Intelligent impact rock drilling while-drilling lithology identification system and identification method

Abstract

The invention discloses an intelligent impact rock drilling while-drilling lithology identification system and method, and belongs to the technical field of coal mining. The system comprises a front drill boom, an electrical unit, a hydraulic unit, an intelligent operation table, a data acquisition unit and a data processing unit, the electric unit and the hydraulic unit provide working power required by rock drilling construction; the intelligent operating platform controls the front drill boom to advance, swing and pitch; the data acquisition unit acquires propulsion pressure, impact pressure, rotation pressure, rotation speed and displacement signals in the construction process; the data processing unit stores and processes data; a reverse learning strategy and a self-adaptive t distribution strategy are used for improving a Tianying algorithm and optimizing and training a support vector machine model, then data collected by a data collection unit serve as input parameters, the optimized support vector machine model is input, an intensity prediction result is output, and real-time prediction of the tunnel face rock intensity in the drilling process is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of coal mining, and in particular relates to an intelligent impact rock drilling while drilling lithology identification system and method. Background Art

[0002] Since the beginning of the 21st century, in the face of a new round of energy technology revolution characterized by informatization and intelligence, the development of intelligent drilling technology and equipment is the general trend in order to reduce the number of underground construction personnel, achieve high production and efficiency, and complete the goals of mechanization, automation, and intelligence in coal mines. Due to the complex and diverse underground geological conditions and the different degrees of difficulty in coal and rock mining, it is still extremely difficult to apply advanced ground technology and equipment to underground coal mine construction, resulting in a slow progress in the intelligentization of underground tunnel excavation.

[0003] A rock drilling rig is a vehicle specially used for rock drilling and hole drilling operations. It has a stable chassis and a powerful power system. It is often used for excavation and drilling operations in underground engineering, tunnel engineering and other fields. At present, the rock drilling rig has a single function and insufficient intelligence. Workers are required to drive and carry out operations during the construction process, and the labor intensity of the workers is relatively high. With the advancement of coal mining methods and processes, the requirements for tunnel rigs are gradually increasing. At present, the rock properties of the surrounding rock of the face cannot be detected in real time, resulting in a single blasting parameter and a slow excavation speed. Therefore, it is urgent to improve the intelligence of the rock drilling rig and develop the rock property identification technology of the rock drilling rig to achieve efficient and rapid excavation of the mine. Summary of the invention

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide an intelligent impact drilling while drilling lithology identification system and method, which solves the problems in the prior art.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent impact rock drilling while drilling lithology identification system, comprising a vehicle body, a front drill arm, an electrical unit, a hydraulic unit, an intelligent operating console, a data acquisition unit, a data processing unit, a power start cabinet and a remote controller;

[0007] The electrical unit and the hydraulic unit provide the working power required for rock drilling construction; the intelligent operating console controls the forward movement, swing and pitch of the front drill arm, and controls the propulsion, impact and rotation of the front drill arm; the data acquisition unit is used to collect propulsion pressure, impact pressure, rotation pressure, rotation speed and displacement signals during the construction process; the data processing unit is used to receive, store and process the sensor data collected by the data acquisition unit; the power starter cabinet provides working power for the data processing unit; and the remote control can realize remote control.

[0008] Furthermore, the front drill arm includes a drill rod, a drill support, a propulsion beam, a propulsion cylinder, a rotary joint, a swing cylinder, a pitch joint, a pitch cylinder and a vehicle-mounted rock drill;

[0009] The drill support is used to ensure the stability of the drill rod during construction; the propulsion beam and the propulsion cylinder are used to realize the horizontal forward and backward movement of the vehicle-mounted rock drill; the rotating joint and the swing cylinder are used to realize the left and right translation of the vehicle-mounted rock drill; the pitch joint and the pitch cylinder are used to realize the vertical rise and fall of the vehicle-mounted rock drill.

[0010] Further, the intelligent operating console includes a propulsion control handle, a rotation control handle, an impact control handle, a flushing fluid control handle, and propulsion, swing and pitch control handles;

[0011] The propulsion, swing and pitch control handles control the speed of extension, swing and pitch of the front drill arm; the propulsion control handle, rotation control handle and impact control handle control the initial propulsion force, initial rotation speed and initial impact force of the vehicle-mounted rock drill; and the flushing fluid control handle controls the flushing fluid pressure.

[0012] Further, the data acquisition unit includes a pull rope displacement sensor, a first pressure sensor, a second pressure sensor, a third pressure sensor and a fourth pressure sensor;

[0013] The vehicle-mounted rock drill includes an impact cylinder, a pushing cylinder and a hydraulic motor; a pull rope displacement sensor is located at the front end of the pushing beam of the front drill arm to monitor the displacement during drilling in real time; a first pressure sensor is connected between the oil inlet of the hydraulic motor and the multi-way control valve of the intelligent operating table to monitor the rotational oil pressure of the hydraulic motor; a second pressure sensor is connected between the oil inlet of the pushing cylinder and the multi-way control valve of the intelligent operating table to monitor the propulsion oil pressure of the pushing cylinder; a third pressure sensor is connected between the oil inlet of the impact cylinder and the multi-way control valve of the intelligent operating table to monitor the impact oil pressure of the impact cylinder; and a fourth pressure sensor is connected between the water supply system and the multi-way control valve of the intelligent operating table to monitor the water inlet pressure during drilling.

[0014] Furthermore, the power starter cabinet includes an intrinsically safe power supply, a power transformer and a signal receiver, which are used to power the data acquisition unit during the drilling process and receive the signal transmitted by the remote controller.

[0015] Furthermore, the positioning function of the remote control adopts a cross analog handle, and the drilling function adopts a single-axis handle. The remote control is equipped with a display screen for displaying real-time drilling parameters.

[0016] An intelligent percussion rock drilling while drilling lithology identification method, using the above-mentioned intelligent percussion rock drilling while drilling lithology identification system, comprises the following steps:

[0017] S1, first connect the intelligent impact drilling while drilling lithology identification system to the water pump to ensure the flow of flushing fluid during drilling, start the hydraulic unit to ensure the system oil pressure runs smoothly, start the power starter cabinet to ensure the data acquisition unit works normally and smoothly;

[0018] S2, adjust the position of the drill arm, adjust the drill bit to a contact position close to the pre-drilling point through the thrust, swing and pitch control handles, give the system initial thrust oil pressure, initial rotation speed and initial impact oil pressure through the thrust control handle, rotation control handle and impact control handle, and start drilling construction;

[0019] S3, the pull rope displacement sensor, the first pressure sensor, the second pressure sensor, the third pressure sensor and the fourth pressure sensor in the data acquisition unit synchronously and in real time acquire drilling parameters and store them through the data processing unit;

[0020] S4, using the reverse learning strategy and the adaptive t-distribution strategy to improve the Tianying algorithm, and using the improved Tianying algorithm to optimize and train the support vector machine model;

[0021] S5, takes the thrust pressure, impact pressure, rotation pressure, drilling displacement and drilling speed as input parameters, inputs them into the optimized and trained support vector machine model, outputs the strength prediction results, and realizes the real-time prediction of the rock strength of the face during the drilling process.

[0022] Furthermore, the steps of optimizing and training the support vector machine model using the improved Sky Eagle algorithm include:

[0023] S41, dividing the data collected by the data collection unit into a training set and a test set in a ratio of 8:2;

[0024] S42, setting the value range of the penalty factor C and the kernel function g in the support vector machine model, as well as specific parameters of the improved Sky Eagle algorithm;

[0025] S43, calculating the fitness of samples in the population and obtaining the optimal fitness and position;

[0026] S44, calculating the fitness value of the population after adversarial learning and adaptive perturbation, and comparing it with the previous fitness value, and selecting the better one;

[0027] S45, judging whether the iteration condition is satisfied, if not, repeating the above actions until the optimal solution is obtained, and serving as the penalty factor C and kernel function g of the support vector machine model.

[0028] An intelligent impact rock drilling while drilling lithology identification device, comprising:

[0029] System startup module: First, connect the intelligent impact drilling lithology identification system to the water pump to ensure the flow of flushing fluid during drilling, start the hydraulic unit to ensure the smooth operation of the system oil pressure, start the power starter cabinet to ensure the normal and stable operation of the data acquisition unit;

[0030] Drilling adjustment module: adjust the position of the drill arm, adjust the drill bit to the contact position close to the pre-drilling point through the thrust, swing and pitch control handles, give the system initial thrust oil pressure, initial rotation speed and initial impact oil pressure through the thrust control handle, rotation control handle and impact control handle, and start drilling construction;

[0031] Data acquisition module: the pull rope displacement sensor, the first pressure sensor, the second pressure sensor, the third pressure sensor and the fourth pressure sensor in the data acquisition unit synchronously and in real time acquire drilling parameters and store them through the data processing unit;

[0032] Model optimization module: Use reverse learning strategy and adaptive t-distribution strategy to improve the Tianying algorithm, and use the improved Tianying algorithm to optimize and train the support vector machine model;

[0033] And, the strength prediction module: takes the thrust pressure, impact pressure, rotational pressure, drilling displacement and drilling speed as input parameters, inputs the optimized and trained support vector machine model, outputs the strength prediction results, and realizes the real-time prediction of the rock strength of the face during the drilling process.

[0034] Beneficial effects of the present invention:

[0035] 1. The intelligent impact drilling while drilling lithology identification system in the present invention is based on a rock drilling trolley, including a vehicle body, a front drill arm, an electrical system, a hydraulic system, an intelligent operating console, a data acquisition system, a data processing system, a power starter cabinet and a remote control. The data acquisition system collects the thrust pressure, impact pressure, rotational pressure, drilling displacement and drilling speed during the drilling process; obtains the while drilling parameters in real time, establishes the response relationship between the rock parameters and the while drilling parameters, predicts the strength of the tunnel surrounding rock through the data processing system, obtains the rock strength of the tunnel rock formation in real time, increases the pertinence of the tunnel face blasting plan, greatly improves the tunnel excavation speed, promotes the intelligent development of underground equipment in coal mines, and greatly ensures construction safety.

[0036] 2. The present invention adopts reverse learning strategy and adaptive t distribution to improve the Sky Eagle algorithm, and uses the improved Sky Eagle algorithm to optimize the initial parameters of the support vector machine. The optimization algorithm has better performance and the rock strength prediction model has a higher accuracy.

[0037] 3. The intelligent impact rock drilling while drilling lithology identification system of the present invention is suitable for the while drilling rock strength prediction of surrounding rocks at different positions in coal mine tunnels. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 It is a structural schematic diagram of the lithology identification system for intelligent impact rock drilling while drilling of the present invention;

[0040] Figure 2 It is a structural schematic diagram of the drill arm;

[0041] Figure 3 It is a structural diagram of the intelligent operating table;

[0042] Figure 4 To improve the prediction flow chart of the Eagle-SVM model;

[0043] In the figure: 1-front drill arm, 2-electrical unit 3-hydraulic unit, 4-intelligent operating table, 5-power start cabinet, 6-power wheel, 7-vehicle-mounted rock drill, 8-first pressure sensor, 9-second pressure sensor, 10-third pressure sensor, 11-fourth pressure sensor; 101-drill rod, 102-drill support, 103-propulsion beam, 104-propulsion cylinder, 105-rotation joint, 106-swing cylinder, 107-pitch joint, 108-pitch cylinder, 109-pull rope displacement sensor; 401-propulsion control handle, 402-rotation control handle, 403-impact control handle, 404-propulsion, swing and pitch control handles, 405-flushing fluid control handle. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Example 1

[0046] like Figure 1 As shown, an intelligent impact rock drilling while drilling lithology identification system includes a vehicle body, a front drill arm 1, an electrical unit 2, a hydraulic unit 3, an intelligent operating console 4, a data acquisition unit, a data processing unit, a power start cabinet 5 and a remote controller;

[0047] Among them, the electrical unit 2 and the hydraulic unit 3 provide the working power required for rock drilling construction; the front drill arm 1 is controlled to move forward, swing and pitch through the intelligent operating console 4, and the propulsion, impact and rotation of the front drill arm 1 are controlled; the data acquisition unit is used to collect propulsion pressure, impact pressure, rotation pressure, rotation speed and displacement signals during the construction process; the data processing unit is used to receive, store and process the sensor data collected by the data acquisition unit; the power starter cabinet 5 provides working power for the data processing unit; the remote control can realize remote control.

[0048] like Figure 1 and Figure 2 As shown, the front drill arm 1 includes a drill rod 101, a drill support 102, a propulsion beam 103, a propulsion cylinder 104, a rotary joint 105, a swing cylinder 106, a pitch joint 107, a pitch cylinder 108 and a vehicle-mounted rock drill 7;

[0049] The drill support 102 is hinged with the propulsion beam 103, and the drill rod 101 passes through the middle of the drill support 102. The drill support 102 is used to ensure the stability of the drill rod 101 during the construction process;

[0050] The thrust cylinder 104 is connected to the thrust beam 103, and drives the vehicle-mounted rock drill 7 to move forward and backward in the horizontal direction; one end of the swing cylinder 106 is connected to the rotating joint 105, and can realize the left and right translation of the vehicle-mounted rock drill 7; one end of the pitch cylinder 108 is connected to the pitch joint 107, and can realize the ascent and descent of the vehicle-mounted rock drill 7 in the vertical direction, meeting the drilling construction operation requirements at different positions and angles of the face.

[0051] like Figure 3 As shown, the intelligent operating console 4 includes a propulsion control handle 401, a rotation control handle 402, an impact control handle 403, a propulsion, swing and pitch control handle 404 and a flushing fluid control handle 405;

[0052] By controlling the switching degree of the propulsion, swing and pitch control handles 404, the speed of the drill arm extension, swing and pitch is controlled; by controlling the switching degree of the propulsion control handle 401, the rotation control handle 402 and the impact control handle 403, different initial propulsion forces, different initial rotation speeds and different initial impact forces of the vehicle-mounted rock drill 7 are controlled; by controlling the switching degree of the flushing fluid control handle 405, different flushing fluid pressures are obtained.

[0053] like Figure 1 and Figure 2 As shown, the data acquisition unit includes a pull rope displacement sensor 109, a first pressure sensor 8, a second pressure sensor 9, a third pressure sensor 10 and a fourth pressure sensor 11;

[0054] The vehicle-mounted rock drill 7 includes an impact cylinder, a push cylinder and a hydraulic motor; a pull rope displacement sensor 109 is located at the front end of the push beam of the front drill arm 1, and is connected to the hydraulic motor through a pull rope to monitor the displacement during drilling in real time; the first pressure sensor 8 is connected between the oil inlet of the hydraulic motor and the multi-way control valve of the operating console 4, and is connected to the hydraulic motor and the multi-way control valve through a hydraulic oil pipe to monitor the rotational oil pressure of the hydraulic motor; the second pressure sensor 9 is connected between the oil inlet of the push cylinder and the multi-way control valve of the operating console, and is connected to the push cylinder and the multi-way control valve through a hydraulic oil pipe to monitor the propulsion oil pressure of the propulsion cylinder; the third pressure sensor 10 is connected between the oil inlet of the impact cylinder and the multi-way control valve of the intelligent operating console 4, and is connected to the impact cylinder and the multi-way control valve through a hydraulic oil pipe to monitor the impact oil pressure of the impact cylinder; the fourth pressure sensor 11 is connected between the water supply system and the multi-way control valve of the intelligent operating console 4, and is connected to the water supply system and the multi-way control valve through a water pipe to monitor the water inlet pressure during drilling.

[0055] The data processing unit is electrically connected to the sensor in the data acquisition unit through a signal line, and is used to receive and store the data collected by the data acquisition unit.

[0056] The power starter cabinet 5 includes an intrinsically safe power supply, a power transformer and a signal receiver, which are used to power the data acquisition unit during the drilling process and receive signals from the remote controller to achieve the purpose of remote control.

[0057] The remote control positioning function adopts a cross analog handle, and the drilling function adopts a single-axis handle. The remote control has a built-in display screen for displaying real-time drilling parameters, realizing the remote control function of the front drill arm 1 positioning and drilling.

[0058] Example 2

[0059] Based on the intelligent impact rock drilling while drilling lithology identification system in Example 1, this embodiment also provides an intelligent impact rock drilling while drilling lithology identification method, including the following steps:

[0060] S1, first connect the intelligent impact drilling while drilling lithology identification system to the water pump to ensure the circulation of flushing fluid during drilling, start the hydraulic unit to ensure the smooth operation of the system oil pressure, start the power starter cabinet 5, and ensure the normal and stable operation of the data acquisition unit;

[0061] S2, adjust the position of the drill arm 1, adjust the drill bit to a contact position close to the pre-drilling point through the thrust, swing, and pitch control handles 404, give the system initial thrust oil pressure, initial rotation speed, and initial impact oil pressure through the thrust control handle 401, the rotation control handle 402, and the impact control handle 403, and start drilling construction;

[0062] S3, the pull rope displacement sensor 109, the first pressure sensor 8, the second pressure sensor 9, the third pressure sensor 10 and the fourth pressure sensor 11 in the data acquisition unit synchronously and in real time acquire drilling parameters and store them through the data processing unit;

[0063] S4, using the reverse learning strategy and the adaptive t-distribution strategy to improve the Tianying algorithm, and using the improved Tianying algorithm to optimize and train the support vector machine model;

[0064] The reverse learning strategy and adaptive t-distribution strategy are used to improve the Tianying algorithm, the purpose is to improve the solution accuracy of the Tianying algorithm, increase its convergence speed, and use the improved Tianying algorithm to optimize the support vector machine;

[0065] The principle of the reverse learning strategy is to place a convex lens at the origin, and the image formed by the lens will be A. * , height h * , A * Projecting point X on the x-axis * best That is the reverse optimal solution position;

[0066] The adaptive t distribution expression is as follows:

[0067] X new =X i +X i t(r)

[0068] In the above formula, X new is the new position after mutation, t(r) is the t distribution with the current number of iterations as the degree of freedom;

[0069] The steps of using the improved SkyEagle algorithm to optimize and train the support vector machine model include:

[0070] S41, dividing the data collected by the data collection unit into a training set and a test set in a ratio of 8:2;

[0071] S42, setting the value range of the penalty factor C and the kernel function g in the support vector machine model, as well as the specific parameters of the improved Sky Eagle algorithm (including the initial population size, the maximum number of iterations, and the initial upper and lower bounds);

[0072] S43, calculating the fitness of samples in the population and obtaining the optimal fitness and position;

[0073] S44, calculating the fitness value of the population after adversarial learning and adaptive perturbation, and comparing it with the previous fitness value, and selecting the better one;

[0074] S45, judging whether the iteration condition is satisfied (the iteration condition is to reach the maximum number of iterations), if not satisfied, repeating the above actions until the optimal solution is obtained, and serving as the penalty factor C and kernel function g of the support vector machine model.

[0075] S5, takes the thrust pressure, impact pressure, rotation pressure, drilling displacement and drilling speed as input parameters, inputs them into the optimized and trained support vector machine model, outputs the strength prediction results, and realizes the real-time prediction of the rock strength of the face during the drilling process.

[0076] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0077] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. An intelligent impact drilling while drilling lithology identification system, characterized in that: It comprises a vehicle body, a front drill arm (1), an electrical unit (2), a hydraulic unit (3), an intelligent operating console (4), a data acquisition unit, a data processing unit, a power starter cabinet (5) and a remote controller; The electrical unit (2) and the hydraulic unit (3) provide the working power required for rock drilling construction; the intelligent operating console (4) controls the forward movement, swing and pitch of the front drill arm (1), and controls the propulsion, impact and rotation of the front drill arm (1); the data acquisition unit is used to collect propulsion pressure, impact pressure, rotation pressure, rotation speed and displacement signals during the construction process; the data processing unit is used to receive, store and process the sensor data collected by the data acquisition unit; the power starter cabinet (5) provides working power for the data processing unit; and the remote control can realize remote control.

2. The intelligent impact drilling while drilling lithology identification system according to claim 1 is characterized in that: The front drill arm (1) comprises a drill rod (101), a drill support (102), a propulsion beam (103), a propulsion cylinder (104), a rotary joint (105), a swing cylinder (106), a pitch joint (107), a pitch cylinder (108) and a vehicle-mounted rock drill (7); The drill support (102) is used to ensure the stability of the drill rod (101) during the construction process; the propulsion beam (103) and the propulsion cylinder (104) are used to realize the forward and backward movement of the vehicle-mounted rock drill (7) in the horizontal direction; the rotation joint 105 and the swing cylinder 106 are used to realize the left and right translation of the vehicle-mounted rock drill (7); and the pitch joint (107) and the pitch cylinder (108) are used to realize the ascent and descent of the vehicle-mounted rock drill (7) in the vertical direction.

3. The intelligent impact drilling while drilling lithology identification system according to claim 2 is characterized in that: The intelligent operating console (4) comprises a propulsion control handle (401), a rotation control handle (402), an impact control handle (403), a flushing fluid control handle (405), and a propulsion, swing and pitch control handle (404); The propulsion, swing and pitch control handle (404) controls the speed of extension, swing and pitch of the front drill arm (1); the propulsion control handle (401), the rotation control handle (402) and the impact control handle (403) control the initial propulsion force, initial rotation speed and initial impact force of the vehicle-mounted rock drill (7); and the flushing fluid control handle (405) controls the flushing fluid pressure.

4. The intelligent rock property identification system for impact drilling while drilling according to claim 3 is characterized in that: The data acquisition unit comprises a pull rope displacement sensor (109), a first pressure sensor (8), a second pressure sensor (9), a third pressure sensor (10) and a fourth pressure sensor (11); The vehicle-mounted rock drill (7) comprises an impact cylinder, a push cylinder and a hydraulic motor; a pull rope displacement sensor (109) is located at the front end of the push beam of the front drill arm (1) to monitor the displacement during the drilling process in real time; a first pressure sensor (8) is connected between the oil inlet of the hydraulic motor and the multi-way control valve of the intelligent operating console (4) to monitor the rotation oil pressure of the hydraulic motor; a second pressure sensor (9) is connected between the oil inlet of the push cylinder and the multi-way control valve of the intelligent operating console (4) to monitor the push oil pressure of the push cylinder; a third pressure sensor (10) is connected between the oil inlet of the impact cylinder and the multi-way control valve of the intelligent operating console (4) to monitor the impact oil pressure of the impact cylinder; and a fourth pressure sensor (11) is connected between the water supply system and the multi-way control valve of the intelligent operating console (4) to monitor the water inlet pressure during the drilling process.

5. The intelligent impact drilling while drilling lithology identification system according to claim 1 is characterized in that: The power starter cabinet (5) comprises an intrinsically safe power supply, a power transformer and a signal receiver, and is used to supply power to a data acquisition unit during drilling and to receive signals transmitted by the remote controller.

6. The intelligent impact drilling while drilling lithology identification system according to claim 1 is characterized in that: The remote control positioning function adopts a cross analog handle, and the drilling function adopts a single-axis handle. The remote control is equipped with a display screen for displaying real-time drilling parameters.

7. An intelligent percussion rock drilling while drilling lithology identification method, using the intelligent percussion rock drilling while drilling lithology identification system according to claim 4, characterized in that: The following steps are involved: S1, first connect the intelligent impact drilling while drilling lithology identification system to the water pump to ensure the circulation of flushing fluid during drilling, start the hydraulic unit to ensure the smooth operation of the system oil pressure, start the power starter cabinet 5, and ensure the normal and stable operation of the data acquisition unit; S2, adjusting the position of the drill arm (1), adjusting the drill bit to a contact position close to the pre-drilling point by means of the thrust, swing and pitch control handles (404), giving the system an initial thrust oil pressure, an initial rotation speed and an initial impact oil pressure by means of the thrust control handle (401), the rotation control handle (402) and the impact control handle (403), and starting the drilling construction; S3, the pull rope displacement sensor (109), the first pressure sensor (8), the second pressure sensor (9), the third pressure sensor (10) and the fourth pressure sensor (11) in the data acquisition unit synchronously and in real time acquire drilling parameters and store them through the data processing unit; S4, using the reverse learning strategy and the adaptive t-distribution strategy to improve the Tianying algorithm, and using the improved Tianying algorithm to optimize and train the support vector machine model; S5, takes the thrust pressure, impact pressure, rotation pressure, drilling displacement and drilling speed as input parameters, inputs them into the optimized and trained support vector machine model, outputs the strength prediction results, and realizes the real-time prediction of the rock strength of the face during the drilling process.

8. The intelligent rock property identification method while drilling according to claim 7 is characterized in that: The steps of using the improved SkyEagle algorithm to optimize and train the support vector machine model include: S41, dividing the data collected by the data collection unit into a training set and a test set in a ratio of 8:2; S42, setting the value range of the penalty factor C and the kernel function g in the support vector machine model, as well as specific parameters of the improved Sky Eagle algorithm; S43, calculating the fitness of samples in the population and obtaining the optimal fitness and position; S44, calculating the fitness value of the population after adversarial learning and adaptive perturbation, and comparing it with the previous fitness value, and selecting the better one; S45, judging whether the iteration condition is satisfied, if not, repeating the above actions until the optimal solution is obtained, and serving as the penalty factor C and kernel function g of the support vector machine model.

9. An intelligent impact drilling while drilling lithology identification device, characterized in that: include: System startup module: first, connect the intelligent impact rock drilling while drilling lithology identification system to the water pump to ensure the circulation of flushing fluid during the drilling process, start the hydraulic unit to ensure the smooth operation of the system oil pressure, start the power starter cabinet (5), and ensure the normal and stable operation of the data acquisition unit; Drilling adjustment module: adjust the position of the drill arm (1), adjust the drill bit to a contact position close to the pre-drilling point through the thrust, swing and pitch control handles (404), give the system initial thrust oil pressure, initial rotation speed and initial impact oil pressure through the thrust control handle (401), the rotation control handle (402) and the impact control handle (403), and start drilling construction; Data acquisition module: the pull rope displacement sensor (109), the first pressure sensor (8), the second pressure sensor (9), the third pressure sensor (10) and the fourth pressure sensor (11) in the data acquisition unit synchronously and in real time acquire drilling parameters and store them through the data processing unit; Model optimization module: Use reverse learning strategy and adaptive t-distribution strategy to improve the Tianying algorithm, and use the improved Tianying algorithm to optimize and train the support vector machine model; And, the strength prediction module: takes the thrust pressure, impact pressure, rotational pressure, drilling displacement and drilling speed as input parameters, inputs the optimized and trained support vector machine model, outputs the strength prediction results, and realizes the real-time prediction of the rock strength of the face during the drilling process.

Images