A method, system, device and storage medium for quantitative evaluation of coal mine disasters

Abstract

The present invention provides a method, system, device and storage medium for quantitative evaluation of coal mine disasters, which belongs to the field of mine safety technology, including creating a relationship between the mine observation area and different disaster types and their corresponding sensors, obtaining data collected by periodic sensors, calculating the score of each measuring point according to a preset scoring rule, and then calculating the sensor score according to the measuring point score; taking a day as a cycle, calculating the corresponding disaster score according to the sensor score, calculating the score of a certain area according to the disaster score and the preset regional weight, and finally calculating the overall score. The method realizes quantification and evaluation of different disasters in the mine area.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine safety, and in particular relates to a method, system, equipment and storage medium for quantitatively evaluating coal mine disasters. Background Art

[0002] Coal mine safety is the top priority in coal mine production activities. Underground coal mine disasters are mainly divided into: water hazard monitoring, fire monitoring, roof disaster monitoring, rock burst disaster monitoring and gas monitoring according to the disaster-causing factors. Each type of disaster requires a variety of sensors to obtain different environmental parameters. Each type of disaster will correspond to a variety of sensors to collect corresponding data, which will be connected to the opc ua bus through opc ua. If a signal is required, the data can be read through opc ua. Or for some sensors, the sensor service company reads the data into a text file and transmits it to the user through FTP files. It only achieves data collection and reading, and has no quantification capability. There is a lack of strategies for quantifying and evaluating different disasters in the mining area. At present, some mines also use quantitative indicator models to assist in disaster assessment, but usually it is necessary to establish targeted models for specific areas. The required data calculation and model training process are relatively complex and not universal. Summary of the invention

[0003] In order to solve the problem of quantitative evaluation of coal mine disaster monitoring data, the present invention provides a coal mine disaster quantitative evaluation method, system, device and storage medium.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] A method for quantitatively evaluating coal mine disasters comprises the following steps:

[0006] Obtain data collected periodically by sensors arranged at different measuring points in the observable area of ​​the mine;

[0007] The data periodically collected by the sensor is filtered using a filter, and the score corresponding to each measuring point data after filtering is output according to a threshold score table, and the minimum score is selected from the scores of the measuring points as the score of the sensor; the threshold score table represents the scores corresponding to different measuring point data;

[0008] With a daily cycle, weights are set for different sensors corresponding to each disaster type, and the score of the corresponding disaster type is calculated based on the sensor score and the corresponding weight; weights are set for different disaster types, and the corresponding regional scores are calculated based on the scores of the disaster types and their weights in the region, and the mine scores are obtained based on the scores of each region.

[0009] Preferably, the score of the sensor is calculated according to the score of the measuring point, specifically by the following formula:

[0010] sensorScore=min(P1, P2, P3...Pn);

[0011] Among them, sensorScore is the sensor score; P1, P2, P3...Pn are the measurement point scores.

[0012] Preferably, the score of the corresponding disaster type is calculated according to the sensor score and the corresponding weight, specifically through the following formula:

[0013]

[0014] Among them, disasterScore is the score of the disaster type, weight is the weight value, and k is the number of sensors.

[0015] Preferably, the method of calculating the corresponding regional total score according to the score of the disaster type and its weight in the region, and obtaining the mine score according to the score of each region, specifically includes the following steps:

[0016] The regional scores are calculated based on the scores of the disaster types and their corresponding weights, as follows:

[0017]

[0018] The mine score is calculated based on the regional scores and proportions, specifically using the following formula:

[0019]

[0020] Among them, areaScore is the area score and mineScore is the mine score.

[0021] The present invention provides a coal mine disaster quantitative evaluation system, which specifically includes:

[0022] The data acquisition module is used to acquire data periodically collected by sensors arranged at different measuring points within the observable area of ​​the mine.

[0023] The first scoring module is used to filter the data periodically collected by the sensor using a filter, output the score corresponding to each measuring point data after filtering according to a threshold score table, and select the minimum score from the scores of the measuring points as the score of the sensor; the threshold score table represents the scores corresponding to different measuring point data.

[0024] The second scoring module sets weights for different sensors corresponding to each disaster type on a daily basis, and calculates the score of the corresponding disaster type based on the sensor score and the corresponding weight; sets weights for different disaster types, and calculates the corresponding regional score based on the score of the disaster type and its weight in the region, and obtains the mine score based on the score of each region.

[0025] The present invention also provides a computer device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps described in the method for quantitatively evaluating coal mine disasters.

[0026] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is loaded by a processor, the steps described in the method for quantitatively evaluating coal mine disasters can be executed.

[0027] The coal mine disaster quantitative evaluation method provided by the present invention has the following beneficial effects:

[0028] The present invention obtains data collected by periodic sensors, calculates the score of the measuring point based on the data collected by the sensor, and then calculates the sensor score based on the score of the measuring point; with a day as a cycle, the corresponding disaster score is calculated based on the sensor score, and the score of a certain area is calculated based on the disaster score and the preset regional weight, and finally the overall score is calculated. The data collected by the mining area sensor is evaluated according to the set weights and scoring rules, forming a hierarchical relationship from area to disaster to specific sensor signals, and quantifying different coal mine disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 The present invention is a flowchart of a method for quantitatively evaluating coal mine disasters according to an embodiment of the present invention.

[0031] Figure 2 Schematic diagram of the hierarchical relationship of the mining disaster observation area in the embodiment of the present invention.

[0032] Figure 3 It is a schematic diagram of the 12345 working surface in an embodiment of the present invention.

[0033] Figure 4 It is a schematic diagram of the working face of the entire mining area in an embodiment of the present invention.

[0034] Figure 54 is a relationship diagram between database tables in an embodiment of the present invention.

[0035] Figure 6 The present invention is a data business flow diagram of a coal mine disaster quantitative evaluation method using the present invention. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0037] Example

[0038] The present invention provides a method for quantitatively evaluating coal mine disasters. Figure 1 As shown, the specific steps include:

[0039] S1. Divide the mine into multiple observable areas, each of which will have one or more disaster types, such as Figure 4 As shown in the figure. In the observable area, a disaster type is created and sensors are associated according to the disaster type. Each disaster type is associated with one or more sensors. The sensors correspond to the measuring points in the observable area, forming a hierarchical relationship from area to disaster to specific sensor signals. The area type can be a working face, tunnel, goaf, certain buildings, etc. Table 1, Table 2 and Table 3 are database tables. The relationship between the database tables is shown in the figure. Figure 5 shown.

[0040] Table 1 Observable Area (AreaInfo) Field Description

[0041]

[0042]

[0043] Table 2 Observable Area (AreaDisaster) field description

[0044]

[0045] Table 3 Definition of area disaster sensor (AreaDisasterSensor)

[0046]

[0047] Table 4 Observation point definition

[0048]

[0049]

[0050] According to the above table relationship, multiple observable areas are created. The observable areas are divided according to the importance of the mine; disaster types are created in the observable areas. There are currently six types of disaster types. One or more disaster types can be created in the observable area. And set weights for disaster types. The sum of the weights of all disaster types in an observable area must be 1. The specific weight value of each item depends on the actual situation and importance, and is determined by mine disaster analysis experts and modelers based on specific scenarios.

[0051] A sensor type is created for a certain disaster type in the observable area. One or more sensors can be associated with a disaster type and weights can be set. The sum of the weights of the sensor types in a disaster type is 1.

[0052] Create measurement points and enter measurement point data. Set the area where each measurement point is located and associate the corresponding sensor. Establish a threshold score table for each sensor signal.

[0053] The relationship between observable area-disaster type-sensor-measurement point is established, such as Figure 2 shown.

[0054] S2. Collect data and periodically scan the mine to obtain data collected periodically by sensors at different measuring points in the observable area of ​​the mine. Calculate the score of each measuring point according to the preset scoring rules of each signal, and then calculate the sensor score based on the score of the measuring point. The relationship between the sensor and the measuring point is not a one-to-one relationship. There are two ways to calculate: one is to take the minimum value among multiple scores; the other is to take the average value.

[0055] like Figure 3 As shown, a 12345 working face is set as an observable area. In this area, the present invention monitors the roof disaster type and the gas disaster type, and the roof disaster type monitors three sensor signals, namely the roof, anchor rod, and hydraulic support. The sum of the scores of the three sensor types is the score of the roof disaster. The weights are set to 0.2, 0.5, and 0.8 respectively. The sum of the weights needs to be equal to 1. The score multiplied by the weight is the actual score. The calculated roof disaster accounts for 0.4 of the weight in the entire working face score. Gas disasters are similar. Assuming the weight is 0.6, the final total score is the total score of the 12345 working face.

[0056] S3. Set weights for different sensors corresponding to each disaster type on a daily basis, and calculate the score of the corresponding disaster type based on the sensor score and the corresponding weight, using the following formula:

[0057]

[0058] Among them, disasterScore is the score of the disaster type, weight is the weight value, and k is the number of sensors.

[0059] Set weights for different disaster types, calculate the corresponding regional total score based on the score of the disaster type and its proportion in the region, and get the mine score based on the total score of each region. The specific formula is as follows:

[0060] The regional scores are calculated based on the scores of the disaster types and their corresponding weights, as follows:

[0061]

[0062] The mine score is calculated based on the regional score and proportion, using the following formula:

[0063]

[0064] Among them, areaScore is the area score and mineScore is the mine score.

[0065] The data service flow of the method for quantitatively evaluating coal mine disasters according to the present invention is as follows: Figure 6 As shown, the processing steps are as follows:

[0066] The sensors deployed in the mines collect data periodically; the periodically collected data streams are transmitted to the disaster warning data center through the API gateway; the disaster warning data center first filters the data stream through the data filter to reduce the server storage pressure and the pressure of data analysis; the filtered data flows into the alarm analysis module, and the alarm information is analyzed according to the preset rule library. If an alarm is generated, the alarm data is inserted into the database; the data is periodically scanned from the database, and the data is evaluated according to the quantitative evaluation rules, and the evaluation results are stored in the database; the data is read and displayed through the large screen to realize the visualization of the quantitative evaluation of coal mine disasters. The higher the score of the whole mine, the safer the mine.

[0067] The present invention also provides a coal mine disaster quantitative evaluation system, which specifically includes:

[0068] The data acquisition module is used to acquire data periodically collected by sensors arranged at different measuring points within the observable area of ​​the mine.

[0069] The first scoring module is used to filter the data periodically collected by the sensor using a filter, output the score corresponding to each measuring point data after filtering according to the threshold score table, and select the minimum score from the scores of the measuring points as the score of the sensor; the threshold score table represents the scores corresponding to different measuring point data.

[0070] The second scoring module sets weights for different sensors corresponding to each disaster type on a daily basis, and calculates the score of the corresponding disaster type based on the sensor score and the corresponding weight; sets weights for different disaster types, and calculates the corresponding regional score based on the score of the disaster type and its weight in the region, and obtains the mine score based on the score of each region.

[0071] Each module in the above-mentioned coal mine disaster quantitative evaluation system can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0072] The present invention also provides a computer device, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in an embodiment of a method for quantitatively evaluating coal mine disasters. The specific implementation method can be found in the method embodiment, which will not be described in detail here.

[0073] Furthermore, the present invention also provides a non-temporary computer-readable storage medium containing instructions, and a computer program is stored on the storage medium. For example, a memory containing instructions, the above instructions can be executed by a processor of a computer device to complete the above method. For example, a non-temporary computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device. When the computer program is executed by the processor, the steps in an embodiment of a method for quantitatively evaluating coal mine disasters can be implemented. The specific implementation method can be found in the method embodiment, which will not be repeated here.

[0074] It will be appreciated by those skilled in the art that embodiments of the present invention may provide methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0075] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0076] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0078] It should be pointed out that the specific implementation methods described above can enable those skilled in the art to understand the invention more comprehensively, but do not limit the invention in any way. Therefore, although the invention has been described in detail in this specification and embodiments, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belongs to the protection scope of the present invention.

Claims

1. A method for quantitatively evaluating coal mine disasters, characterized in that: The following steps are involved: Obtain data collected periodically by sensors arranged at different measuring points in the observable area of ​​the mine; The data collected periodically by the sensor is filtered using a filter, and the score corresponding to each measuring point data after filtering is output according to a threshold score table, and the minimum score is selected from the scores of the measuring points as the score of the sensor; the threshold score table represents the scores corresponding to different measuring point data; With a daily cycle, weights are set for different sensors corresponding to each disaster type, and the scores of the corresponding disaster types are calculated based on the sensor scores and corresponding weights; Weights are set for different disaster types, and corresponding regional scores are calculated based on the scores of the disaster types and their weights in the regions, and mine scores are obtained based on the scores of the various regions.

2. A method for quantitatively evaluating coal mine disasters according to claim 1, characterized in that: The sensor score is calculated based on the score of the measuring point, specifically through the following formula: sensorScore=min(P1, P2, P3...Pn); Among them, sensorScore is the sensor score; P1, P2, P3...Pn are the measurement point scores.

3. A method for quantitatively evaluating coal mine disasters according to claim 1, characterized in that: The score of the corresponding disaster type is calculated according to the sensor score and the corresponding weight, specifically through the following formula: Among them, disasterScore is the score of the disaster type, weight is the weight value, and k is the number of sensors.

4. A method for quantitatively evaluating coal mine disasters according to claim 1, characterized in that: The method of calculating the corresponding regional score according to the score of the disaster type and its weight in the region, and obtaining the mine score according to the score of each region specifically includes the following steps: The regional scores are calculated based on the scores of the disaster types and their corresponding weights, as follows: The mine score is calculated based on the regional scores and proportions, specifically using the following formula: Among them, areaScore is the area score and mineScore is the mine score.

5. A coal mine disaster quantitative evaluation system, characterized in that: include: A data acquisition module, used to acquire data periodically collected by sensors arranged at different measuring points in the observable area of ​​the mine; A first scoring module is used to filter the data periodically collected by the sensor using a filter, output the score corresponding to each measuring point data after filtering according to a threshold score table, and select the minimum score from the scores of the measuring points as the score of the sensor; the threshold score table represents the scores corresponding to different measuring point data; The second scoring module sets weights for different sensors corresponding to each disaster type on a daily basis, and calculates the score of the corresponding disaster type based on the sensor score and the corresponding weight; Weights are set for different disaster types, and corresponding regional scores are calculated based on the scores of the disaster types and their distribution in the area, and mine scores are obtained based on the scores of each area.

6. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is loaded into a processor, the computer program can execute the steps of the method according to any one of claims 1 to 4.

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