An intelligent evaluation model and method for coal mine tunnel safety

Abstract

The present invention discloses an intelligent evaluation model and method for coal mine roadway safety, which relates to the technical field of coal mine roadway safety evaluation. The model includes a data acquisition and preprocessing module, a tunneling working section roof safety evaluation module, a tunneling impact section safety evaluation module, a mining impact section safety evaluation module, and a roadway safety evaluation response feedback module. The present invention realizes real-time monitoring and dynamic evaluation of coal mine roadway safety by adding laser radar, anchor stress gauge, anchor cable stress gauge, roof separation meter and other equipment to the main equipment and anchor materials of the coal mine roadway through multivariate data fusion analysis. By proposing eight evaluation indicators under the three roadway usage scenarios of tunneling working section, tunneling impact section and mining impact section, the safety of coal mine roadways can be dynamically analyzed, monitored in real time, and timely feedback can be provided to ensure the safety and stability of coal mine roadways during their use cycle, thus solving the problem of difficult roadway safety evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine tunnel safety evaluation, and in particular to a coal mine tunnel safety intelligent evaluation model and method. Background Art

[0002] With the continuous improvement of coal mine production levels, the application of tunnel safety monitoring methods such as anchor stress gauges, anchor cable stress gauges, and roof separation meters in coal mine tunnels has gradually increased. However, the current application of various monitoring methods is relatively independent, and can only monitor the working status of the target anchor protection equipment, and cannot form a comprehensive evaluation and timely feedback on tunnel safety.

[0003] Tunnel excavation can be divided into four sections based on the process: the excavation working section, the excavation impact section, and the mining impact section. The excavation working section is when the excavation equipment is engaged in excavation work. During this stage, the working face roof is essentially exposed, with no relevant support measures. The excavation impact section is the stage after the tunnel excavation and support work is completed. This section is susceptible to safety hazards due to the stress concentration at the head of the excavation. The mining impact section is the stage after the tunnel excavation work is completed and begins to be affected by mining. This section is susceptible to safety hazards due to the stress concentration of mining.

[0004] The use of bolt stress gauges, cable stress gauges, and roof separation meters in coal mine roadways provides a technical basis for roadway stability assessment. However, there is still a lack of comprehensive, real-time, and accurate evaluation methods to determine whether the support level and surrounding rock stability at each stage of roadway support meet the requirements for safe mine production. Existing coal mine roadway safety assessments focus on summary evaluations of roadway support levels and lack regular evaluations of roadway safety during roadway excavation and mining. This makes it difficult to meet the real-time evaluation and intelligent early warning requirements for safe and efficient coal mine production. Summary of the Invention

[0005] In view of this, the present invention discloses an intelligent evaluation model and method for coal mine tunnel safety. By comprehensively, real-time and accurately evaluating the support level and surrounding rock deformation during coal mine tunnel excavation and mining, an intelligent evaluation of the safety of coal mine tunnels during their service life is achieved, which can be widely applied to the fields of tunnels and tunnels.

[0006] According to the purpose of the present invention, an intelligent evaluation model for coal mine roadway safety is proposed, which includes a data acquisition and preprocessing module, a tunneling working section roof safety evaluation module, a tunneling influence section safety evaluation module, a mining influence section safety evaluation module, and a roadway safety evaluation response feedback module; the data acquisition and preprocessing module is respectively connected to the tunneling working section roof safety evaluation module, the tunneling influence section safety evaluation module, and the mining influence section safety evaluation module, and is used to obtain relevant point cloud data of the tunneling roadway roof profile, anchor net profile, anchor rod position, and anchor cable position, as well as anchor rod stress and number, anchor cable stress and number, roadway roof delamination amount, and delamination meter position data for preprocessing, and transmits them to the tunneling working section roof safety evaluation module, the tunneling influence section safety evaluation module, and the mining influence section safety evaluation module;

[0007] The tunneling section roof safety evaluation module is used to perform real-time analysis and calculation on the pre-processed point cloud data of the roof during tunneling of the tunneling equipment to obtain a tunneling section roof safety evaluation index;

[0008] The tunneling influence section safety evaluation module is used to perform real-time analysis and calculation on the pre-processed anchor support point cloud data, anchor cable support point cloud data and anchor net support point cloud data of the tunneling influence section to obtain the tunneling influence section safety evaluation index;

[0009] The mining influence section safety evaluation module is used to perform real-time analysis and calculation on the pre-processed anchor support point cloud data, anchor cable support point cloud data, anchor net support point cloud data, anchor stress gauge data, anchor cable stress gauge data and roof separation meter data of the mining influence section to obtain the mining influence section safety evaluation index;

[0010] The tunnel safety evaluation response feedback module is respectively connected to the excavation working section roof safety evaluation module, the excavation influence section safety evaluation module, and the mining influence section safety evaluation module, and is used to provide signal feedback based on the evaluation indicators of each stage provided by the excavation working section roof safety evaluation module, the excavation influence section safety evaluation module, and the mining influence section safety evaluation module, and to issue danger warnings for areas with excessive overhead distance, insufficient support, failed support, and obvious detachment, so as to remind the construction team to make timely reinforcements.

[0011] Preferably, the data acquisition and preprocessing module includes a tunneling machinery laser radar data acquisition submodule, a rail vehicle laser radar data acquisition submodule, an anchor stress gauge data acquisition submodule, an anchor cable stress gauge data acquisition submodule, a roof delamination instrument data acquisition submodule, and a data preprocessing submodule; the tunneling machinery laser radar data acquisition submodule, the rail vehicle laser radar data acquisition submodule, the anchor stress gauge data acquisition submodule, the anchor cable stress gauge data acquisition submodule, and the roof delamination instrument data acquisition submodule are respectively connected to the data preprocessing submodule, and the data preprocessing submodule is respectively connected to the tunneling working section roof safety evaluation module, the tunneling influence section safety evaluation module, and the mining influence section safety evaluation module;

[0012] The tunneling section roof safety assessment module includes a tunneling section point cloud data parsing submodule, a suspended roof size analysis submodule, and a roof safety assessment submodule; the tunneling section point cloud data parsing submodule is connected to the data preprocessing submodule; the tunneling section point cloud data parsing submodule is connected to the suspended roof size analysis submodule; the suspended roof size analysis submodule is connected to the roof safety assessment submodule; and the roof safety assessment submodule is connected to the tunnel safety assessment response feedback module.

[0013] The tunneling influence section safety evaluation module includes a tunneling influence section point cloud data analysis submodule, an anchor support quality evaluation submodule, an anchor cable support quality evaluation submodule, and an anchor net support quality evaluation submodule; the tunneling influence section point cloud data analysis submodule is connected to the data preprocessing submodule; the tunneling influence section point cloud data analysis submodule is respectively connected to the anchor support quality evaluation submodule, the anchor cable support quality evaluation submodule, and the anchor net support quality evaluation submodule; the anchor support quality evaluation submodule, the anchor cable support quality evaluation submodule, and the anchor net support quality evaluation submodule are respectively connected to the tunnel safety evaluation response feedback module;

[0014] The mining influence section safety evaluation module includes a mining influence section point cloud data analysis submodule, an anchor support abnormality evaluation submodule, an anchor cable support abnormality evaluation submodule, an anchor net support abnormality evaluation submodule and a roof detachment abnormality evaluation submodule; the mining influence section point cloud data analysis submodule is connected to the data preprocessing submodule; the mining influence section point cloud data analysis submodule is respectively connected to the anchor support abnormality evaluation submodule, the anchor cable support abnormality evaluation submodule, the anchor net support abnormality evaluation submodule and the roof detachment abnormality evaluation submodule; the anchor support abnormality evaluation submodule, the anchor cable support abnormality evaluation submodule, the anchor net support abnormality evaluation submodule and the roof detachment abnormality evaluation submodule are respectively connected to the tunnel safety evaluation response feedback module.

[0015] Preferably, the tunneling machinery laser radar data acquisition submodule is a laser radar sensor installed on the tunneling equipment, which is used to scan the tunnel information including the exposed range contour of the roof, the protection contour of the shield beam, the contour of the anchor rod and anchor cable, the contour of the anchor net, and the contour of the steel belt during the tunnel support process, and obtain three-dimensional point cloud data in the absolute coordinate system of the earth;

[0016] The rail vehicle laser radar data acquisition submodule is a laser radar sensor installed on the rail vehicle, which is used to perform normalized scanning of the tunnel support material and obtain three-dimensional point cloud data in the absolute coordinate system of the earth;

[0017] The anchor stress meter data acquisition submodule is an anchor stress meter installed on the tunnel surrounding rock anchor, which is used to record the working status of the anchor and obtain the corresponding numbered anchor working resistance data.

[0018] The anchor cable stress meter data acquisition submodule is installed on the anchor cable stress meter on the tunnel surrounding rock anchor cable, and is used to record the working status of the anchor cable and obtain the working resistance data of the corresponding number of the anchor cable.

[0019] The roof separation meter data acquisition submodule is a roof separation meter installed on the tunnel roof, which is used to monitor the separation position and separation amount of the roof at different depths and obtain the roof separation amount at the corresponding tunnel position.

[0020] The data preprocessing submodule is used to set scanning parameters for the three-dimensional point cloud data of tunnel support equipment and support parameters obtained by the tunneling machinery laser radar data acquisition submodule and the rail vehicle laser radar data acquisition submodule, and to eliminate redundant data through noise reduction processing, and to perform segmented processing on the support point cloud data of different support stages to obtain point cloud data of the tunneling working section, tunneling impact section, and mining impact section respectively; the type of the point cloud data is the XYZ three-dimensional coordinates and echo intensity value of the target unit.

[0021] Preferably, the excavation working section point cloud data parsing submodule receives the point cloud data provided by the data preprocessing submodule, selects the point cloud data of the front end, left side, and right side edges of the roof of the coal mine tunnel excavation working face, and the point cloud data of the anchor rods in the front row, and sequentially connects the above data in a clockwise or counterclockwise direction to form a closed polygonal area, thereby obtaining the contour data of the exposed roof of the excavation working face;

[0022] The overhang size analysis submodule analyzes the exposed contour data of the overhang of the tunneling working face processed by the tunneling working section point cloud data analysis submodule to obtain the length L of the overhang of the tunnel after the tunneling equipment has been driven.

[0023] The roof safety evaluation submodule analyzes the size data of the exposed roof range processed by the tunneling working section point cloud data analysis submodule, calculates the ratio S1 of the difference between the length of the tunnel hanging roof part and the design parameter and the design parameter, and determines whether the hanging roof range of the tunneling working section meets the design requirements; the calculation formula is: S1 = |(LL d ) / L d |, where L d Design length for the suspended roof part of the tunnel.

[0024] Preferably, the tunneling impact section point cloud data parsing submodule receives the point cloud data provided by the data preprocessing submodule, numbers the anchor rods and anchor cables that complete all the support work of the tunnel, accurately locates the three-dimensional coordinates of each anchor rod and anchor cable, accurately identifies the position coordinates of the intersection points of the anchor network grid, and forms the anchor network contour data;

[0025] The anchor support quality evaluation submodule analyzes and processes the numbered anchor point cloud data provided by the tunneling impact section point cloud data analysis submodule, and calculates the actual spacing d of each anchor. i左 d i右 and actual row spacing d i前 d i后 And find the distance d between it and the design i间 d i排 The difference between △d i左间 , △d i右间 , △d i前排 , △d i后排 , and then calculate the average spacing difference △d of a single anchor i =(△d i左间 +△d i右间 +△d i前排 +△d i后排 ) / 4, and finally calculate the maximum value of the difference between the spacing of all anchors in the reinforced support section and the design size S2=max(△d i ) as the basis for judging the quality evaluation of anchor support in the tunneling affected section;

[0026] The anchor cable support quality evaluation submodule analyzes and processes the numbered anchor cable point cloud data provided by the tunneling impact section point cloud data analysis submodule, and calculates the actual spacing d of each anchor cable. j左 d j右 and actual row spacing d j前 d j后 And find the distance d between it and the design j间 d j排 The difference between △d j左间 , △d j右间 , △d j前排 , △d j后排, and then calculate the average spacing difference △d of a single anchor cable j =(△d j左间 +△d j右间 +△d j前排 +△d j后排 ) / 4, and finally calculate the maximum value of the difference between the spacing of all anchor cables in the reinforced support section and the design size S3=max(△d j ) as the basis for judging the quality evaluation of anchor cable support in the excavation-affected section;

[0027] The anchor net support quality evaluation submodule analyzes and processes the tunnel contour data and anchor net contour data provided by the reinforced support section point cloud data analysis submodule, and calculates the tunnel roof contour area S respectively. 顶 and the area S of the anchor net laid on the tunnel roof 网 , and obtain the anchor net laying index S4 of the reinforced support section roadway = (S 顶 -S 网 ) / S 网 It serves as the basis for evaluating the quality of anchor net support in the strengthened support section.

[0028] Preferably, the mining influence section point cloud data parsing submodule receives the three-dimensional point cloud and numbering data of the anchor rods, anchor cables and anchor nets from the tunneling influence section point cloud data parsing submodule as the original data of the tunnel support equipment, receives the three-dimensional point cloud data, anchor rod stress gauge data, anchor cable stress gauge data and roof detachment provided by the data preprocessing submodule as the real-time support status data of the anchor material, and analyzes and organizes the three-dimensional point cloud data, anchor rod stress gauge data, anchor cable stress gauge data and roof detachment of the anchor rods, anchor cables and anchor nets into a data set consistent with the anchor material number provided by the tunneling influence section point cloud data parsing submodule; and realizes dynamic evaluation and real-time monitoring of the support quality of the tunnel anchor material by comparing the changes of the anchor rods, anchor cables, anchor nets and roof detachment during the tunnel mining process;

[0029] The anchor support abnormality evaluation submodule receives the initial horizontal position parameter d of the anchor provided by the mining impact section point cloud data analysis submodule. i左间 d i右间 d i前排 d i后排 and vertical height coordinate z i , and obtain in real time the horizontal position parameter d of the roadway anchor in the state of mining disturbance during the mining process of the coal mine working face i左间 '、d i右间 '、d i前排 '、d i后排 ', vertical height coordinate z i ' and anchor stress gauge data, and then calculate the real-time horizontal position difference △d of the anchor i左间 '=|di左间 '-d i左间 |, △d i右间 '=|d i右间 '-d i右间 |, △d i前排 '=|d i前排 '-d i前排 |, △d i后排 '=|d i后排 '-d i后排 | and vertical height parameter difference △z i =|z i -z i '|, calculate the average spacing difference △d of a single anchor i '=(△d i左间 '+△d i右间 '+△d i前排 '+△d i后排 ') / 4, and then calculate the anchor stress value F i The difference between F0 and the original rock stress △F i =|F i -F0|, and finally calculate the maximum change value S5=max[(△d i '+△z i ) / (2d i间 +2d i排 )+(△F i / F0)] as the basis for judging the abnormal evaluation of anchor support in the mining-affected section;

[0030] The anchor support abnormality evaluation submodule receives the initial horizontal position parameter d of the anchor provided by the mining impact segment point cloud data analysis submodule. j左间 d j右间 d j前排 d j后排 and vertical height coordinate z j , and obtain in real time the horizontal position parameter d of the tunnel anchor cable under the mining disturbance state during the mining process of the coal mine working face j左间 '、d j右间 '、d j前排 '、d j后排 ', vertical height coordinate z j ' and the anchor cable stress gauge data, and then calculate the real-time horizontal position difference △d of the anchor cable j左间 '=|d j左间 '-d j左间 |, △d j右间 '=|d j右间 '-d j右间 |, △d j前排 '=|d j前排 '-d j前排 |, △dj后排 '=|d j后排 '-d j后排 | and vertical height parameter difference △z j =|z j -z j '|, calculate the average spacing difference △d of a single anchor cable j '=(△d j左间 '+△d j右间 '+△d j前排 '+△d j后排 ') / 4, and then calculate the anchor stress value F j The difference between F0 and the original rock stress △F j =|F j -F0|, and finally calculate the maximum change value of all anchor cables in the mining influence section S6=max[(△d j '+△z j ) / (2d j间 +2d j排 )+(△F j / F0)] as the basis for judging abnormal evaluation of anchor cable support in mining-affected sections;

[0031] The anchor net support abnormality evaluation submodule is to receive the roadway roof contour area S provided by the mining impact segment point cloud data analysis submodule. 顶 and the area S of the anchor net laid on the tunnel roof 网 , and obtain in real time the area S of the anchor net under the disturbance state during the mining process of the coal mine working face 网 ', and obtain the abnormal index of the roadway anchor net support under the mining disturbance state S7=(S 顶 -S 网 ') / S 网 It serves as the basis for evaluating the abnormality of anchor net support in the mining-affected section.

[0032] The roof separation abnormality evaluation submodule is to receive the roadway roof separation value S provided by the mining impact segment point cloud data analysis submodule. i , and obtain the abnormal index of roadway roof separation under mining disturbance state S8=S i It serves as the basis for evaluating the abnormal roof separation in the mining-affected section.

[0033] Preferably, the tunnel safety evaluation response feedback module can provide signal feedback based on the evaluation indicators of each stage provided by each evaluation module, and issue a danger warning for areas with excessive overhang distance, insufficient support, failed support, and excessive separation, so as to remind the construction team to carry out timely reinforcement, including the following steps:

[0034] Step 1: Use 10*(1-S1) as the score of the roof safety quality of the excavation working section. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued, the excavation work will be stopped, the staff will be evacuated, and support will be strengthened; if the score is qualified, a reminder will be issued, the excavation work will be stopped, and the next support work will be carried out; if the score is excellent, no reminder will be given;

[0035] Step 2: Use 10-S2 as the score for the anchor support quality; scores of 0-8, 8-9, and 9-10 are respectively given as unqualified, qualified, and excellent. If the score is unqualified, an immediate warning is issued and reinforced support is carried out; if the score is qualified, the staff is reminded to pay attention to the roof movement in the relevant area; if the score is excellent, no reminder is given;

[0036] Step 3: Use 10-S3 as the score for the anchor support quality; for scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and reinforced support will be carried out; if the score is qualified, the staff will be reminded to pay attention to the roof movement in the relevant area; if the score is excellent, no reminder will be given;

[0037] Step 4: Use 10*(1-S4) as the score of the anchor net support quality. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and the anchor net will be laid on the part with a void top. If the score is qualified, the staff will be reminded to check the working status of the anchor net and replace the part with a leak or damage. If the score is excellent, no reminder will be given.

[0038] Step 5: Use 10-S5 as the score for the anchor support quality of the mining-affected section. Scores of 0-8, 8-9, and 9-10 are assigned as unqualified, qualified, and excellent, respectively. If the score is unqualified, an immediate warning is issued and anchors with obvious displacement are replaced or reinforced. If the score is qualified, the staff is reminded to check the working status of the corresponding anchors and reinforce them in a timely manner. If the score is excellent, no reminder is given.

[0039] Step 6: Use 10-S6 as the score for the anchor cable support quality of the mining-affected section. Scores of 0-8, 8-9, and 9-10 are assigned as unqualified, qualified, and excellent, respectively. If the score is unqualified, an immediate warning is issued and the anchor cables with obvious displacement are replaced or reinforced. If the score is qualified, the staff is reminded to check the working status of the corresponding anchor cables and reinforce them in a timely manner. If the score is excellent, no reminder is given.

[0040] Step 7: Use 10*(1-S7) as the score of the anchor net support quality in the mining-affected section; scores of 0-8, 8-9, and 9-10 are respectively given as unqualified, qualified, and excellent. If the score is unqualified, an immediate warning is issued and additional anchor nets are added to the anchor net area damaged by mining. If the score is qualified, the staff is reminded to check the working status of the anchor net and repair it in real time. If the score is excellent, no reminder is given.

[0041] Step 8: Use S8 as the score to judge the amount of roof separation in the mining-affected section. If the abnormal index S8 of the roadway roof separation is less than or equal to 50mm, the score is 10 points, and the roof separation is within a reasonable range and no special treatment is required. If the abnormal index S8 of the roadway roof separation is greater than 50mm and less than or equal to 80mm, the score is 9 points, and the roof separation exceeds the reasonable limit, and it is necessary to remind the staff to strengthen support. If the abnormal index S8 of the roadway roof separation is greater than 80mm and less than or equal to 150mm, the score is 8 points, and the roof separation is obviously abnormal, and it is necessary to report to the mine chief engineer, analyze the cause of the separation, and formulate measures. If the abnormal index S8 of the roadway roof separation is greater than 150mm, the score is 7 points, and the roof separation must be immediately evacuated. Relevant personnel in the roadway must be evacuated and special measures must be formulated to deal with it.

[0042] Step 9. Select the sum of all scores in steps 1 to 8 as the final score of the coal mine tunnel safety evaluation. If the total score is in the range of 0-60, 60-70, or 70-80, the coal mine tunnel safety evaluation is unqualified, qualified, or excellent.

[0043] The present invention further discloses a method for intelligently evaluating the safety of coal mine tunnels, comprising the following steps:

[0044] S1: During the tunnel excavation process, the laser radar sensor installed on the tunneling equipment is used to scan the tunnel information and tunnel support materials, obtain three-dimensional point cloud data and number the anchor materials; during the tunnel mining process, the laser radar sensor installed on the rail train is used to scan the tunnel information and tunnel support materials, obtain three-dimensional point cloud data and match it with the number of the anchor materials, use the anchor stress gauge and anchor cable stress gauge installed on the anchor rods and anchor cables to monitor the stress values ​​of the anchor rods and anchor cables, and use the roof delamination meter installed on the tunnel roof to monitor the delamination amount of the tunnel roof.

[0045] S2: Select the three-dimensional point cloud data of the excavation working section, calculate the safety index of the excavation empty top size, and provide the evaluation index to the tunnel safety evaluation response feedback module for real-time monitoring and feedback.

[0046] S3: Select the three-dimensional point cloud data of the tunneling affected section, calculate the anchor material support quality index of the tunneling affected section, and provide the evaluation index to the tunnel safety evaluation response feedback module for real-time monitoring and feedback.

[0047] S4: Select the three-dimensional point cloud data, anchor stress value, anchor cable stress and roof delamination of the mining-affected section, calculate the anchor material support quality index of the mining-affected section, and provide the evaluation index to the tunnel safety evaluation response feedback module for real-time monitoring and feedback.

[0048] S5: Based on the evaluation indicators provided at each stage, conduct a comprehensive score and comprehensive evaluation of the roadway safety, and finally obtain the coal mine roadway safety evaluation level.

[0049] Compared with the existing technology, the advantages of the intelligent evaluation model and method for coal mine tunnel safety disclosed in the present invention are:

[0050] The present invention adds laser radars, anchor stress gauges, anchor cable stress gauges, roof delamination meters and other equipment to the main equipment and anchor protection materials in coal mine tunnels, and realizes real-time monitoring and dynamic evaluation of coal mine tunnel safety through multivariate data fusion analysis, covering the tunnel safety evaluation of the entire cycle from tunnel excavation to the end of tunnel use; by proposing eight evaluation indicators in the three tunnel use scenarios of tunneling working section, tunneling impact section and mining impact section, the safety of coal mine tunnels can be dynamically analyzed, monitored in real time, and timely feedback can be given to ensure the safety and stability of coal mine tunnels during their use cycle, thus solving the problem of difficulty in tunnel safety evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, 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 paying any creative work.

[0052] Figure 1 This is the data collection structure diagram.

[0053] Figure 2 This is a schematic diagram of an intelligent evaluation model for coal mine tunnel safety disclosed in the present invention.

[0054] Figure 3 This is the structural diagram of the data acquisition and preprocessing module.

[0055] Figure 4 This is the structural diagram of the roof safety evaluation module for the excavation working section.

[0056] Figure 5 This is the structural diagram of the safety assessment module for the tunneling impact section.

[0057] Figure 6 This is the structural diagram of the safety assessment module for the mining impact section.

[0058] Figure 7 Schematic diagram of the tunnel safety evaluation response feedback module.

[0059] In the figure: 1-data acquisition and preprocessing module; 11-tunneling machinery laser radar data acquisition submodule; 12-railway vehicle laser radar data acquisition submodule; 13-anchor stress gauge data acquisition submodule; 14-anchor cable stress gauge data acquisition submodule; 15-roof separation meter data acquisition submodule; 16-data preprocessing submodule; 2-tunneling working section roof safety evaluation module; 21-tunneling working section point cloud data analysis submodule; 22-hanging roof size analysis submodule; 23-roof safety evaluation submodule; 3-tunneling affected section safety evaluation module; 31-tunneling affected section point cloud data analysis submodule; 32-anchor support quality evaluation submodule; 33-anchor cable Support quality evaluation submodule; 34-anchor net support quality evaluation submodule; 4-mining impact section safety evaluation module; 41-mining impact section point cloud data analysis submodule; 42-anchor support abnormality evaluation submodule; 43-anchor cable support abnormality evaluation submodule; 44-anchor net support abnormality evaluation submodule; 45-roof separation abnormality evaluation submodule; 5-tunnel safety evaluation response feedback module; 10-tunnel excavation equipment; 20-lidar sensor; 30-monorail crane; 40-anchor stress gauge; 50-anchor cable stress gauge; 60-roof separation meter; 70-edge computing module; 80-can to Ethernet module; 90-switch; 100-server. DETAILED DESCRIPTION

[0060] The following is a brief description of the specific embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts are also within the scope of protection of the present invention.

[0061] Figure 1-Figure 7 The preferred embodiments of the present invention are shown and analyzed in detail.

[0062] like Figure 2 The intelligent evaluation model for coal mine roadway safety shown includes a data acquisition and preprocessing module 1, a tunneling working section roof safety evaluation module 2, a tunneling impact section safety evaluation module 3, a mining impact section safety evaluation module 4, and a roadway safety evaluation response feedback module 5.

[0063] like Figure 3As shown, data acquisition and preprocessing module 1 is used to obtain relevant point cloud data of the tunnel roof profile, anchor mesh profile, anchor bolt position, anchor cable position, as well as anchor bolt stress and number, anchor cable stress and number, tunnel roof delamination, and delamination meter position data, preprocess the data, and transmit it to tunneling section roof safety assessment module 2, tunneling impact section safety assessment module 3, and mining impact section safety assessment module 4. Data acquisition and preprocessing module 1 includes tunneling machinery lidar data acquisition submodule 11, railcar lidar data acquisition submodule 12, anchor bolt stress gauge data acquisition submodule 13, anchor cable stress gauge data acquisition submodule 14, roof delamination meter data acquisition submodule 15, and data preprocessing submodule 16. The tunneling machinery laser radar data acquisition submodule 11, the rail vehicle laser radar data acquisition submodule 12, the anchor stress gauge data acquisition submodule 13, the anchor cable stress gauge data acquisition submodule 14, and the roof delamination meter data acquisition submodule 15 are respectively connected to the data preprocessing submodule 16, and the data preprocessing submodule 16 is respectively connected to the tunneling working section roof safety evaluation module 2, the tunneling impact section safety evaluation module 3, and the mining impact section safety evaluation module 4.

[0064] The tunneling machinery laser radar data acquisition submodule 11 is a laser radar sensor 20 installed on tunneling equipment 10 such as tunneling machines, tunneling and anchoring machines, and anchor trolleys. It is used to scan tunnel information including the exposed range contour of the roof, the protection contour of the protective beam, the contour of the anchor rod and anchor cable, the contour of the anchor net, and the contour of the steel belt during the tunnel support process, and obtain three-dimensional point cloud data in the absolute coordinate system of the earth, including XYZ three-dimensional coordinate data and echo intensity value, and pass the obtained three-dimensional point cloud data to the data preprocessing submodule 16 to provide original data for the safety evaluation of coal mine tunnels in the tunneling working section, tunneling impact section, and mining impact section. The rail vehicle lidar data acquisition submodule 12 is a lidar sensor 20 installed on the monorail crane 30. During the tunnel transportation process, the tunnel support materials are scanned in a normalized manner through auxiliary transportation equipment such as the monorail crane 30, and three-dimensional point cloud data in the absolute coordinate system of the earth is obtained in real time, including XYZ three-dimensional coordinate data and echo intensity values, and the obtained three-dimensional point cloud data is passed to the data preprocessing submodule 16.

[0065] The anchor stress meter data acquisition submodule 13 is an anchor stress meter 40 installed on the anchor in the surrounding rock of the tunnel, which is used to record the working status of the anchor and obtain the anchor working resistance data of the corresponding number.

[0066] The anchor cable stress meter data acquisition submodule 14 is installed on the anchor cable 50 on the surrounding rock anchor cable of the tunnel, and is used to record the working status of the anchor cable and obtain the working resistance data of the corresponding number of the anchor cable.

[0067] The roof separation meter data acquisition submodule 15 is a roof separation meter 60 installed on the roadway roof, which is used to monitor the separation position and separation amount of the roof at different depths and obtain the roof separation amount at the corresponding roadway position.

[0068] like Figure 1 As shown, the lidar sensor 20 is connected to an edge computing module 70, which is used for downhole mapping and real-time position calculation. The edge computing module 70 is also connected to a CAN-to-Ethernet module 80, which is used to convert the positioning information of the edge computing module 70 from CAN transmission to Ethernet transmission. The anchor stress gauge 40, anchor cable stress gauge 50, roof delamination meter 60, and CAN-to-Ethernet module 80 are then connected to a switch 90, which then connects to a server 100, which collects all the data.

[0069] The data preprocessing submodule 16 is used to set scanning parameters for the three-dimensional point cloud data of tunnel support equipment and support parameters obtained by the tunneling machinery laser radar data acquisition submodule 11, the rail vehicle laser radar data acquisition submodule 12, the anchor stress gauge data acquisition submodule 13, the anchor cable stress gauge data acquisition submodule 14 and the roof delamination meter data acquisition submodule 15, and eliminate redundant data through noise reduction processing, and perform segmented processing on the support point cloud data of different support stages to obtain point cloud data of the tunneling working section, the tunneling influence section, and the mining influence section respectively; the type of point cloud data is the XYZ three-dimensional coordinates and echo intensity value of the target unit.

[0070] like Figure 4 As shown, the tunneling section roof safety assessment module 2 is used to perform real-time analysis and calculation of the pre-processed point cloud data of the roof during tunneling of the tunneling equipment, obtain the tunneling section roof safety assessment index, and issue an early warning for over-limit tunneling of the tunneling working face. The tunneling section roof safety assessment module 2 includes a tunneling section point cloud data parsing submodule 21, a suspended roof size analysis submodule 22, and a roof safety assessment submodule 23. The tunneling section point cloud data parsing submodule 21 is connected to the data preprocessing submodule 16, the tunneling section point cloud data parsing submodule 21 is connected to the suspended roof size analysis submodule 22, and the suspended roof size analysis submodule 22 is connected to the roof safety assessment submodule 23. The roof safety assessment submodule 23 is connected to the tunnel safety assessment response feedback module 5.

[0071] The excavation working section point cloud data analysis submodule 21 receives the point cloud data provided by the data preprocessing submodule 16, selects the front end, left side, and right edge point cloud data of the roof of the coal mine tunnel excavation working face and the anchor point cloud data of the front row, and connects the above data in a clockwise or counterclockwise direction to form a closed polygonal area, thereby obtaining the exposed contour data of the suspended roof of the excavation working face.

[0072] The overhang size analysis submodule 22 analyzes the exposed contour data of the overhang of the excavation working face processed by the excavation working section point cloud data analysis submodule 21 to obtain the length L of the overhang portion of the tunnel after the excavation equipment has excavated.

[0073] The roof safety evaluation submodule 23 analyzes the size data of the exposed roof range processed by the tunneling working section point cloud data analysis submodule 21, calculates the ratio S1 of the difference between the length of the tunnel hanging roof part and the design parameter and the design parameter, and determines whether the hanging roof range of the tunneling working section meets the design requirements; the calculation formula is: S1 = |(LL d ) / L d |, where L d Design length for the suspended roof part of the tunnel.

[0074] like Figure 5 As shown, the tunneling section safety assessment module 3 is used to perform real-time analysis and calculation of the pre-processed point cloud data of the anchor bolt support, anchor cable support, and anchor mesh support in the tunneling section to obtain tunneling section safety assessment indicators and issue early warnings for insufficient support or excessive construction range in the tunneling section. The module includes a tunneling section point cloud data analysis submodule 31, an anchor bolt support quality assessment submodule 32, an anchor cable support quality assessment submodule 33, and an anchor mesh support quality assessment submodule 34. The excavation impact section point cloud data analysis submodule 31 is connected to the data preprocessing submodule 16; the excavation impact section point cloud data analysis submodule 31 is respectively connected to the anchor support quality evaluation submodule 32, the anchor cable support quality evaluation submodule 33 and the anchor net support quality evaluation submodule 34; the anchor support quality evaluation submodule 32, the anchor cable support quality evaluation submodule 33 and the anchor net support quality evaluation submodule 34 are respectively connected to the tunnel safety evaluation response feedback module 5.

[0075] The excavation impact section point cloud data analysis submodule 31 receives the point cloud data provided by the data preprocessing submodule 16, numbers the anchor rods and anchor cables that complete all the support work of the tunnel, accurately locates the three-dimensional coordinates of each anchor rod and anchor cable, accurately identifies the position coordinates of the intersection points of the anchor network grid, and forms anchor network contour data to be transmitted to the anchor rod support quality evaluation submodule 32, the anchor cable support quality evaluation submodule 33 and the anchor network support quality evaluation submodule 34.

[0076] The anchor support quality evaluation submodule 32 analyzes and processes the numbered anchor point cloud data provided by the tunneling impact section point cloud data analysis submodule 31, and calculates the actual spacing d of each anchor. i左 d i右 and actual row spacing d i前 d i后 And find the distance d between it and the designi间 d i排 The difference between △d i左间 , △d i右间 , △d i前排 , △d i后排 , and then calculate the average spacing difference △d of a single anchor i =(△d i左间 +△d i右间 +△d i前排 +△d i后排 ) / 4, and finally calculate the maximum value of the difference between the spacing of all anchors in the reinforced support section and the design size S2=max(△d i ) is used as the basis for judging the quality evaluation of anchor support in the excavation impact section.

[0077] The anchor cable support quality evaluation submodule 33 analyzes and processes the numbered anchor cable point cloud data provided by the tunneling impact section point cloud data analysis submodule 31, and calculates the actual spacing d of each anchor cable. j左 d j右 and actual row spacing d j前 d j后 And find the distance d between it and the design j间 d j排 The difference between △d j左间 , △d j右间 , △d j前排 , △d j后排 , and then calculate the average spacing difference △d of a single anchor cable j =(△d j左间 +△d j右间 +△d j前排 +△d j后排 ) / 4, and finally calculate the maximum value of the difference between the spacing of all anchor cables in the reinforced support section and the design size S3=max(△d j ) is used as the basis for judging the quality evaluation of anchor cable support in the excavation affected section.

[0078] The anchor net support quality evaluation submodule 34 analyzes and processes the tunnel contour data and anchor net contour data provided by the reinforced support section point cloud data analysis submodule, and calculates the tunnel roof contour area S 顶 and the area S of the anchor net laid on the tunnel roof 网 , and obtain the anchor net laying index S4 of the reinforced support section roadway = (S 顶 -S 网 ) / S 网 It serves as the basis for evaluating the quality of anchor net support in the strengthened support section.

[0079] like Figure 6As shown, the mining influence section safety evaluation module 4 is used to perform real-time analysis and calculation on the pre-processed anchor support point cloud data, anchor cable support point cloud data, anchor net support point cloud data, anchor stress meter 40 data, anchor cable stress meter 50 data and roof delamination meter 60 data of the mining influence section to obtain the mining influence section safety evaluation index; the mining influence section safety evaluation module 4 includes a mining influence section point cloud data analysis submodule 41, an anchor support abnormality evaluation submodule 42, an anchor cable support abnormality evaluation submodule 43, an anchor net support abnormality evaluation submodule 44 and a roof delamination abnormality evaluation submodule 45. The mining impact section point cloud data analysis submodule 41 is connected to the data preprocessing submodule 16; the mining impact section point cloud data analysis submodule 41 is respectively connected to the anchor support abnormality evaluation submodule 42, the anchor cable support abnormality evaluation submodule 43, the anchor net support abnormality evaluation submodule 44 and the roof separation abnormality evaluation submodule 45; the anchor support abnormality evaluation submodule 42, the anchor cable support abnormality evaluation submodule 43, the anchor net support abnormality evaluation submodule 44 and the roof separation abnormality evaluation submodule 45 are respectively connected to the tunnel safety evaluation response feedback module 5.

[0080] The mining influence section point cloud data analysis submodule 41 receives the three-dimensional point cloud and numbering data of the anchor rods, anchor cables, and anchor nets in the tunneling influence section point cloud data analysis submodule 31 as the original data of the tunnel support equipment, receives the three-dimensional point cloud data, anchor rod stress gauge 40 data, anchor cable stress gauge 50 data, and roof delamination data provided by the data preprocessing submodule 16 as the real-time support status data of the anchoring material, and analyzes and organizes the three-dimensional point cloud data of the anchor rods, anchor cables, and anchor nets, the anchor rod stress gauge 40 data, anchor cable stress gauge 50 data, and roof delamination data into a data set consistent with the anchoring material number provided by the tunneling influence section point cloud data analysis submodule 31; by comparing the changes in the anchor rods, anchor cables, anchor nets and roof delamination during the tunnel mining process, dynamic evaluation and real-time monitoring of the tunnel anchoring material support quality are achieved.

[0081] The anchor support abnormality evaluation submodule 42 receives the initial horizontal position parameter d of the anchor provided by the mining impact segment point cloud data analysis submodule 41. i左间 d i右间 d i前排 d i后排 and vertical height coordinate z i , and obtain in real time the horizontal position parameter d of the roadway anchor in the state of mining disturbance during the mining process of the coal mine working face i左间 '、d i右间 '、d i前排 '、d i后排 ', vertical height coordinate z i ' and the anchor stress gauge 40 data, and then calculate the real-time horizontal position difference △d of the anchor i左间 '=|di左间 '-d i左间 |, △d i右间 '=|d i右间 '-d i右间 |, △d i前排 '=|d i前排 '-d i前排 |, △d i后排 '=|d i后排 '-d i后排 | and vertical height parameter difference △z i =|z i -z i '|, calculate the average spacing difference △d of a single anchor i '=(△d i左间 '+△d i右间 '+△d i前排 '+△d i后排 ') / 4, and then calculate the anchor stress value F i The difference between F0 and the original rock stress △F i =|F i -F0|, and finally calculate the maximum change value S5=max[(△d i '+△z i ) / (2d i间 +2d i排 )+(△F i / F0)] as the basis for judging the abnormal evaluation of anchor support in the mining-affected section;

[0082] The anchor support abnormality evaluation submodule 43 receives the initial horizontal position parameter d of the anchor provided by the mining impact segment point cloud data analysis submodule 41. j左间 d j右间 d j前排 d j后排 and vertical height coordinate z j , and obtain in real time the horizontal position parameter d of the tunnel anchor cable under the mining disturbance state during the mining process of the coal mine working face j左间 '、d j右间 '、d j前排 '、d j后排 ', vertical height coordinate z j ' and the anchor cable stress gauge 50 data, and then calculate the real-time horizontal position difference △d of the anchor cable j左间 '=|d j左间 '-d j左间 |, △d j右间 '=|d j右间 '-d j右间 |, △d j前排 '=|d j前排 '-d j前排|, △d j后排 '=|d j后排 '-d j后排 | and vertical height parameter difference △z j =|z j -z j '|, calculate the average spacing difference △d of a single anchor cable j '=(△d j左间 '+△d j右间 '+△d j前排 '+△d j后排 ') / 4, and then calculate the anchor stress value F j The difference between F0 and the original rock stress △F j =|F j -F0|, and finally calculate the maximum change value of all anchor cables in the mining influence section S6=max[(△d j '+△z j ) / (2d j间 +2d j排 )+(△F j / F0)] is used as the basis for judging the abnormal evaluation of anchor cable support in the mining-affected section.

[0083] The anchor net support abnormality evaluation submodule 44 receives the tunnel roof contour area S provided by the mining impact segment point cloud data analysis submodule 41. 顶 and the area S of the anchor net laid on the tunnel roof 网 , and obtain in real time the area S of the anchor net under the disturbance state during the mining process of the coal mine working face 网 ', and obtain the abnormal index of the roadway anchor net support under the mining disturbance state S7=(S 顶 -S 网 ') / S 网 It serves as the basis for evaluating the abnormality of anchor net support in the mining-affected section.

[0084] The roof separation abnormality evaluation submodule 45 is to receive the roadway roof separation value S provided by the mining impact segment point cloud data analysis submodule 41. i , and obtain the abnormal index of roadway roof separation under mining disturbance state S8=S i It serves as the basis for evaluating the abnormal roof separation in the mining-affected section.

[0085] like Figure 7As shown, the tunnel safety evaluation response feedback module 5 is respectively connected to the roof safety evaluation submodule 23, the anchor support quality evaluation submodule 32, the anchor cable support quality evaluation submodule 33, the anchor net support quality evaluation submodule 34, the anchor support abnormality evaluation submodule 42, the anchor cable support abnormality evaluation submodule 43, the anchor net support abnormality evaluation submodule 44, and the roof separation abnormality evaluation submodule 45, and is used to provide signal feedback based on the evaluation indicators of each stage provided by the excavation working section roof safety evaluation module 2, the excavation impact section safety evaluation module 3, and the mining impact section safety evaluation module 4, and to issue danger warnings for areas with excessive roof suspension distance, insufficient support, support failure, and obvious separation, so as to remind the construction team to make timely reinforcement. Specifically, the following steps are included:

[0086] Step 1: Use 10*(1-S1) as the score of the roof safety quality of the excavation working section. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued, the excavation work will be stopped, the staff will be evacuated, and support will be strengthened; if the score is qualified, a reminder will be given, the excavation work will be stopped, and the next support work will be carried out; if the score is excellent, no reminder will be given.

[0087] Step 2: Use 10-S2 as the score for the anchor support quality; for scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and reinforced support will be carried out; if the score is qualified, the staff will be reminded to pay attention to the roof activities in the relevant area; if the score is excellent, no reminder will be given.

[0088] Step 3. Use 10-S3 as the score for the anchor support quality; for scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and reinforced support will be carried out; if the score is qualified, the staff will be reminded to pay attention to the roof activities in the relevant area; if the score is excellent, no reminder will be given.

[0089] Step 4: Use 10*(1-S4) as the score of the anchor net support quality. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and an anchor net will be laid on the part with a void top; if the score is qualified, the staff will be reminded to check the working status of the anchor net and replace the part with a leak or damage; if the score is excellent, no reminder will be given.

[0090] Step 5. Use 10-S5 as the score for the anchor support quality of the mining-affected section. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and the anchors with obvious displacement will be replaced or reinforced; if the score is qualified, the staff will be reminded to check the working status of the corresponding anchors and reinforce them in time; if the score is excellent, no reminder will be given.

[0091] Step 6. Use 10-S6 as the score for the anchor cable support quality of the mining-affected section. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and the anchor cables with obvious displacement will be replaced or reinforced; if the score is qualified, the staff will be reminded to check the working status of the corresponding anchor cables and reinforce them in time; if the score is excellent, no reminder will be given.

[0092] Step 7. Use 10*(1-S7) as the score of the anchor net support quality in the mining-affected section; for scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and additional anchor nets will be added to the anchor net area damaged by the mining; if the score is qualified, the staff will be reminded to check the working status of the anchor net and repair it in real time; if the score is excellent, no reminder will be given.

[0093] Step 8: Use S8 as the score to judge the amount of roof separation in the mining-affected section. If the abnormal index S8 of the roadway roof separation is less than or equal to 50mm, the score is 10 points, and the roof separation is within a reasonable range and no special treatment is required. If the abnormal index S8 of the roadway roof separation is greater than 50mm and less than or equal to 80mm, the score is 9 points, and the roof separation exceeds the reasonable limit, and the staff needs to be reminded to strengthen support. If the abnormal index S8 of the roadway roof separation is greater than 80mm and less than or equal to 150mm, the score is 8 points, and the roof separation is obviously abnormal, and it is necessary to report to the mine chief engineer, analyze the cause of the separation, and formulate measures. If the abnormal index S8 of the roadway roof separation is greater than 150mm, the score is 7 points, and the roof separation is occurring, and the relevant staff of the roadway must be evacuated immediately, and special measures must be formulated to deal with it.

[0094] Step 9. Select the sum of all scores in steps 1 to 8 as the final score of the coal mine tunnel safety evaluation. If the total score is in the range of 0-60, 60-70, or 70-80, the coal mine tunnel safety evaluation is unqualified, qualified, or excellent.

[0095] Through the above process, intelligent evaluation of coal mine tunnel safety and intelligent early warning of each stage of tunnel excavation can be realized, realizing comprehensive, real-time and accurate real-time monitoring and dynamic evaluation under rapid excavation conditions.

[0096] The present invention further discloses a method for intelligently evaluating the safety of coal mine tunnels, comprising the following steps:

[0097] S1: During the tunnel excavation process, the laser radar sensor 20 installed on the excavation equipment is used to scan the tunnel information and tunnel support materials, obtain three-dimensional point cloud data and number the anchor materials; during the tunnel mining process, the laser radar sensor 20 installed on the monorail crane 30 is used to scan the tunnel information and tunnel support materials, obtain three-dimensional point cloud data and correspond it to the number of the anchor materials, use the anchor stress gauge 40 and anchor stress gauge 50 installed on the anchor rods and anchor cables to monitor the stress values ​​of the anchor rods and anchor cables, and use the roof delamination meter 60 installed on the tunnel roof to monitor the delamination amount of the tunnel roof.

[0098] S2: Select the three-dimensional point cloud data of the excavation working section, calculate the safety index of the excavation empty top size, and provide the evaluation index to the tunnel safety evaluation response feedback module 5 for real-time monitoring and feedback.

[0099] S3: Select the three-dimensional point cloud data of the tunneling affected section, calculate the anchor material support quality index of the tunneling affected section, and provide the evaluation index to the tunnel safety evaluation response feedback module 5 for real-time monitoring and feedback.

[0100] S4: Select the three-dimensional point cloud data, anchor stress value, anchor cable stress and roof separation of the mining-affected section, calculate the anchor material support quality index of the mining-affected section, and provide the evaluation index to the tunnel safety evaluation response feedback module 5 for real-time monitoring and feedback.

[0101] S5: Based on the evaluation indicators provided at each stage, conduct a comprehensive score and comprehensive evaluation of the roadway safety, and finally obtain the coal mine roadway safety evaluation level.

[0102] The above description of the disclosed embodiments will enable one skilled in the art to implement and use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent evaluation model for coal mine tunnel safety, characterized by: It includes a data acquisition and preprocessing module (1), a tunneling working section roof safety evaluation module (2), a tunneling influence section safety evaluation module (3), a mining influence section safety evaluation module (4), and a tunnel safety evaluation response feedback module (5); The data acquisition and preprocessing module (1) is respectively connected to the excavation working section roof safety evaluation module (2), the excavation influence section safety evaluation module (3), and the mining influence section safety evaluation module (4), and is used to obtain relevant point cloud data of the excavation roadway roof profile, anchor net profile, anchor rod position, anchor cable position, as well as anchor rod stress, number, anchor cable stress, number, roadway roof delamination amount, delamination meter position data for preprocessing, and transmit them to the excavation working section roof safety evaluation module (2), the excavation influence section safety evaluation module (3), and the mining influence section safety evaluation module (4); The tunneling section roof safety evaluation module (2) is used to perform real-time analysis and calculation on the pre-processed point cloud data of the roof during tunneling of the tunneling equipment to obtain a tunneling section roof safety evaluation index; The tunneling influence section safety evaluation module (3) is used to perform real-time analysis and calculation on the pre-processed anchor support point cloud data, anchor cable support point cloud data and anchor net support point cloud data of the tunneling influence section to obtain a tunneling influence section safety evaluation index; The mining-affected section safety evaluation module (4) is used to perform real-time analysis and calculation on the pre-processed anchor support point cloud data, anchor cable support point cloud data, anchor net support point cloud data, anchor stress meter (40) data, anchor cable stress meter (50) data and roof separation meter (60) data of the mining-affected section to obtain a mining-affected section safety evaluation index; The tunnel safety evaluation response feedback module (5) is respectively connected to the tunneling working section roof safety evaluation module (2), the tunneling influence section safety evaluation module (3), and the mining influence section safety evaluation module (4), and is used to provide signal feedback based on the evaluation indicators of each stage provided by the tunneling working section roof safety evaluation module (2), the tunneling influence section safety evaluation module (3), and the mining influence section safety evaluation module (4), and to issue a danger warning for areas with excessively large hanging roof distance, insufficient support, failed support, and obvious separation, so as to remind the construction team to make timely reinforcement.

2. The intelligent evaluation model for coal mine tunnel safety according to claim 1, characterized in that: The data acquisition and preprocessing module (1) comprises a tunneling machinery laser radar data acquisition submodule (11), a rail vehicle laser radar data acquisition submodule (12), an anchor stress gauge data acquisition submodule (13), an anchor cable stress gauge data acquisition submodule (14), a roof separation instrument data acquisition submodule (15), and a data preprocessing submodule (16); the tunneling machinery laser radar data acquisition submodule (11), the rail vehicle laser radar data acquisition submodule (12), the anchor stress gauge data acquisition submodule (13), the anchor cable stress gauge data acquisition submodule (14), and the roof separation instrument data acquisition submodule (15) are respectively connected to the data preprocessing submodule (16), and the data preprocessing submodule (16) is respectively connected to the tunneling working section roof safety evaluation module (2), the tunneling influence section safety evaluation module (3), and the mining influence section safety evaluation module (4); The tunneling section roof safety evaluation module (2) comprises a tunneling section point cloud data parsing submodule (21), a suspended roof size analysis submodule (22), and a roof safety evaluation submodule (23); the tunneling section point cloud data parsing submodule (21) is connected to a data preprocessing submodule (16); the tunneling section point cloud data parsing submodule (21) is connected to a suspended roof size analysis submodule (22); the suspended roof size analysis submodule (22) is connected to a roof safety evaluation submodule (23); the roof safety evaluation submodule (23) is connected to a tunnel safety evaluation response feedback module (5); The tunneling influence section safety evaluation module (3) includes a tunneling influence section point cloud data parsing submodule (31), an anchor support quality evaluation submodule (32), an anchor cable support quality evaluation submodule (33), and an anchor net support quality evaluation submodule (34); the tunneling influence section point cloud data parsing submodule (31) is connected to the data preprocessing submodule (16); the tunneling influence section point cloud data parsing submodule (31) is respectively connected to the anchor support quality evaluation submodule (32), the anchor cable support quality evaluation submodule (33), and the anchor net support quality evaluation submodule (34); the anchor support quality evaluation submodule (32), the anchor cable support quality evaluation submodule (33), and the anchor net support quality evaluation submodule (34) are respectively connected to the tunnel safety evaluation response feedback module (5); The mining influence section safety evaluation module (4) includes a mining influence section point cloud data parsing submodule (41), an anchor support abnormality evaluation submodule (42), an anchor cable support abnormality evaluation submodule (43), an anchor net support abnormality evaluation submodule (44) and a roof separation abnormality evaluation submodule (45); the mining influence section point cloud data parsing submodule (41) is connected to the data preprocessing submodule (16); the mining influence section point cloud data parsing submodule (41) is respectively connected to the anchor support abnormality evaluation submodule (42), the anchor cable support abnormality evaluation submodule (43), the anchor net support abnormality evaluation submodule (44) and the roof separation abnormality evaluation submodule (45); the anchor support abnormality evaluation submodule (42), the anchor cable support abnormality evaluation submodule (43), the anchor net support abnormality evaluation submodule (44) and the roof separation abnormality evaluation submodule (45) are respectively connected to the tunnel safety evaluation response feedback module (5).

3. The intelligent evaluation model for coal mine tunnel safety according to claim 2, characterized in that: The tunneling machinery laser radar data acquisition submodule (11) is a laser radar sensor (20) installed on the tunneling equipment (10), which is used to scan the tunnel information including the exposed range contour of the roof, the shielding contour of the shielding beam, the contour of the anchor rod and anchor cable, the contour of the anchor net, and the contour of the steel belt during the tunnel support process, and obtain three-dimensional point cloud data in the absolute coordinate system of the earth; The rail vehicle laser radar data acquisition submodule (12) is a laser radar sensor (20) installed on the rail vehicle, which is used to perform normalized scanning of the tunnel support material and obtain three-dimensional point cloud data in the earth's absolute coordinate system; The anchor stress meter data acquisition submodule (13) is an anchor stress meter (40) installed on the tunnel surrounding rock anchor, which is used to record the working state of the anchor and obtain the corresponding numbered anchor working resistance data; The anchor cable stress meter data acquisition submodule (14) is installed on the anchor cable stress meter (50) on the tunnel surrounding rock anchor cable, and is used to record the working state of the anchor cable and obtain the working resistance data of the corresponding numbered anchor cable; The roof separation meter data acquisition submodule (15) is a roof separation meter (60) installed on the roadway roof, which is used to monitor the separation position and separation amount of the roof at different depths and obtain the roof separation amount at the corresponding roadway position; The data preprocessing submodule (16) is used to set scanning parameters for the three-dimensional point cloud data of the tunnel support equipment and support parameters acquired by the tunneling machinery laser radar data acquisition submodule (11) and the rail vehicle laser radar data acquisition submodule (12), and to eliminate redundant data through noise reduction processing, and to perform segmented processing on the support point cloud data of different support stages, and to respectively acquire point cloud data of the tunneling working section, the tunneling influence section, and the mining influence section; the type of the point cloud data is the XYZ three-dimensional coordinates and echo intensity value of the target unit.

4. The intelligent evaluation model for coal mine tunnel safety according to claim 3, characterized in that: The excavation working section point cloud data parsing submodule (21) receives the point cloud data provided by the data preprocessing submodule (16), selects the point cloud data of the front end, left side, and right side edges of the roof of the coal mine tunnel excavation working face, and the point cloud data of the anchor rods in the front row, and sequentially connects the above data in a clockwise or counterclockwise direction to form a closed polygonal area, thereby obtaining the contour data of the exposed roof of the excavation working face; The overhanging roof size analysis submodule (22) analyzes the exposed contour data of the overhanging roof of the excavation working face processed by the excavation working section point cloud data analysis submodule (21) to obtain the length L of the overhanging roof portion of the tunnel after the excavation equipment has excavated; The roof safety evaluation submodule (23) analyzes the size data of the exposed range of the roof after being processed by the tunneling working section point cloud data analysis submodule (21), calculates the length of the tunnel suspended roof part and the ratio S1 of the difference between the design parameters and the design parameters, and judges whether the suspended roof range of the tunneling working section meets the design requirements; the calculation formula is: S1=|(LL d ) / L d |, where L d Design length for the suspended roof part of the tunnel.

5. The intelligent evaluation model for coal mine tunnel safety according to claim 4, characterized in that: The tunneling impact section point cloud data parsing submodule (31) receives the point cloud data provided by the data preprocessing submodule (16), performs numbering processing on the anchor rods and anchor cables that complete all the tunnel support work, accurately locates the three-dimensional coordinates of each anchor rod and anchor cable, accurately identifies the position coordinates of the intersection points of the anchor network grid, and forms the anchor network contour data; The anchor support quality evaluation submodule (32) analyzes and processes the numbered anchor point cloud data provided by the tunneling impact section point cloud data analysis submodule (31), and calculates the actual spacing d of each anchor. i左 d i右 and actual row spacing d i前 d i后 And find the distance d between it and the design i间 d i排 The difference between △d i左间 , △d i右间 , △d i前排 , △d i后排 , and then calculate the average spacing difference △d of a single anchor i =(△d i左间 +△d i右间 +△d i前排 +△d i后排 ) / 4, and finally calculate the maximum value of the difference between the spacing of all anchors in the reinforced support section and the design size S2=max(△d i ) as the basis for judging the quality evaluation of anchor support in the tunneling affected section; The anchor cable support quality evaluation submodule (33) analyzes and processes the numbered anchor cable point cloud data provided by the tunneling impact section point cloud data analysis submodule (31), and calculates the actual spacing d of each anchor cable. j左 d j右 and actual row spacing d j前 d j后 And find the distance d between it and the design j间 d j排 The difference between △d j左间 , △d j右间 , △d j前排 , △d j后排 , and then calculate the average spacing difference △d of a single anchor cable j =(△d j左间 +△d j右间 +△d j前排 +△d j后排 ) / 4, and finally calculate the maximum value of the difference between the spacing of all anchor cables in the reinforced support section and the design size S3=max(△d j ) as the basis for judging the quality evaluation of anchor cable support in the excavation-affected section; The anchor net support quality evaluation submodule (34) analyzes and processes the tunnel contour data and anchor net contour data provided by the reinforced support section point cloud data analysis submodule, and calculates the tunnel roof contour area S respectively. 顶 and the area S of the anchor net laid on the tunnel roof 网 , and obtain the anchor net laying index S4 of the reinforced support section roadway = (S 顶 -S 网 ) / S 网 It serves as the basis for evaluating the quality of anchor net support in the strengthened support section.

6. The intelligent evaluation model for coal mine tunnel safety according to claim 5, characterized in that: The mining influence segment point cloud data parsing submodule (41) receives the three-dimensional point cloud and number data of the anchor rods, anchor cables, and anchor nets from the tunneling influence segment point cloud data parsing submodule (31) as the original data of the tunnel support equipment, receives the three-dimensional point cloud data, anchor rod stress meter (40) data, anchor cable stress meter (50) data, and roof separation amount provided by the data preprocessing submodule (16) as the real-time support status data of the anchor material, and analyzes and organizes the three-dimensional point cloud data of the anchor rods, anchor cables, and anchor nets, the anchor rod stress meter (40) data, anchor cable stress meter (50) data, and roof separation amount into a data set consistent with the anchor material number provided by the tunneling influence segment point cloud data parsing submodule (31); and realizes dynamic evaluation and real-time monitoring of the tunnel anchor material support quality by comparing the changes of the anchor rods, anchor cables, anchor nets, and roof separation during the tunnel mining process; The anchor support abnormality evaluation submodule (42) is provided by receiving the initial horizontal position parameter d of the anchor provided by the mining impact segment point cloud data analysis submodule (41). i左间 d i右间 d i前排 d i后排 and vertical height coordinate z i , and obtain in real time the horizontal position parameter d of the roadway anchor in the state of mining disturbance during the mining process of the coal mine working face i左间 '、d i右间 '、d i前排 '、d i后排 ', vertical height coordinate z i ' and the anchor stress meter (40) data, and then calculate the real-time horizontal position difference △d of the anchor i左间 '=|d i左间 '-d i左间 |, △d i右间 '=|d i右间 '-d i右间 |, △d i前排 '=|d i前排 '-d i前排 |, △d i后排 '=|d i后排 '-d i后排 | and vertical height parameter difference △z i =|z i -z i '|, calculate the average spacing difference △d of a single anchor i '=(△d i左间 '+△d i右间 '+△d i前排 '+△d i后排 ') / 4, and then calculate the anchor stress value F i The difference between F0 and the original rock stress △F i =|F i -F0|, and finally calculate the maximum change value S5=max[(△d i '+△z i ) / (2d i间 +2d i排 )+(△F i / F0)] as the basis for judging the abnormal evaluation of anchor support in the mining-affected section; The anchor support abnormality evaluation submodule (43) is provided by receiving the initial horizontal position parameter d of the anchor provided by the mining impact segment point cloud data analysis submodule (41). j左间 d j右间 d j前排 d j后排 and vertical height coordinate z j , and obtain in real time the horizontal position parameter d of the tunnel anchor cable under the mining disturbance state during the mining process of the coal mine working face j左间 '、d j右间 '、d j前排 '、d j后排 ', vertical height coordinate z j ' and the anchor cable stress gauge (50) data, and then calculate the real-time horizontal position difference △d of the anchor cable j左间 '=|d j左间 '-d j左间 |, △d j右间 '=|d j右间 '-d j右间 |, △d j前排 '=|d j前排 '-d j前排 |, △d j后排 '=|d j后排 '-d j后排 | and vertical height parameter difference △z j =|z j -z j '|, calculate the average spacing difference △d of a single anchor cable j '=(△d j左间 '+△d j右间 '+△d j前排 '+△d j后排 ') / 4, and then calculate the anchor stress value F j The difference between F0 and the original rock stress △F j =|F j -F0|, and finally calculate the maximum change value of all anchor cables in the mining influence section S6=max[(△d j '+△z j ) / (2d j间 +2d j排 )+(△F j / F0)] as the basis for judging abnormal evaluation of anchor cable support in mining-affected sections; The anchor net support abnormality evaluation submodule (44) is formed by receiving the tunnel roof contour area S provided by the mining impact segment point cloud data analysis submodule (41). 顶 and the area S of the anchor net laid on the tunnel roof 网 , and obtain in real time the area S of the anchor net under the disturbance state during the mining process of the coal mine working face 网 ', and obtain the abnormal index of the roadway anchor net support under the mining disturbance state S7=(S 顶 -S 网 ') / S 网 As the basis for evaluating the abnormality of anchor net support in mining-affected sections; The roof separation abnormality evaluation submodule (45) is provided by receiving the roadway roof separation amount S provided by the mining impact segment point cloud data analysis submodule (41). i , and obtain the abnormal index of roadway roof separation under mining disturbance state S8=S i It serves as the basis for evaluating the abnormal roof separation in the mining-affected section.

7. The intelligent evaluation model for coal mine tunnel safety according to claim 6, characterized in that: The tunnel safety evaluation response feedback module (5) can provide signal feedback based on the evaluation indicators of each stage provided by each evaluation module, and issue a danger warning for areas with excessive overhead distance, insufficient support, failed support, and excessive separation, so as to remind the construction team to carry out timely reinforcement, including the following steps: Step 1: Use 10*(1-S1) as the score of the roof safety quality of the excavation working section. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued, the excavation work will be stopped, the staff will be evacuated, and support will be strengthened; if the score is qualified, a reminder will be issued, the excavation work will be stopped, and the next support work will be carried out; if the score is excellent, no reminder will be given; Step 2: Use 10-S2 as the score for the anchor support quality. Scores of 0-8, 8-9, and 9-10 are rated as unqualified, qualified, and excellent, respectively. If the score is unqualified, an immediate warning is issued and reinforced support is carried out; if the score is qualified, the staff is reminded to pay attention to the roof movement in the relevant area; if the score is excellent, no reminder is given; Step 3: Use 10-S3 as the score for the anchor cable support quality. Scores of 0-8, 8-9, and 9-10 are rated as unqualified, qualified, and excellent, respectively. If the score is unqualified, an immediate warning is issued and reinforced support is carried out; if the score is qualified, the staff is reminded to pay attention to the roof movement in the relevant area; if the score is excellent, no reminder is given; Step 4: Use 10*(1-S4) as the score of the anchor net support quality. For scores of 0-8, 8-9, and 9-10, give unqualified, qualified, and excellent scores respectively. If the score is unqualified, an immediate warning will be issued and the anchor net will be laid on the part with a void top. If the score is qualified, the staff will be reminded to check the working status of the anchor net and replace the part with a leak or damage. If the score is excellent, no reminder will be given. Step 5: Use 10-S5 as the score for the anchor support quality of the mining-affected section. Scores of 0-8, 8-9, and 9-10 are assigned as unqualified, qualified, and excellent, respectively. If the score is unqualified, an immediate warning is issued and anchors with obvious displacement are replaced or reinforced. If the score is qualified, the staff is reminded to check the working status of the corresponding anchors and reinforce them in a timely manner. If the score is excellent, no reminder is given. Step 6: Use 10-S6 as the score for the anchor cable support quality of the mining-affected section. Scores of 0-8, 8-9, and 9-10 are assigned as unqualified, qualified, and excellent, respectively. If the score is unqualified, an immediate warning is issued and the anchor cables with obvious displacement are replaced or reinforced. If the score is qualified, the staff is reminded to check the working status of the corresponding anchor cables and reinforce them in a timely manner. If the score is excellent, no reminder is given. Step 7: Use 10*(1-S7) as the score of the anchor net support quality in the mining-affected section. Scores of 0-8, 8-9, and 9-10 are respectively given as unqualified, qualified, and excellent. If the score is unqualified, an immediate warning is issued and additional anchor nets are added to the anchor net area damaged by mining. If the score is qualified, the staff is reminded to check the working status of the anchor net and repair it in real time. If the score is excellent, no reminder is given. Step 8. Use S8 as the score for judging the roof separation amount of the mining-affected section. If the abnormal index S8 of the roadway roof separation is less than or equal to 50mm, the score is 10 points, and the roof separation amount is within a reasonable range and no special treatment is required; if the abnormal index S8 of the roadway roof separation is greater than 50mm and less than or equal to 80mm, the score is 9 points, and the roof separation amount exceeds the reasonable limit, and the staff needs to be reminded to strengthen support; if the abnormal index S8 of the roadway roof separation is greater than 80mm and less than or equal to 150mm, the score is 8 points, and the roof separation amount is obviously abnormal, and it is necessary to report to the mine chief engineer, analyze the cause of the separation, and formulate measures; if the abnormal index S8 of the roadway roof separation is greater than 150mm, the score is 7 points, and the roof separation occurs, and the relevant staff of the roadway must be evacuated immediately and special measures must be formulated to deal with it; Step 9. Select the sum of all scores in steps 1 to 8 as the final score of the coal mine tunnel safety evaluation. If the total score is in the range of 0-60, 60-70, or 70-80, the coal mine tunnel safety evaluation is unqualified, qualified, or excellent.

8. A method for intelligently evaluating the safety of coal mine tunnels using the intelligent evaluation model for coal mine tunnel safety according to any one of claims 1 to 7, characterized in that: The following steps are involved: S1: During the tunneling process, a laser radar sensor (20) installed on the tunneling equipment is used to scan the tunnel information and tunnel support materials, obtain three-dimensional point cloud data and number the anchor materials; during the tunnel mining process, a laser radar sensor (20) installed on the rail train is used to scan the tunnel information and tunnel support materials, obtain three-dimensional point cloud data and correspond it with the number of the anchor materials, use the anchor stress gauge (40) and anchor stress gauge (50) installed on the anchor rod and anchor cable to monitor the stress value of the anchor rod and anchor cable, and use the roof separation meter (60) installed on the tunnel roof to monitor the separation amount of the tunnel roof; S2: Select the three-dimensional point cloud data of the excavation working section, calculate the safety index of the excavation empty top size, and provide the evaluation index to the tunnel safety evaluation response feedback module (5) for real-time monitoring and feedback; S3: Select the three-dimensional point cloud data of the tunneling affected section, calculate the anchor material support quality index of the tunneling affected section, and provide the evaluation index to the tunnel safety evaluation response feedback module (5) for real-time monitoring and feedback; S4: Select the three-dimensional point cloud data, anchor stress value, anchor cable stress and roof separation of the mining-affected section, calculate the anchor material support quality index of the mining-affected section, and provide the evaluation index to the tunnel safety evaluation response feedback module (5) for real-time monitoring and feedback; S5: Based on the evaluation indicators provided at each stage, conduct a comprehensive score and comprehensive evaluation of the roadway safety, and finally obtain the coal mine roadway safety evaluation level.

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