determine whether the coal mine needs to be managed. The early warning system can regularly determine whether the coal mine needs to be managed in advance based on the conditions of the sub-working area and the sub-surrounding area, thereby enabling safety assessments to be conducted before coal mining, further improving the safety early warning effect of coal mining. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0042] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0044] Example 1: Please refer to Figure 1 As shown, the coal mine safety early warning method based on edge computing described in this embodiment includes the following steps:

[0045] The early warning system obtains the map information of the coal mining area through the coal mine management platform, divides the coal mining area into a sub-working area and multiple sub-peripheral areas based on the map information, and generates the weight of each sub-peripheral area according to the distance between the multiple sub-peripheral areas and the sub-working area. The closer the sub-peripheral area is to the sub-working area, the greater the weight of the sub-peripheral area. During the coal mining process, the real-time cumulative risk index and soil layer risk index of the sub-working area are obtained, and the abnormal score of the working area is calculated based on the real-time cumulative risk index and the soil layer risk index. The comparison result of the abnormal score of the working area and the abnormal threshold is used to predict whether the sub-working area will be abnormal. Multiple sub-peripheral areas are obtained. The soil layer risk index of the surrounding area is used to predict whether anomalies will occur in the sub-surrounding area based on the comparison results of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction results and the sub-surrounding area anomaly prediction results, the corresponding management strategy is generated and sent to the coal mine management platform. The average working area anomaly score of the sub-working area and the average soil layer risk index of multiple sub-surrounding areas are obtained regularly. The average soil layer risk index of multiple sub-surrounding areas is weighted and calculated to obtain the surrounding area anomaly score assignment. The evaluation model is used to analyze the average working area anomaly score and the surrounding area anomaly score assignment to determine whether the coal mine needs to be managed, and the judgment result is sent to the coal mine management platform.

[0046] This application divides the coal mining area into a sub-working area and multiple sub-peripheral areas, obtains the real-time cumulative risk index and soil layer risk index of the sub-working area, and calculates the working area anomaly score based on the real-time cumulative risk index and soil layer risk index. It predicts whether the sub-working area will be abnormal based on the comparison result of the working area anomaly score and the anomaly threshold, and predicts whether the sub-peripheral area will be abnormal based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction result and the sub-peripheral area anomaly prediction result, a corresponding management strategy is generated and sent to the coal mine management platform. The working area anomaly score and the surrounding area anomaly score are regularly analyzed through the evaluation model to determine whether the coal mine needs to be managed. This early warning system can perform multi-region and multi-source data fusion monitoring and early warning on coal mining, and regularly combine the monitoring results of multiple regions to evaluate whether the entire coal mining needs to be managed, which greatly ensures the safe mining of coal mines.

[0047] Example 2: The early warning system obtains coal mining area map information through the coal mine management platform, and divides the coal mining area into a sub-working area and multiple sub-surrounding areas based on the map information, including the following steps:

[0048] Get the center position of the sub-work area , the center position Usually the center point of the mine or the center point of the mining area, get the radius of the sub-working area ,radius It is set according to the actual scope and mining conditions of the mine, and is not limited here. The first sub-peripheral area is a ring area that spreads outward from the sub-working area. The second sub-peripheral area is a ring area that spreads outward from the first sub-peripheral area. Several sub-peripheral areas are obtained by analogy. The width of each sub-peripheral area is ​​ The same, for each sub-surrounding area, the boundaries are divided from the inside to the outside, and the inner radius of the i-th sub-surrounding area is , the outer radius is ,in, , for the first sub-surrounding area boundary is .

[0049] Generating a weight for each sub-peripheral area according to the distances between the plurality of sub-peripheral areas and the sub-working area, wherein the closer the sub-peripheral area is to the sub-working area, the greater the weight of the sub-peripheral area, includes the following steps:

[0050] Get the distance between each sub-surrounding area and the sub-working area. The expression is: , where is the distance between the boundary of the ith sub-surrounding area and the boundary of the sub-working area, represents the outer radius of the ith sub-surrounding area, represents the radius of the ith sub-surrounding area, and the weight of the ith sub-surrounding area is:

[0051]

[0052] Where, is the weight of the ith sub-surrounding area, represents the number of sub-surrounding areas, is the distance between the boundary of the ith sub-peripheral area and the boundary of the sub-working area.

[0053] Assume that the radius of the sub-working area is 100m, the width of the sub-peripheral area is 50m, and there are three sub-peripheral areas:

[0054] First sub-surrounding area: inner radius , outer radius ;

[0055] Second sub-surrounding area: inner radius , outer radius ;

[0056] The third sub-surrounding area: inner radius , outer radius ;

[0057] The distance between the first sub-peripheral area boundary and the sub-working area boundary is 125m, the distance between the second sub-peripheral area boundary and the sub-working area boundary is 175m, and the distance between the third sub-peripheral area boundary and the sub-working area boundary is 225m. Then:

[0058]

[0059]

[0060]

[0061] Where, 、 、 are the weights of the first sub-surrounding area, the second sub-surrounding area, and the third sub-surrounding area, respectively. is the distance between the first sub-peripheral area boundary and the sub-working area boundary, is the distance between the second sub-peripheral area boundary and the sub-working area boundary, is the distance between the boundary of the third sub-peripheral area and the boundary of the sub-working area.

[0062] During coal mining, obtaining the real-time cumulative risk index and soil layer risk index of the sub-working area includes the following steps:

[0063] The functional expression of the cumulative risk index is: , is the cumulative risk index, For time The gas concentration growth rate at time For time The coal dust concentration growth rate at the time, For the time range, when the cumulative risk index is larger, the safety risks in coal mining are manifested in the following impacts:

[0064] Increased safety hazards: An increase in the cumulative risk value means that the gas concentration and coal dust concentration are high over a period of time, or frequently exceed the standard. This may be caused by factors such as gas accumulation inside the mine and poor ventilation, posing a major safety hazard.

[0065] Increased risk of explosions and fires: High gas and coal dust concentrations are among the main factors contributing to explosions and fires in coal mines. Increased cumulative risk values ​​could lead to increased exposure to these hazards, increasing the likelihood of explosions and fires in mines.

[0066] Increased pressure on production safety: Coal mine management departments and staff need to increase safety monitoring efforts, strengthen production safety management, and adopt stricter safety measures to reduce the occurrence of accidents and protect the lives and property of workers.

[0067] Production restrictions or shutdowns: To reduce safety risks, coal mining activities may need to be reduced or stopped, which will affect production plans and the economic performance of the mine.

[0068] Increased environmental pollution: High coal dust concentrations may lead to increased pollution in the environment surrounding coal mines, affecting the environment and people's health in the surrounding areas.

[0069] The logic for obtaining the soil layer risk index is as follows: the vibration amplitude and displacement of the soil layer in the sub-working area are obtained in real time through sensing equipment, the vibration amplitude and displacement are normalized, the range of the vibration amplitude and displacement is mapped to the range [0, 1], the normalized vibration amplitude value and the normalized displacement value are obtained, and the normalized vibration amplitude value and the normalized displacement value are summed to obtain the soil layer risk index. The normalization of the vibration amplitude and displacement value belongs to the existing technology and will not be detailed here.

[0070] The calculation expressions of vibration amplitude and displacement are:

[0071]

[0072] Where, is the vibration amplitude, is the initial value of the vibration amplitude, is the angular frequency, For time, is the initial phase, is the displacement, is the initial displacement of the soil monitoring point, is the initial velocity of the soil layer monitoring point, is the acceleration of the soil layer monitoring point;

[0073] The larger the soil risk index, the greater the soil vibration amplitude or displacement in the coal mining area, which may indicate that there are safety risks in coal mining. The specific impacts include:

[0074] Increased risk of geological disasters: Increased soil vibration amplitude and displacement may lead to increased risk of geological disasters such as subsidence, landslides, and collapses, posing a threat to the safety of areas surrounding the mine.

[0075] Damage to mining facilities: Soil vibration may cause damage or rupture of mining facilities (such as tunnels, pillars, etc.), increase safety hazards inside the mine, and even lead to accidents.

[0076] Equipment damage: Soil vibration can affect equipment in the mine, exacerbating equipment wear and damage, reducing equipment life, and increasing maintenance costs.

[0077] Workers' safety is threatened: Soil vibration poses a direct threat to workers' safety and may lead to serious consequences such as collapse, casualties, etc.

[0078] Increased environmental pollution: Soil vibration may cause soil loosening, resulting in the release of environmental pollutants such as coal dust and wastewater into the surrounding environment, affecting the surrounding ecological environment and people's lives.

[0079] The work area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The comparison between the work area anomaly score and the anomaly threshold is used to predict whether anomalies will occur in the sub-work area. The following steps are included:

[0080] After the early warning system obtains the cumulative risk index and the soil layer risk index, it comprehensively calculates and obtains the abnormal score of the working area. The function expression is: , where Score the work area anomaly, is the cumulative risk index, is the soil risk index, 、 are the proportional coefficients of the cumulative risk index and the soil layer risk index, respectively, and 、 All greater than 0;

[0081] The larger the working area anomaly score, the more likely it is that an anomaly will occur in the sub-working area. The obtained working area anomaly score is compared with the preset anomaly threshold. The anomaly threshold is used to predict whether an anomaly will occur in the sub-working area during the coal mining process. If the working area anomaly score is less than or equal to the anomaly threshold, it is predicted that no anomaly will occur in the sub-working area during the coal mining process. If the working area anomaly score is greater than the anomaly threshold, it is predicted that an anomaly will occur in the sub-working area during the coal mining process.

[0082] Obtain soil layer risk indexes for multiple sub-surrounding areas, and predict whether anomalies will occur in the sub-surrounding areas based on the comparison results of the soil layer risk indexes and the index thresholds, including the following steps:

[0083] The logic for obtaining the soil layer risk index is as follows: the vibration amplitude and displacement of the soil layer in the sub-surrounding area are obtained in real time through sensing equipment, the vibration amplitude and displacement are normalized, the range of the vibration amplitude and displacement is mapped to the range [0, 1], the normalized vibration amplitude value and the normalized displacement value are obtained, and the normalized vibration amplitude value and the normalized displacement value are summed to obtain the soil layer risk index. The normalization of the vibration amplitude and displacement value belongs to the existing technology and will not be elaborated here.

[0084] The larger the soil layer risk index, the more likely it is that an anomaly will occur in the sub-surrounding area. The soil layer risk index obtained for the sub-surrounding area is compared with the preset index threshold. The index threshold is used to predict whether an anomaly will occur in the sub-surrounding area during the coal mining process. If the soil layer risk index is less than or equal to the index threshold, it is predicted that no anomaly will occur in the sub-surrounding area during the coal mining process. If the soil layer risk index is greater than the index threshold, it is predicted that an anomaly will occur in the sub-surrounding area during the coal mining process.

[0085] Based on the abnormal prediction results of the sub-working area and the abnormal prediction results of the sub-surrounding area, a corresponding management strategy is generated and sent to the coal mine management platform, including the following steps:

[0086] When it is predicted that there will be no abnormality in the sub-working area or sub-surrounding area during coal mining, the early warning system does not generate a management strategy. When it is predicted that there will be abnormality in the sub-working area or sub-surrounding area during coal mining, the early warning system generates a management strategy, and when it is predicted that there will be abnormality in the sub-working area during coal mining, it generates a management strategy that requires emergency management. When it is predicted that there will be abnormality in the sub-surrounding area during coal mining, it generates a management strategy that requires management.

[0087] Regularly obtain the average work area anomaly score of the sub-work area and the average soil layer risk index of multiple sub-surrounding areas, and perform weighted calculation on the average soil layer risk index of multiple sub-surrounding areas to obtain the surrounding area anomaly score assignment. Use the evaluation model to analyze the average work area anomaly score and the surrounding area anomaly score assignment to determine whether the coal mine needs to be managed. The judgment result is sent to the coal mine management platform, including the following steps:

[0088] During multiple mining processes in a coal mine, if there are no abnormalities in the predictions for the sub-working area and the sub-surrounding area, the early warning system will obtain the abnormal scores of the working area multiple times at regular intervals to calculate the average abnormal score of the working area, and obtain the soil layer risk index of the sub-surrounding area multiple times to calculate the average soil layer risk index for each sub-surrounding area;

[0089] The soil layer risk index average of multiple sub-surrounding areas is weighted and calculated to obtain the surrounding area abnormality score assignment, which is expressed as:

[0090]

[0091] Where, Assign anomaly scores to the surrounding areas, is the weight of the ith sub-surrounding area, represents the number of sub-surrounding areas, represents the mean value of soil risk index of the ith sub-surrounding area;

[0092] The evaluation model is used to analyze the mean abnormality score of the working area and the abnormality score assignment of the surrounding area to determine whether the coal mine needs to be managed. The function expression of the evaluation model is:

[0093]

[0094] Where, For management value, is the mean abnormality score of the work area, Assign anomaly scores to the surrounding areas;

[0095] If the management value is greater than the management threshold, it is determined that the coal mine needs to be managed; if the management value is less than or equal to the management threshold, it is determined that the coal mine does not need to be managed;

[0096] In the process of multiple mining in a coal mine, if the predictions for the sub-working area and the sub-surrounding area are all normal, the early warning system obtains the abnormal scores of the working area multiple times at intervals to calculate the average abnormal score of the working area, obtains the soil layer risk index of the sub-surrounding area multiple times to calculate the average soil layer risk index for each sub-surrounding area, and weights the average soil layer risk index of multiple sub-surrounding areas to obtain the abnormal score assignment of the surrounding area. The evaluation model analyzes the average abnormal score of the working area and the abnormal score assignment of the surrounding area to determine whether the coal mine needs to be managed. The early warning system can regularly combine the conditions of the sub-working area and the sub-surrounding area to determine whether the coal mine needs to be managed in advance, so that a safety assessment can be performed before the coal mine is mined, further improving the safety early warning effect of coal mine mining.

[0097] Example 3: The coal mine safety early warning system based on edge computing described in this embodiment includes a regional division module, a regional anomaly prediction module, and a comprehensive assessment module;

[0098] Regional division module: obtains coal mining area map information through the coal mine management platform, divides the coal mining area into a sub-working area and multiple sub-peripheral areas based on the map information, and generates a weight for each sub-peripheral area based on the distance between the multiple sub-peripheral areas and the sub-working area. The closer the sub-peripheral area is to the sub-working area, the greater the weight of the sub-peripheral area. The division results of the sub-working area and multiple sub-peripheral areas are sent to the regional anomaly prediction module, and the weight of each sub-peripheral area is sent to the comprehensive evaluation module;

[0099] Regional anomaly prediction module: During the coal mining process, the real-time cumulative risk index and soil layer risk index of the sub-working area are obtained, and the working area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The sub-working area is predicted to have an anomaly based on the comparison result between the working area anomaly score and the anomaly threshold. The soil layer risk index of multiple sub-surrounding areas is obtained, and the sub-surrounding areas are predicted to have an anomaly based on the comparison result between the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction results and the sub-surrounding area anomaly prediction results, a corresponding management strategy is generated and sent to the coal mine management platform. The working area anomaly score and the soil layer risk index are sent to the comprehensive evaluation module;

[0100] Comprehensive evaluation module: Regularly obtain the average working area anomaly score of the sub-working area and the average soil layer risk index of multiple sub-surrounding areas, weightedly calculate the average soil layer risk index of multiple sub-surrounding areas to obtain the surrounding area anomaly score assignment, and use the evaluation model to analyze the average working area anomaly score and the surrounding area anomaly score assignment to determine whether the coal mine needs to be managed, and send the judgment result to the coal mine management platform.

[0101] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0102] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0103] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0104] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0105] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A coal mine safety early warning method based on edge computing, characterized by: The early warning method comprises the following steps: The early warning system obtains the map information of the coal mining area through the coal mine management platform, and divides the coal mining area into a sub-working area and multiple sub-peripheral areas based on the map information. The center position and radius of the sub-working area are obtained. The first sub-peripheral area is a ring area that spreads outward from the sub-working area, and the i-th sub-peripheral area is a ring area that spreads outward from the i-1 sub-peripheral area. For each sub-peripheral area, the boundaries are divided and set from the inside to the outside. The inner radius of the i-th sub-peripheral area is r i-1 , the outer radius is r i , generating a weight for each sub-peripheral area according to the distances between the multiple sub-peripheral areas and the sub-working area; During the coal mining process, the real-time cumulative risk index and soil layer risk index of the sub-working area are obtained, and the work area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The sub-working area is predicted to have an anomaly based on the comparison result of the work area anomaly score and the anomaly threshold. The soil layer risk index of multiple sub-surrounding areas is obtained, and the sub-surrounding areas are predicted to have an anomaly based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction results and the sub-surrounding area anomaly prediction results, a corresponding management strategy is generated and sent to the coal mine management platform; Regularly obtain the average working area anomaly score of the sub-working area and the average soil layer risk index of multiple sub-surrounding areas, and perform weighted calculation on the average soil layer risk index of multiple sub-surrounding areas to obtain the surrounding area anomaly score assignment. Analyze the average working area anomaly score and the surrounding area anomaly score assignment through the evaluation model to determine whether the coal mine needs to be managed, and send the judgment result to the coal mine management platform.

2. The coal mine safety early warning method based on edge computing according to claim 1 is characterized in that: The width Δr of each sub-peripheral area is the same, and the inner radius of the i-th sub-peripheral area is r i-1 , the outer radius is r i , and r i =r i-1 +Δr.

3. The coal mine safety early warning method based on edge computing according to claim 2 is characterized in that: Generating a weight for each sub-surrounding area according to the distances between the plurality of sub-surrounding areas and the sub-working area includes the following steps: Get the distance between each sub-surrounding area and the sub-working area. The expression is: Where, d i is the distance between the boundary of the ith sub-surrounding area and the boundary of the sub-working area, r i Represents the outer radius of the ith sub-surrounding area, r i-1 represents the radius of the ith sub-surrounding area, and the weight of the ith sub-surrounding area is: Where, ω i is the weight of the ith sub-peripheral area, n represents the number of sub-peripheral areas, and n is the distance between the boundary of the ith sub-peripheral area and the boundary of the sub-working area.

4. The coal mine safety early warning method based on edge computing according to claim 3 is characterized by: During coal mining, obtaining the real-time cumulative risk index and soil layer risk index of the sub-working area includes the following steps: The functional expression of real-time cumulative risk index is: fx accumulate is the real-time cumulative risk index, C g (t) is the function of gas concentration changing with time t, C d (t) is the function of coal dust concentration changing with time t, and [0, T] is the time range; The logic for obtaining the soil layer risk index is as follows: the vibration amplitude and displacement of the soil layer in the sub-working area are obtained in real time through sensing equipment, the vibration amplitude and displacement are normalized, the value range of the vibration amplitude and displacement is mapped to [0, 1], the normalized value of the vibration amplitude and the normalized value of the displacement are obtained, and the soil layer risk index is obtained by summing the normalized values ​​of the vibration amplitude and the displacement.

5. The coal mine safety early warning method based on edge computing according to claim 4 is characterized in that: The work area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The comparison between the work area anomaly score and the anomaly threshold is used to predict whether anomalies will occur in the sub-work area. The following steps are included: After the early warning system obtains the real-time cumulative risk index and soil layer risk index, it calculates the abnormal score of the working area comprehensively. The function expression is: Al rating =α·fx accumulate +β·fx Soil_layer , where Al rating Score the work area anomaly, fx accumulate is the real-time cumulative risk index, fx Soil_layer is the soil layer risk index, α and β are the proportional coefficients of the real-time cumulative risk index and the soil layer risk index, respectively, and both α and β are greater than 0; The obtained working area anomaly score is compared with the preset anomaly threshold. The anomaly threshold is used to predict whether anomalies will occur in the sub-working area during the coal mining process. If the working area anomaly score is less than or equal to the anomaly threshold, it is predicted that no anomalies will occur in the sub-working area during the coal mining process. If the working area anomaly score is greater than the anomaly threshold, it is predicted that anomalies will occur in the sub-working area during the coal mining process.

6. The coal mine safety early warning method based on edge computing according to claim 5 is characterized in that: Obtain soil layer risk indexes for multiple sub-surrounding areas, and predict whether anomalies will occur in the sub-surrounding areas based on the comparison results of the soil layer risk indexes and the index thresholds, including the following steps: The soil layer risk index obtained for the sub-peripheral area is compared with the preset index threshold. The index threshold is used to predict whether anomalies will occur in the sub-peripheral area during the coal mining process. If the soil layer risk index is less than or equal to the index threshold, it is predicted that no anomalies will occur in the sub-peripheral area during the coal mining process. If the soil layer risk index is greater than the index threshold, it is predicted that anomalies will occur in the sub-peripheral area during the coal mining process.

7. The coal mine safety early warning method based on edge computing according to claim 6 is characterized in that: The evaluation model analyzes the mean abnormality score of the working area and the abnormality score assignment of the surrounding area to determine whether the coal mine needs to be managed, including the following steps: During multiple mining processes in a coal mine, if there are no abnormalities in the predictions for the sub-working area and the sub-surrounding area, the early warning system will obtain the abnormal scores of the working area multiple times at regular intervals to calculate the average abnormal score of the working area, and obtain the soil layer risk index of the sub-surrounding area multiple times to calculate the average soil layer risk index for each sub-surrounding area; The average of the soil layer risk indexes of multiple sub-surrounding areas is weighted to obtain the surrounding area abnormality score assignment, and the expression is: Where, Assign an abnormal score to the surrounding area, ω i is the weight of the ith sub-surrounding area, n represents the number of sub-surrounding areas, represents the mean value of soil risk index of the ith sub-surrounding area; The evaluation model is used to analyze the mean abnormality score of the working area and the abnormality score assignment of the surrounding area to determine whether the coal mine needs to be managed. The function expression of the evaluation model is: Where, GL value For management value, is the mean abnormality score of the work area, Assign anomaly scores to the surrounding areas; If the management value is greater than the management threshold, it is determined that the coal mine needs to be managed. If the management value is less than or equal to the management threshold, it is determined that the coal mine does not need to be managed.

8. A coal mine safety early warning system based on edge computing, used to implement the early warning method according to any one of claims 1 to 7, characterized in that: Including regional division module, regional anomaly prediction module, and comprehensive evaluation module; Area division module: obtains coal mining area map information through the coal mine management platform, divides the coal mining area into a sub-working area and multiple sub-surrounding areas based on the map information, and generates a weight for each sub-surrounding area based on the distance between the multiple sub-surrounding areas and the sub-working area; Regional anomaly prediction module: During the coal mining process, the real-time cumulative risk index and soil layer risk index of the sub-working area are obtained, and the working area anomaly score is calculated based on the real-time cumulative risk index and the soil layer risk index. The sub-working area is predicted to have an anomaly based on the comparison result of the working area anomaly score and the anomaly threshold. The soil layer risk index of multiple sub-surrounding areas is obtained, and the sub-surrounding areas are predicted to have an anomaly based on the comparison result of the soil layer risk index and the index threshold. Based on the sub-working area anomaly prediction results and the sub-surrounding area anomaly prediction results, the corresponding management strategy is generated and sent to the coal mine management platform; Comprehensive evaluation module: Regularly obtain the average working area anomaly score of the sub-working area and the average soil layer risk index of multiple sub-surrounding areas, weightedly calculate the average soil layer risk index of multiple sub-surrounding areas to obtain the surrounding area anomaly score assignment, and use the evaluation model to analyze the average working area anomaly score and the surrounding area anomaly score assignment to determine whether the coal mine needs to be managed, and send the judgment result to the coal mine management platform.

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