Coal mine tunnel surrounding rock catastrophe monitoring system and method

Abstract

The invention belongs to the field of coal mine catastrophe monitoring, relates to a data analysis technology, is used for solving the problem that in the prior art, a monitoring means and a protection means of a coal mine tunnel cannot be matched and analyzed by combining historical monitoring data, and particularly relates to a coal mine tunnel surrounding rock catastrophe monitoring system and method. The catastrophe monitoring platform is in communication connection with a historical data statistics module, a historical data processing module, a catastrophe monitoring analysis module and a database; according to the method, the surrounding rock catastrophe historical monitoring data of the coal mine tunnel can be processed, the depth interval is formed after the mining depth value is processed, and then the matching objects of the depth interval are classified according to the monitoring means and the protection means; and finally, according to the monitoring effective value and the catastrophe state, a monitoring matching means and a protection matching means are marked, so that coal mine tunnels with different mining depths can be quickly matched with proper monitoring means and protection means, and the coal mining safety is ensured.

Description

Technical Field

[0001] The invention belongs to the field of coal mine disaster monitoring, relates to data analysis technology, and specifically is a coal mine tunnel surrounding rock disaster monitoring system and method. Background Art

[0002] The stability of the surrounding rock of underground tunnels during tunnel excavation directly determines the efficiency and safety of underground tunnel excavation. With the continuous increase in the depth of coal mine comprehensive mining operations, the problems of mine pressure fluctuation and stress concentration faced during deep tunnel excavation operations are prominent, especially in areas with low surrounding rock strength and obvious crushing. The surrounding rock is severely deformed, which poses a serious hidden danger to the safety of underground comprehensive mining operations.

[0003] The invention patent with announcement number CN116502386B discloses a simulation method and system for the catastrophic evolution of tunnel anchored surrounding rock under static and dynamic loads. The method simulates the pressure of the support structure during actual coal mining by constructing a particle flow numerical model of the tunnel surrounding rock under point loads, and uses the method of applying boundary velocity to the model to constrain the internal particle flow velocity, so that the simulation results are more realistic, providing a new idea for preventing surrounding rock disasters from occurring on site in the tunnel during coal mining. However, the method cannot match the monitoring means and protection means of the coal mine tunnel with historical monitoring data, resulting in the inability to use the most optimized monitoring means and protection means to avoid disasters in the coal mine tunnel, and the safety of coal mining is low.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a coal mine tunnel surrounding rock disaster monitoring system and method, which is used to solve the problem that the existing technology cannot match and analyze the monitoring means and protection means of the coal mine tunnel in combination with historical monitoring data;

[0006] The technical problem to be solved by the present invention is: how to provide a coal mine tunnel surrounding rock disaster monitoring system and method that can match and analyze the monitoring means and protection means of the coal mine tunnel in combination with historical monitoring data.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A coal mine tunnel surrounding rock disaster monitoring system, comprising a disaster monitoring platform, wherein the disaster monitoring platform is communicatively connected to a historical data statistics module, a historical data processing module, a disaster monitoring analysis module and a database;

[0009] The historical data statistics module is used to statistically analyze the historical monitoring data of the surrounding rock disasters in coal mine roadways: mark the roadways that have completed coal mining as statistical objects, and the historical monitoring data of the statistical objects include: mining depth value, monitoring means, protection means, monitoring effectiveness value, and disaster state;

[0010] The historical data processing module is used to process the historical monitoring data of the surrounding rock disasters in coal mine roadways: form a depth range from the maximum and minimum values of the mining depth values of all statistical objects, divide the depth range into several depth intervals, mark the statistical objects with mining depth values within the depth intervals as matching objects of the depth intervals, classify the matching objects according to the monitoring means and protection means adopted, and mark the monitoring matching means and protection matching means of the depth intervals;

[0011] The disaster monitoring and analysis module is used to conduct disaster monitoring and analysis on coal mine roadways: mark the coal mine roadways for which disaster monitoring and analysis are to be carried out as analysis objects, obtain the mining depth values of the analysis objects, and retrieve the monitoring matching means and protection matching means corresponding to the depth intervals of the mining depth values and mark them as the monitoring implementation means and protection implementation means of the analysis objects.

[0012] Furthermore, the monitoring means include convergence meter measurement, multi-point displacement meter measurement, acoustic wave monitoring equipment, and vibration meter measurement, and the protection means include support protection, reinforcement protection, stress control protection, and shotcrete protection; the monitoring effectiveness value is the ratio of the number of effective alarm signals to the number of ineffective alarm signals when the statistical object uses the monitoring means to monitor the disaster risk; the disaster state includes disaster occurrence and disaster avoidance. Disaster occurrence means that a disaster accident has occurred in the statistical object during the entire coal mining process, and disaster avoidance means that no disaster accident has occurred in the statistical object during the entire coal mining process.

[0013] Furthermore, the specific process of marking the monitoring matching means and protection matching means of the depth intervals includes: mark the matching objects using the same monitoring means as monitoring division objects, sum and average the monitoring effectiveness values of all monitoring division objects to obtain the priority data of the monitoring means, and mark the monitoring means with the largest priority data as the monitoring matching means of the depth interval; mark the matching objects using the same protection means as protection division objects, mark the ratio of the number of protection division objects with the disaster state of disaster avoidance to the total number of protection division objects as protection data, and mark the protection means with the largest protection data as the protection matching means of the depth interval.

[0014] Further, the specific process of monitoring and analyzing the disaster changes in coal mine roadways includes: arranging the matching objects that adopt the protection matching means and the monitoring matching means within the depth range in descending order of the monitoring effective value to obtain a reference sequence, marking the matching object ranked first in the reference sequence as the layout reference object, comparing the layout reference object with the analysis object to obtain a reference coefficient CK, and extracting the reference data of the layout reference object through the reference coefficient CK.

[0015] Further, the specific process of extracting the reference data of the layout reference object includes: obtaining a reference threshold CKmax through the database, and comparing the reference coefficient CK with the reference threshold CKmax: if the reference coefficient CK is less than the reference threshold CKmax, it is determined that the mining environment of the layout reference object is consistent with the analysis object, retrieving the reference data of the layout reference object and sending it to the mobile terminal of the management personnel through the disaster change monitoring platform, and the reference data includes the number of monitoring devices adopted by the monitoring matching means, the installation location, and the signal transmission method; if the reference coefficient CK is greater than or equal to the reference threshold CKmax, it is determined that the mining environment of the layout reference object is inconsistent with the analysis object, marking the matching object ranked second in the reference sequence as the new layout reference object, comparing the new layout reference object with the analysis object again, and so on until the extraction of the reference data is completed.

[0016] Further, the specific process of comparing the layout reference object with the analysis object includes: obtaining the stress deviation data YP, the temperature deviation data WP, and the dip angle deviation data QP between the layout reference object and the analysis object. The stress deviation data YP is the absolute value of the difference between the maximum high ground stress of the layout reference object and the maximum high ground stress of the analysis object. The temperature deviation data YP is the absolute value of the temperature difference between the layout reference object and the analysis object in the underground rock formation. The dip angle deviation data QP is the absolute value of the difference between the coal seam dip angle values of the layout reference object and the analysis object; calculating the reference coefficient CK of the layout reference object relative to the analysis object through numerical calculation of the stress deviation data YP, the temperature deviation data WP, and the dip angle deviation data QP.

[0017] A method for monitoring the disaster changes of the surrounding rock of a coal mine roadway includes the following steps:

[0018] Step 1: Statistically analyze the historical monitoring data of the disaster changes of the surrounding rock of the coal mine roadway: Mark the roadways that have completed coal mining as statistical objects, and the historical monitoring data of the statistical objects includes: mining depth value, monitoring means, protection means, monitoring effective value, and disaster change status;

[0019] Step 2: Process the historical monitoring data of the surrounding rock disasters in the coal mine roadway: The depth range is formed by the maximum and minimum values of the mining depths of all statistical objects. The depth range is divided into several depth intervals. The statistical objects with mining depth values within the depth interval are marked as the matching objects of the depth interval. The monitoring matching means and the protection matching means are marked according to the monitoring effective values and disaster states of the matching objects;

[0020] Step 3: Conduct disaster monitoring and analysis on the coal mine roadway: Mark the coal mine roadway to be subjected to disaster monitoring and analysis as the analysis object, obtain the mining depth value of the analysis object, retrieve the monitoring matching means and the protection matching means corresponding to the depth interval of the mining depth value and mark them as the monitoring implementation means and the protection implementation means of the analysis object;

[0021] Step 4: Extract the reference data of the layout reference object: Arrange the matching objects using the protection matching means and the monitoring matching means within the depth interval in descending order of the monitoring effective values to obtain a reference sequence. Screen the layout reference objects from the reference sequence, compare the layout reference objects with the analysis object, and extract the reference data of the layout reference object.

[0022] The present invention has the following beneficial effects:

[0023] 1. Through the historical data statistics module, the historical monitoring data of the surrounding rock disasters in the coal mine roadway can be statistically analyzed, parameters such as the mining depth value, monitoring means, and protection means can be recorded, and the recorded results provide data support for the data processing and analysis process;

[0024] 2. Through the historical data processing module, the historical monitoring data of the surrounding rock disasters in the coal mine roadway can be processed. After processing the mining depth value, a depth interval is formed. Then, the matching objects in the depth interval are classified according to the monitoring means and the protection means. Finally, the monitoring matching means and the protection matching means are marked according to the monitoring effective value and the disaster state, enabling coal mine roadways with different mining depths to quickly match suitable monitoring means and protection means and ensuring the safety of coal mining;

[0025] 3. Through the disaster monitoring and analysis module, disaster monitoring and analysis can be conducted on the coal mine roadway. According to the mining depth value of the analysis object, the monitoring matching means and the protection matching means of the depth interval are retrieved and allocated. Then, a reference sequence is generated. Layout reference objects are sequentially selected from the reference sequence and compared with the analysis object, and the reference data of the layout reference object whose mining environment is consistent with the analysis object are extracted. According to the reference data, the monitoring equipment in the roadway of the analysis object is arranged, further improving the effectiveness of the monitoring data. Description of the Drawings

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0027] Figure 1 It is the system block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 It is the method flow chart of Embodiment 2 of the present invention. Detailed implementation manners

[0029] The following will clearly and completely describe the technical solutions of the present invention in combination with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0030] Embodiment 1: As Figure 1 shown, a coal mine roadway surrounding rock disaster monitoring system includes a disaster monitoring platform, and the disaster monitoring platform is communicatively connected to a historical data statistics module, a historical data processing module, a disaster monitoring analysis module, and a database.

[0031] The historical data statistics module is used to statistically analyze the historical monitoring data of the surrounding rock disasters in coal mine roadways: mark the roadways that have completed coal mining as statistical objects, and the historical monitoring data of the statistical objects include: mining depth value, monitoring means, protection means, monitoring effectiveness value, and disaster state. The monitoring means include convergence meter measurement, multi-point displacement meter measurement, acoustic monitoring equipment, and vibration meter measurement. The protection means include support protection, reinforcement protection, stress control protection, and shotcrete protection; the monitoring effectiveness value is the ratio of the number of effective alarm signals to the number of ineffective alarm signals when the statistical object uses the monitoring means for disaster risk monitoring; the disaster state includes the occurrence of disasters and the avoidance of disasters. The occurrence of disasters means that a disaster accident has occurred in the statistical object during the entire coal mining process, and the avoidance of disasters means that no disaster accident has occurred in the statistical object during the entire coal mining process; record parameters such as the mining depth value, monitoring means, and protection means, and provide data support for the data processing and analysis process according to the recording results.

[0032] The historical data processing module is used to process the historical monitoring data of surrounding rock disasters in coal mine roadways: The depth range is composed of the maximum and minimum values of the mining depths of all statistical objects. The depth range is divided into several depth intervals. The statistical objects with mining depth values within the depth intervals are marked as matching objects of the depth intervals. The matching objects are classified according to the adopted monitoring means and protection means. The matching objects using the same monitoring means are marked as monitoring division objects. The average value of the sum of the effective monitoring values of all monitoring division objects is obtained as the priority data of the monitoring means. The monitoring means with the largest priority data is marked as the monitoring matching means of the depth interval. The matching objects using the same protection means are marked as protection division objects. The ratio of the number of protection division objects with the disaster state of avoiding disasters to the total number of protection division objects is marked as protection data. The protection means with the largest protection data is marked as the protection matching means of the depth interval. After processing the mining depth values to form depth intervals, the matching objects of the depth intervals are classified according to the monitoring means and protection means. Finally, the monitoring matching means and protection matching means are marked according to the effective monitoring values and disaster states, so that coal mine roadways with different mining depths can quickly match suitable monitoring means and protection means, ensuring the safety of coal mine mining.

[0033] The disaster monitoring and analysis module is used to conduct disaster monitoring and analysis on coal mine roadways: The coal mine roadway for which disaster monitoring and analysis is to be carried out is marked as the analysis object. The mining depth value of the analysis object is obtained. The monitoring matching means and protection matching means corresponding to the depth interval of the mining depth value are retrieved and marked as the monitoring implementation means and protection implementation means of the analysis object. The matching objects within the depth interval using the protection matching means and monitoring matching means are sorted in descending order of the effective monitoring value to obtain a reference sequence. The matching object ranked first in the reference sequence is marked as the layout reference object. The layout reference object is compared with the analysis object to obtain a reference coefficient CK.

[0034] The reference threshold CKmax is obtained through the database. The reference coefficient CK is compared with the reference threshold CKmax: If the reference coefficient CK is less than the reference threshold CKmax, it is determined that the mining environment of the layout reference object is consistent with that of the analysis object. The reference data of the layout reference object is retrieved and sent to the mobile terminal of the management personnel through the disaster monitoring platform. The reference data includes the number of monitoring devices used by the monitoring matching means, the installation location, and the signal transmission method. If the reference coefficient CK is greater than or equal to the reference threshold CKmax, it is determined that the mining environment of the layout reference object is inconsistent with that of the analysis object. The matching object ranked second in the reference sequence is marked as the new layout reference object. The new layout reference object is compared with the analysis object again, and so on, until the extraction of the reference data is completed.

[0035] The specific process of comparing the layout reference object with the analysis object includes: obtaining the stress deviation data YP, temperature deviation data WP, and dip angle deviation data QP of the layout reference object and the analysis object. The stress deviation data YP is the absolute value of the difference between the maximum high ground stress of the layout reference object and the maximum high ground stress of the analysis object. The temperature deviation data YP is the absolute value of the temperature difference between the layout reference object and the analysis object in the underground rock formation. The dip angle deviation data QP is the absolute value of the difference between the coal seam dip angle values of the layout reference object and the analysis object. The reference coefficient CK of the layout reference object relative to the analysis object is obtained through the formula CK = c1×YP + c2×WP + c3×QP, where c1, c2, and c3 are all proportionality coefficients, and c1 > c2 > c3 > 1. The monitoring matching means and protection matching means of the depth interval are retrieved according to the mining depth value of the analysis object for allocation, and then a reference sequence is generated. The layout reference object and the analysis object are sequentially selected from the reference sequence for comparison. The reference data of the layout reference object whose mining environment is consistent with the analysis object is extracted, and the monitoring equipment in the roadway of the analysis object is arranged according to the reference data to further improve the effectiveness of the monitoring data.

[0036] Embodiment 2: As Figure 2 shown, a method for monitoring the disaster transformation of the surrounding rock of a coal mine roadway includes the following steps:

[0037] Step 1: Statistically analyze the historical monitoring data of the disaster transformation of the surrounding rock of the coal mine roadway: Mark the roadway where coal mining has been completed as the statistical object. The historical monitoring data of the statistical object includes: mining depth value, monitoring means, protection means, monitoring effective value, and disaster transformation state.

[0038] Step 2: Process the historical monitoring data of the disaster transformation of the surrounding rock of the coal mine roadway: The depth range is composed of the maximum and minimum values of the mining depth values of all statistical objects. The depth range is divided into several depth intervals. The statistical objects whose mining depth values are within the depth interval are marked as the matching objects of the depth interval. The monitoring matching means and protection matching means are marked according to the monitoring effective value and disaster transformation state of the matching objects.

[0039] Step 3: Conduct disaster transformation monitoring and analysis on the coal mine roadway: Mark the coal mine roadway undergoing disaster transformation monitoring and analysis as the analysis object, obtain the mining depth value of the analysis object, retrieve the monitoring matching means and protection matching means of the corresponding depth interval of the mining depth value, and mark them as the monitoring implementation means and protection implementation means of the analysis object.

[0040] Step 4: Extract reference data of the layout reference object: Arrange the matching objects that adopt the protection matching means and the monitoring matching means within the depth interval in descending order of the monitoring effective value to obtain a reference sequence, screen the layout reference object from the reference sequence, compare the layout reference object with the analysis object, and extract the reference data of the layout reference object.

[0041] A coal mine roadway surrounding rock disaster monitoring system and method. During operation, mark the roadway where coal mining has been completed as the statistical object. The historical monitoring data of the statistical object includes: mining depth value, monitoring means, protection means, monitoring effective value, and disaster state. The depth range is composed of the maximum and minimum values of the mining depth values of all statistical objects. Divide the depth range into several depth intervals, and mark the statistical objects with mining depth values within the depth interval as the matching objects of the depth interval. Mark the monitoring matching means and the protection matching means according to the monitoring effective value and the disaster state of the matching object. Mark the coal mine roadway for disaster monitoring analysis as the analysis object, obtain the mining depth value of the analysis object, and retrieve the monitoring matching means and the protection matching means corresponding to the depth interval of the mining depth value and mark them as the monitoring implementation means and the protection implementation means of the analysis object. Arrange the matching objects that adopt the protection matching means and the monitoring matching means within the depth interval in descending order of the monitoring effective value to obtain a reference sequence, screen the layout reference object from the reference sequence, compare the layout reference object with the analysis object, and extract the reference data of the layout reference object.

[0042] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of the present technology make various modifications or supplements to the described specific embodiments or use similar methods for substitution. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should all fall within the protection scope of the present invention.

[0043] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients in the formula are set by those skilled in the art according to the actual situation. For example: the formula CK = c1×YP + c2×WP + c3×QP; those skilled in the art collect multiple groups of sample data and set corresponding reference coefficients for each group of sample data; substitute the set reference coefficients and the collected sample data into the formula, and any three formulas form a system of linear equations with three variables. Screen the calculated coefficients and take the average value to obtain the values of c1, c2, and c3 as 3.68, 2.81, and 2.32 respectively.

[0044] The magnitude of the coefficient is a specific value obtained by quantifying each parameter, which facilitates subsequent comparison. Regarding the magnitude of the coefficient, it depends on the amount of sample data and the reference coefficients initially set by those skilled in the art for each set of sample data; as long as the proportional relationship between the parameter and the quantified value is not affected, for example, the reference coefficient is proportional to the value of the stress deviation data.

[0045] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0046] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A coal mine tunnel surrounding rock disaster monitoring system, characterized in that: It includes a disaster monitoring platform, which is communicatively connected to a historical data statistics module, a historical data processing module, a disaster monitoring and analysis module, and a database; The historical data statistics module is used to perform statistical analysis on the historical monitoring data of surrounding rock disasters in coal mine tunnels: the tunnels that have completed coal mining are marked as statistical objects, and the historical monitoring data of the statistical objects include: mining depth value, monitoring means, protection means, monitoring effective value and disaster status; The historical data processing module is used to process the historical monitoring data of surrounding rock disasters in coal mine tunnels: the maximum and minimum mining depth values ​​of all statistical objects constitute a depth range, the depth range is divided into a number of depth intervals, the statistical objects whose mining depth values ​​are within the depth interval are marked as matching objects of the depth interval, the matching objects are classified according to the adopted monitoring means and protection means, and the monitoring matching means and protection matching means of the depth interval are marked; The disaster monitoring and analysis module is used to perform disaster monitoring and analysis on coal mine tunnels: the coal mine tunnels to be subjected to disaster monitoring and analysis are marked as analysis objects, the mining depth value of the analysis object is obtained, the monitoring matching means and protection matching means of the depth interval corresponding to the mining depth value are retrieved and marked as the monitoring implementation means and protection implementation means of the analysis object.

2. A coal mine tunnel surrounding rock disaster monitoring system according to claim 1, characterized in that: Monitoring methods include convergence meter measurement, multi-point displacement meter measurement, acoustic wave monitoring equipment and vibrator measurement; protection methods include support protection, reinforcement protection, stress control protection and anchor spraying protection; the monitoring effective value is the ratio of the number of valid alarm signals to the number of invalid alarm signals issued when the statistical object adopts monitoring methods to monitor the disaster risk; the disaster status includes the occurrence of disaster and the avoidance of disaster. The occurrence of disaster means that the statistical object has a disaster accident in the whole process of coal mining, and the avoidance of disaster means that the statistical object has no disaster accident in the whole process of coal mining.

3. A coal mine tunnel surrounding rock disaster monitoring system according to claim 2, characterized in that: The specific process of marking the monitoring matching means and protection matching means of the depth interval includes: marking the matching objects using the same monitoring means as monitoring division objects, summing up and averaging the monitoring effective values ​​of all monitoring division objects to obtain the priority data of the monitoring means, and marking the monitoring means with the largest priority data as the monitoring matching means of the depth interval; marking the matching objects using the same protection means as protection division objects, marking the ratio of the number of protection division objects whose disaster status is disaster avoidance to the total number of protection division objects as protection data, and marking the protection means with the largest protection data as the protection matching means of the depth interval.

4. A coal mine tunnel surrounding rock disaster monitoring system according to claim 3, characterized in that: The specific process of disaster monitoring and analysis of coal mine tunnels includes: arranging the matching objects of protection matching means and monitoring matching means in the depth interval in descending order of monitoring effective value to obtain a reference sequence, marking the first matching object in the reference sequence as a layout reference object, comparing the layout reference object with the analysis object and obtaining a reference coefficient CK, and extracting the reference data of the layout reference object through the reference coefficient CK.

5. A coal mine tunnel surrounding rock disaster monitoring system according to claim 4, characterized in that: The specific process of extracting the reference data of the layout reference object includes: obtaining the reference threshold CKmax through the database, comparing the reference coefficient CK with the reference threshold CKmax: if the reference coefficient CK is less than the reference threshold CKmax, it is determined that the mining environment of the layout reference object is consistent with the analysis object, and the reference data of the layout reference object is retrieved and sent to the mobile terminal of the manager through the disaster monitoring platform. The reference data includes the number of monitoring devices used in the monitoring matching means, the installation location and the signal transmission method; if the reference coefficient CK is greater than or equal to the reference threshold CKmax, it is determined that the mining environment of the layout reference object is inconsistent with the analysis object, and the second matching object in the reference sequence is marked as a new layout reference object, and the new layout reference object is compared with the analysis object again, and so on, until the reference data is extracted.

6. A coal mine tunnel surrounding rock disaster monitoring system according to claim 5, characterized in that: The specific process of comparing the layout reference object with the analysis object includes: obtaining stress deviation data YP, temperature deviation data WP and inclination deviation data QP of the layout reference object and the analysis object, the stress deviation data YP is the absolute value of the difference between the maximum ground stress of the layout reference object and the maximum ground stress of the analysis object, the temperature deviation data YP is the absolute value of the temperature difference between the layout reference object and the analysis object in the underground rock formation, and the inclination deviation data QP is the absolute value of the difference between the inclination angle of the coal seam of the layout reference object and the analysis object; the reference coefficient CK of the layout reference object relative to the analysis object is obtained by numerically calculating the stress deviation data YP, the temperature deviation data WP and the inclination deviation data QP.

7. A method for monitoring disasters in surrounding rock of coal mine tunnels, characterized in that: The following steps are involved: Step 1: Statistical analysis of the historical monitoring data of surrounding rock disasters in coal mine tunnels: Mark the tunnels that have completed coal mining as statistical objects. The historical monitoring data of the statistical objects include: mining depth value, monitoring means, protection means, monitoring effective value and disaster status; Step 2: Process the historical monitoring data of surrounding rock disasters in coal mine tunnels: the maximum and minimum mining depth values ​​of all statistical objects constitute a depth range, the depth range is divided into several depth intervals, and the statistical objects whose mining depth values ​​are within the depth interval are marked as matching objects of the depth interval. The monitoring matching means and the protection matching means are marked according to the monitoring effective value and disaster status of the matching object; Step 3: Conduct disaster monitoring and analysis on coal mine tunnels: Mark the coal mine tunnels for disaster monitoring and analysis as analysis objects, obtain the mining depth value of the analysis object, retrieve the monitoring matching means and protection matching means of the depth interval corresponding to the mining depth value, and mark them as the monitoring implementation means and protection implementation means of the analysis object; Step 4: Extract the reference data of the layout reference object: Arrange the matching objects that use protection matching means and monitoring matching means within the depth interval in descending order of monitoring effective value values ​​to obtain a reference sequence, screen the layout reference objects from the reference sequence, compare the layout reference objects with the analysis objects, and extract the reference data of the layout reference objects.

Images