Intelligent evaluation method for local pressure relief and danger relief effect of rock burst

Abstract

The invention discloses an intelligent evaluation method for the local pressure relief and danger relief effect of rock burst, and relates to the field of mining engineering, and the method specifically comprises the following steps: S1, collecting torque data and rotating speed data measured by a rotating speed and torque sensor through a data collection instrument, and uploading the collected torque data and rotating speed data to a computer; s2, establishing a neural network model through a computer, operating the neural network model, and outputting an evaluation result of pressure relief and danger relief; the neural network model comprises a drill bit cutting parameter processing model, a coal body stress processing model and a pressure relief risk relieving evaluation model. According to the method, related drilling parameters can be obtained in real time through the neural network model established by the computer, and the coal stress can be calculated, so that the pressure relief and danger relieving effect is accurately evaluated, manual analysis is not needed, time and labor are saved, and time and labor are saved in time.

Description

Technical Field

[0001] The present invention relates to the field of mining engineering, and particularly to an intelligent evaluation method for the local pressure relief and danger elimination effect of rock bursts. Background Art

[0002] Rock burst is one of the most destructive disasters in coal mines. It can destroy the coal mining face, damage the roadway, cause a large number of casualties and huge economic losses, seriously threatening the safe production of coal mines. Conducting research on rock burst prevention and control is the guarantee for the safe production of coal mines.

[0003] In the prevention and control of coal mine rock bursts, local pressure relief is an important part of the danger elimination measures. Local pressure relief is to reduce the stress concentration degree in the coal body by taking certain measures, release or reduce the accumulated elastic energy, so as to slow down or eliminate the danger of rock bursts. Specifically, the large-diameter borehole pressure relief measure for coal body is the preferred pressure relief measure in rock burst mines. By constructing boreholes on the two sides or the floor of the roadway in the rock burst dangerous area, the integrity of the coal body structure is damaged, the stress state of the coal body is changed, and the accumulated strain energy in the coal body is slowly released, converting the sudden instability failure that may occur in the coal body into a slow progressive failure, eliminating or reducing the danger of rock bursts.

[0004] The pressure relief stress generated by local pressure relief is part of the coal body stress. Since it is difficult to obtain the pressure relief stress, the pressure relief stress can be indirectly reflected by measuring the coal body stress, and then the pressure relief and danger elimination effects can be evaluated. The necessary conditions for coal mine rock bursts are high stress and stress concentration in the coal body. Therefore, accurately measuring the coal body stress is the key to rock burst early warning and prevention. The most commonly used methods for measuring coal body stress are the stress online method and the drill cuttings method. The stress online method obtains the single-point stress values at the deep and shallow base points by monitoring the oil pressure change of the hydraulic oil bladder. The monitored data is the change value of the coal body stress rather than the real value, and its value is greatly affected by sensor installation, sensor structure stiffness, etc. The drill cuttings method uses the relationship between coal body stress and the amount of coal powder, and estimates the coal body stress through the amount of coal powder to obtain the equivalent stress at different depths of the borehole. Since it takes a certain time for the coal powder to be discharged from the bottom of the hole to the hole mouth, there is a deviation in the corresponding relationship between the coal powder collected at the hole mouth and the position of the drill bit at the bottom of the hole. It can be seen that the existing devices for measuring coal body stress have a great influence on the measurement results themselves, cannot collect and transmit real-time data, and thus cannot accurately measure the coal body stress. In addition, the existing monitoring and evaluation process for the local pressure relief and danger elimination effect requires manual analysis, which is time-consuming, laborious and not timely. Moreover, the existing coal body stress measurement methods only establish the relationship between a single drilling parameter and the coal body stress, without considering the correlation between drilling parameters. Summary of the Invention

[0005] The present invention provides an intelligent evaluation method for the effect of local pressure relief and danger relief of rock bursts, so as to solve the problems that the existing methods for measuring the stress of coal bodies cannot collect and transmit relevant real-time data, and the existing evaluation methods require manual analysis, which is time-consuming and laborious, and only establish the relationship between a single drilling parameter and the stress of coal bodies, thus indirectly or directly leading to inaccurate evaluation results.

[0006] The intelligent evaluation method for the effect of local pressure relief and danger relief of rock bursts of the present invention adopts the following technical solution: It includes measuring equipment, the measuring equipment includes a drilling rig, and the measuring equipment also includes a rotational speed and torque sensor for monitoring the torque data and rotational speed data of the drill bit, a data acquisition instrument communicatively connected to the rotational speed and torque sensor, and a computer communicatively connected to the data acquisition instrument; the rotational speed and torque sensor is installed on the output shaft of the drilling rig;

[0007] Specifically, it includes the following steps:

[0008] S1. The data acquisition instrument collects the torque data and rotational speed data measured by the rotational speed and torque sensor, and uploads the collected torque data and rotational speed data to the computer;

[0009] S2. The computer establishes a neural network model, runs the neural network model and outputs the evaluation result of pressure relief and danger relief;

[0010] The neural network model includes a drill bit cutting parameter processing model, a coal body stress processing model and a pressure relief and danger relief evaluation model; the operation of the neural network model includes the following steps:

[0011] S21. The drill bit cutting parameter processing model receives the torque data and rotational speed data, and obtains the coal body stress value according to the torque data and rotational speed data;

[0012] S22. The coal body stress processing model obtains the coal body stress concentration coefficient A according to the coal body stress value;

[0013] S23. The pressure relief and danger relief evaluation model uses the coal body stress concentration coefficient A to conduct a grading evaluation on the effect of pressure relief and danger relief.

[0014] Preferably, the drill bit cutting parameter processing model is established by analyzing the shape of the drill bit through the computer, and the drill bit cutting parameter processing model includes the calculation formula of coal body stress, as follows:

[0015]

[0016] In the formula: σ s is the coal body stress received by the borehole wall, n is the rotational speed of the drill bit, M ais the drill bit torque; m0 is the number of drill teeth, b0 is the drill tooth width, c0 is the cohesion of the coal body, R0 is the distance from the point of action of the drill bit cutting force to the center of the borehole, θ0 is the drill bit cutting angle, is the internal friction angle of the coal body, φ0 is the drill bit anti-drilling angle, and k is the influence coefficient of the drill bit rotation speed.

[0017] Preferably, the coal body stress treatment model includes a calculation formula for the coal body stress concentration coefficient A, as follows:

[0018]

[0019] Where A is the stress concentration coefficient of coal, σ max is the maximum value of coal body stress, σ0 is the average value of coal body stress;

[0020] The maximum value of the coal body stress is given by σ max The coal body stress is obtained by screening the maximum value from the coal body stress values ​​using the pre-established coal body stress treatment model; the average value σ0 of the coal body stress is calculated by averaging the coal body stress values ​​using the pre-established coal body stress treatment model.

[0021] Preferably, the pressure relief and emergency response assessment model is:

[0022] When A is less than 1.2, the pressure relief and emergency relief effect is evaluated as significantly effective;

[0023] When 1.2≤A≤1.5, the pressure relief and emergency relief effect is evaluated as generally effective;

[0024] When A>1.5, the pressure relief and emergency relief effect is evaluated as invalid.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. In the present invention, the speed torque sensor is installed on the output shaft of the drilling rig, which can monitor the drill speed and drill torque on the drilling rig in real time, and further derive the expression of the influence of the two data of the drill speed and the drill torque on the coal body stress, taking into account the correlation between the drilling parameters, so as to make the final evaluation result more accurate.

[0027] 2. In the present invention, the data acquisition instrument is communicatively connected with the speed torque sensor and the data acquisition instrument is communicatively connected with the computer. The established neural network model can realize timely analysis of the monitoring data, thereby reducing the test and analysis of relevant site and drill bit parameters, automatically processing the site data, and giving accurate pressure relief and hazard elimination evaluation results without relying on manual analysis. The whole process saves time and effort and is very intelligent. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying 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 accompanying drawings can be obtained based on these drawings.

[0029] Figure 1 This is the flowchart of the present invention.

[0030] Figure 2 This is the framework diagram of the neural network model of the present invention.

[0031] Figure 3 This is the framework diagram of the measuring device of the present invention. Detailed implementation manners

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. 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.

[0033] An embodiment of an intelligent evaluation method for the local pressure relief and danger relief effect of rock burst in the present invention, as Figure 1 and Figure 2 shown, includes a measuring device. The measuring device includes a drill, and the measuring device further includes a rotational speed and torque sensor for monitoring the torque data and rotational speed data of the drill bit, a data acquisition instrument communicatively connected to the rotational speed and torque sensor, and a computer communicatively connected to the data acquisition instrument; the rotational speed and torque sensor is installed on the output shaft of the drill.

[0034] Specifically, it includes the following steps:

[0035] S1. Collect the torque data and rotational speed data measured by the rotational speed and torque sensor through the data acquisition instrument, and upload the collected torque data and rotational speed data to the computer;

[0036] S2. Establish a neural network model through the computer, run the neural network model and output the evaluation result of pressure relief and danger relief;

[0037] The neural network model includes a drill bit cutting parameter processing model, a coal body stress processing model, and a pressure relief and danger relief evaluation model; the operation of the neural network model includes the following steps:

[0038] S21. The drill bit cutting parameter processing model receives the torque data and the rotational speed data, and obtains the coal body stress value according to the torque data and the rotational speed data;

[0039] S22. The coal body stress processing model obtains the coal body stress concentration coefficient A according to the coal body stress value;

[0040] S23. The pressure relief and danger relief evaluation model uses the coal body stress concentration coefficient A to conduct a hierarchical evaluation of the effect of pressure relief and danger relief.

[0041] It should be noted that the drill bit is connected to the drill rig through the output shaft of the drill rig.

[0042] It should be noted that the rotational speed and torque sensor is installed on the output shaft of the drill rig, and can collect the drill bit rotational speed data and the drill bit torque data while the drill rig is working. In this way, the monitored data are all true values, and their values are not affected by its own installation and structural stiffness, etc., achieving the purpose of full measurement, improving the sensitivity and accuracy of monitoring the coal body stress, and collecting the measurement results in real time and accurately uploading them to the computer.

[0043] In this embodiment, a drill bit cutting parameter processing model is established by analyzing the shape of the drill bit through the computer. The drill bit cutting parameter processing model includes the calculation formula for the coal body stress, as follows:

[0044]

[0045] In the formula: σ s is the coal body stress received by the borehole wall, n is the rotational speed of the drill bit, M a is the torque of the drill bit; m0 is the number of drill tooth rows of the drill bit, b0 is the width of the drill teeth of the drill bit, c0 is the cohesion of the coal body, R0 is the distance from the action point of the resultant cutting force of the drill bit to the center of the borehole, θ0 is the cutting angle of the drill bit, is the internal friction angle of the coal body, φ0 is the anti-drilling angle of the drill bit, and k is the influence coefficient of the drill bit rotational speed.

[0046] In this embodiment, the coal body stress processing model includes the calculation formula for the coal body stress concentration coefficient A, as follows:

[0047]

[0048] In the formula, A is the coal body stress concentration coefficient, σ max is the maximum value of the coal body stress, and σ0 is the average value of the coal body stress;

[0049] The maximum value of the coal body stress is obtained from σ maxIt is obtained by screening the maximum value from the coal body stress values by the pre-established coal body stress processing model; the average value σ0 of the coal body stress is calculated by taking the average value from the coal body stress values by the pre-established coal body stress processing model.

[0050] In this embodiment, it should be noted that the pre-established coal body stress processing model is used to screen out the maximum value from the coal body stress values and is also used to calculate the average value from the coal body stress values.

[0051] In this embodiment, the pressure relief and danger elimination evaluation model is as follows:

[0052] When A < 1.2, the evaluation of the pressure relief and danger elimination effect is significantly effective level;

[0053] When 1.2 ≤ A ≤ 1.5, the evaluation of the pressure relief and danger elimination effect is generally effective level;

[0054] When A > 1.5, the evaluation of the pressure relief and danger elimination effect is ineffective level.

[0055] In this embodiment, it should be noted that the stress concentration coefficient is a parameter used to describe the degree of local stress concentration. In the coal mine working scenario, it reflects the uneven degree of the stress distribution of the coal and rock mass around the borehole.

[0056] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent evaluation method for local pressure relief of rock burst, comprising a measuring device, wherein the measuring device comprises a drilling rig, characterized in that: The measuring device further comprises a speed torque sensor for monitoring the torque data and the speed data of the drill bit, a data acquisition device communicatively connected to the speed torque sensor, and a computer communicatively connected to the data acquisition device; the speed torque sensor is mounted on the output shaft of the drilling rig; The specific steps include: S1, collecting the torque data and the speed data measured by the speed torque sensor through the data acquisition instrument, and uploading the collected torque data and the speed data to the computer; S2. Establishing a neural network model through the computer, running the neural network model and outputting the evaluation result of pressure relief and crisis resolution; The neural network model includes a drill bit cutting parameter processing model, a coal body stress processing model and a pressure relief and emergency assessment model; the operation of the neural network model includes the following steps: S21, the drill bit cutting parameter processing model receives the torque data and the rotation speed data, and obtains a coal body stress value according to the torque data and the rotation speed data; S22, the coal body stress processing model obtains the coal body stress concentration coefficient A according to the coal body stress value; S23. The pressure relief and emergency relief evaluation model uses the coal body stress concentration coefficient A to perform graded evaluation on the effect of pressure relief and emergency relief.

2. The intelligent evaluation method for local pressure relief of rock burst according to claim 1 is characterized in that: The shape of the drill bit is analyzed by the computer to establish a drill bit cutting parameter processing model, and the drill bit cutting parameter processing model includes a calculation formula for coal body stress, as follows: Where: s is the coal stress on the borehole wall, n is the drill bit speed, M a is the drill bit torque; m0 is the number of drill teeth, b0 is the drill tooth width, c0 is the cohesion of the coal body, R0 is the distance from the point of action of the drill bit cutting force to the center of the borehole, θ0 is the drill bit cutting angle, is the internal friction angle of the coal body, φ0 is the drill bit anti-drilling angle, and k is the influence coefficient of the drill bit rotation speed.

3. The intelligent evaluation method for local pressure relief of rock burst according to claim 1 is characterized in that: The coal body stress treatment model includes a calculation formula for the coal body stress concentration coefficient A, which is as follows: Where A is the stress concentration coefficient of coal, σ max is the maximum value of coal body stress, σ0 is the average value of coal body stress; The maximum value of the coal body stress is given by σ max The coal body stress is obtained by screening the maximum value from the coal body stress values ​​using the pre-established coal body stress treatment model; the average value σ0 of the coal body stress is calculated by averaging the coal body stress values ​​using the pre-established coal body stress treatment model.

4. The intelligent evaluation method for local pressure relief of rock burst according to claim 1 is characterized in that: The pressure relief and hazard relief assessment model is: When A is less than 1.2, the pressure relief and emergency relief effect is evaluated as significantly effective; When 1.2≤A≤1.5, the pressure relief and emergency relief effect is evaluated as generally effective; When A>1.5, the pressure relief and emergency relief effect is evaluated as invalid.

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