CN116291193A - Tunnel face stability monitoring and rock parameter predicting device and operation method thereof - Google Patents

Abstract

The invention provides a device for monitoring stability of tunnel face and predicting rock parameters and an operation method thereof, belonging to the technical field of tunnel construction investigation, wherein the device comprises a tunnel crawler, a central control room, a drilling arm and a scanning arm; the drilling arm comprises a drill rod and a drill bit, and a stability monitoring system is arranged on the side edge of the scanning arm; the periphery of the drilling arm is fixedly provided with a drilling acoustic monitoring system and a drilling parameter monitoring system; the operation method comprises the following steps: 1) Opening a central control room; 2) Moving to a target position; 3) Opening each system and setting drilling depth; 4) The drill rod starts to drill, and information such as drilling speed, drilling pressure, drill torque, rock mass vibration frequency, rock mass natural frequency and the like of the drill rod are obtained; 5) The central control room receives the data and parameters, and the numerical values of the compressive strength, the tensile strength, the internal friction angle and the like of the drilling rock mass are accurately predicted based on the fusion analysis of a least square support vector machine system.

Description

A tunnel face stability monitoring and rock mass parameter prediction device and its operation method

technical field

The invention belongs to the technical field of tunnel construction investigation, and in particular relates to a tunnel face stability monitoring and rock mass parameter prediction device and an operating method thereof.

Background technique

In the tunnel construction survey technology, the drilling process monitoring technology monitors the parameter changes of the drill pipe (head) by installing a monitoring device on the drilling rig, which reflects the softness and hardness of the drilled rock and soil layer to a certain extent. However, the parameters selected by the drilling process monitoring technology are mostly drilling speed, bit pressure, drilling torque, etc., which can only qualitatively reflect the soft and hard conditions of the formation. At the same time, during the drilling construction process, rocks often fall off. , has a strong risk, and the existing technology cannot quickly and accurately evaluate the rock mass parameters and stability of the face of the drilled tunnel.

Contents of the invention

The object of the present invention is to provide a tunnel face stability monitoring and rock mass parameter prediction device and its operation method, which is characterized in that it includes a tunnel crawler vehicle, a central control room fixed above the tunnel crawler vehicle, and is movable and fixed in the central control room. The drilling arm on the front side of the control room and the scanning arm fixed on the top of the central control room;

The drilling arm includes a drill pipe and a drill bit fixed at the end of the drill pipe. A face stability monitoring system is installed on the side of the scanning arm to monitor and record the basic condition of the face and the vibration frequency of the rock mass at the face;

The face stability monitoring system includes multiple laser transmitters and laser receivers, and multiple laser transmitters and laser receivers are connected to the central control room for signals;

The tunnel face stability monitoring and rock mass parameter prediction device controls the movement of the tunnel crawler vehicle, the drilling arm and the scanning arm through the laser control room, and receives, transmits and processes the data of the face stability monitoring system.

Further, the number of laser emitters and laser receivers is five, and the five laser emitters and laser receivers are divided into five groups of laser parts, each group of laser parts includes a laser emitter and a laser receiver set opposite to each other , five sets of laser parts are fixed on the side of the scanning arm at equal intervals.

Furthermore, the scanning arm realizes the up and down scanning of the tunnel and the comprehensive scanning of the tunnel face, and the scanning frequency of the tunnel face stability monitoring system is 400HZ.

Furthermore, a drilling acoustic monitoring system is fixed on the periphery of the drilling arm for monitoring and recording various data information when the drill bit breaks rocks. The drilling acoustic monitoring system is connected to the central control room for signals, and the central control room receives, transmits and processes the drilling data. Various data transmitted into the acoustic monitoring system.

Further, a drilling parameter monitoring system for monitoring and recording the drilling speed, drilling pressure and drilling torque of the drill pipe is also fixed on the periphery of the drilling arm. The drilling parameter monitoring system is connected to the central control room for signal connection, and the central control room Receive, transmit and process drilling speed, drilling pressure and drilling torque.

A method for operating a tunnel face stability monitoring and rock mass parameter prediction device, comprising the following steps:

S1: open the central control room;

S2: Control the crawler vehicle through the central control room to move the tunnel face stability monitoring and rock mass parameter prediction device to the target position, and move the drilling arm to the drilling position;

S3: Turn on the drilling acoustic monitoring system, the drilling parameter monitoring system and the tunnel face stability monitoring system, and set the target drilling depth;

S4: The drill pipe starts to drill, and records the drilling speed parameters, drilling pressure parameters, drill bit torque parameters and various data when the drill bit breaks rock;

S5: The central control room receives and processes various data and parameters and analyzes them to complete the prediction of rock mass parameters.

Further, in S5, various data and parameters are fused and analyzed through the least squares support vector machine to complete the prediction of rock mass parameters.

Furthermore, the central control room receives data from the tunnel face stability monitoring system and monitors the vibration of the entire face rock mass in real time. When the natural vibration frequency of the face rock mass drops sharply, the central control room immediately monitors body for warning.

Compared with the prior art, the beneficial effects of the present invention are mainly reflected in:

1. The parameters in the drilling process of the drill pipe and the sound pressure information of drilling rock breaking are obtained through the present invention, and these data are fused and analyzed through the least squares support vector machine system, which can accurately predict the compressive strength of the drilled rock mass, Tensile strength, internal friction angle and other values can monitor the vibration frequency of the entire face rock mass in real time, and provide real-time early warning of dangerous rock mass caused by drilling construction disturbance at the face face.

Description of drawings

Fig. 1 is a structural schematic diagram of a tunnel face stability monitoring and rock mass parameter prediction device of the present invention;

Fig. 2 is a schematic diagram of the relationship model between drilling response and compressive strength established based on SVM;

Fig. 3 is a schematic diagram of the training matrix of the present invention;

Fig. 4 is a schematic diagram of the test matrix of the present invention;

Fig. 5 is the schematic diagram that the present invention carries out normalization processing to the received data;

Fig. 6 is a graph of the fitness degree of the present invention.

Among them, 1. Laser transmitter; 2. Laser receiver; 3. Drilling acoustic monitoring system; 4. Drill bit; 5. Drilling arm; 6. Drilling parameter monitoring system; 7. Scanning arm; 8. Central control room ; 9. Tunnel crawler vehicles.

Detailed ways

A tunnel face stability monitoring and rock mass parameter prediction device and its operating method will be described in more detail below in conjunction with the schematic diagram, wherein a preferred embodiment of the present invention is shown, it should be understood that those skilled in the art can modify the The present invention described above, while still achieving the advantageous effects of the present invention, therefore, the following description should be understood as the broad knowledge of those skilled in the art, and not as a limitation to the present invention.

As shown in FIG. 1 , the present invention provides a tunnel face stability monitoring and rock mass parameter prediction device, which consists of four parts: a tunnel crawler vehicle 9 , a central control room 8 , a drilling arm 5 , and a scanning arm 7 .

Wherein, the advance of the control device of the tunnel crawler vehicle 9 can adapt to various complex geological conditions.

Central control room 8: drive and control the crawler vehicle, the movement of the drilling arm 5 and the scanning arm 7 through motors and motors, integrating the movement control system of the vehicle and the mechanical arm, monitoring the stability of the tunnel face and rock mass The fusion analysis system of the parameter prediction system and the least squares support vector machine system can receive, transmit and process data from the drilling acoustic monitoring system 3, the drilling parameter monitoring system 6 and the tunnel face stability monitoring system.

Drilling arm 5: located at the front side of the central control room 8, capable of crushing and drilling high-strength rocks.

Scanning arm 7: located on the top of the central control room 8 and protruding forward, it can realize comprehensive scanning of the face of the palm. The scanning arm 7 can realize scanning up and down, and the scanning frequency is 400HZ.

The drilling acoustic monitoring system 3 and the drilling parameter monitoring system 6 are installed on the periphery of the drilling arm 5 , and the tunnel face stability monitoring system is installed on the side of the scanning arm 7 .

The drilling acoustic monitoring system 3 can monitor and record information such as sound, frequency, and sound pressure when the drill bit 4 breaks rock.

The drilling parameter monitoring system 6 can monitor and record the drilling speed, drilling pressure and drilling torque of the drill pipe.

The tunnel face stability monitoring system consists of five sets of laser parts arranged at equal intervals. Each set of laser parts includes a laser transmitter 1 and a laser receiver 2, which can monitor, record and scan the basic conditions of the face and the tunnel face. The vibration frequency of the rock mass.

The embodiment of the present invention also provides a tunnel face stability monitoring and rock mass parameter prediction method, including the following steps:

The first step: open the central control room 8;

Step 2: Control the crawler vehicle to travel to a suitable position, and move the drilling arm 5 to the target drilling position;

Step 3: Open the data of the drilling acoustic monitoring system 3, the drilling parameter monitoring system 6 and the tunnel face stability monitoring system;

Step 4: Set the target drilling depth, start drilling the drill pipe, record the drilling speed, drilling pressure, drill bit 4 torque, sound, frequency, sound pressure and rock mass vibration frequency when the drill bit 4 breaks rock, Rock mass natural frequency information and other data;

Step 5: The central control room 8 receives and processes the records recorded by the drilling acoustic monitoring system 3 and the drilling parameter monitoring system 6. The drilling speed, drilling pressure, drill bit 4 torque, sound, frequency, Acoustic pressure, rock mass vibration frequency, rock mass natural frequency information and other data, based on the least squares support vector machine system fusion analysis of these data, predict the compressive strength, tensile strength, density and other values of the drilled rock mass. The specific analysis process is:

Set the adaptive threshold e, particle dimension n, population size m, iteration number P, learning factors c ₁ , c ₂ and inertia factor ε of the particle swarm least squares SVM algorithm, and randomly give the initial solution space position x _i0 of the particle . and particle initial velocity v _i0 . Most of the samples obtained in the data are used as the learning samples of the particle swarm optimization least squares SVM model, and a few samples are selected as the test samples. In order to avoid the influence of inconsistent data dimensions and improve the training speed, the training samples are normalized to the interval [0, 1]. The test sample is predicted by the support vector machine model corresponding to each particle vector, and the prediction error of the predicted test sample is used as the individual fitness value, which reflects the promotion and prediction ability of the support vector model.

Among them, n is the number of particle samples participating in the particle swarm least squares LS-SVM training, and y _j ^d and y _j are the training output value of the least squares support vector machine and the expected output value of the particle, respectively.

The fitness value calculated for each particle is compared with the fitness value of the current individual optimal solution. If S _i (x)<pbesti, replace the current special optimal solution with particles, ie pbesti=S _i (x), xpbesti=xi. The fitting value of each particle's current individual optimal solution and the current population optimal fitness value is compared. If pbesti<gbesti, replace the original population optimal solution with particles, namely: gbesti=pbesti, xgbesti=xi. After calculating the entire particle swarm, judge whether the termination condition is satisfied, if not, generate a new particle swarm, and return to the initial step. If the termination requirements are met, the calculation ends and the calculation result is output. Based on the principle of PSOLSSVM, an input matrix consisting of rotational speed (N), drilling speed (V), drilling pressure (F), drilling torque (M), drilling sound level (Leq) etc. is established and respectively The output matrix consisting of uniaxial compressive strength (Rc), tensile strength (Rm), density, etc., is shown in Figure 2. Call the PS0LSSVM program in the Matlab software, the training matrix is shown in Figure 3, the test matrix is shown in Figure 4, and the normalization process is performed, as shown in Figure 5. After the processing is completed, machine learning (training) and prediction are performed. After the fitness curve is flat, as shown in Figure 6, machine learning (training) and prediction are completed.

Furthermore, the central control room 8 receives data from the tunnel face stability monitoring system, and monitors the vibration of the rock mass on the entire face in real time. Early warning of dangerous rock mass.

The foregoing are only preferred embodiments of the present invention, and do not limit the present invention in any way. Any person skilled in the technical field, within the scope of the technical solution of the present invention, makes any form of equivalent replacement or modification to the technical solution and technical content disclosed in the present invention, which does not depart from the technical solution of the present invention. The content still belongs to the protection scope of the present invention.

Claims (8)

1. A tunnel face stability monitoring and rock mass parameter prediction device is characterized in that it comprises a tunnel crawler vehicle, a central control room fixed above the tunnel crawler vehicle, and a drill fixed on the front side of the central control room. The moving arm and the scanning arm fixed on the top of the central control room; The drilling arm includes a drill pipe and a drill bit fixed at the end of the drill pipe. A face stabilizer is provided on the side of the scanning arm for monitoring and recording the basic condition of the face and the vibration frequency of the rock mass at the face. sex monitoring system; The face stability monitoring system includes a plurality of laser emitters and laser receivers, and a plurality of the laser emitters and the laser receivers are all signal-connected to the central control room; The tunnel face stability monitoring and rock mass parameter prediction device controls the movement of the tunnel crawler, the drilling arm and the scanning arm through the laser control room, and receives, transmits and processes the face stability monitoring system data. 2. The tunnel face stability monitoring and rock mass parameter prediction device according to claim 1, wherein the number of the laser emitters and the laser receivers is five, and the five laser emitters The laser receiver and the laser receiver are divided into five groups of laser parts, each group of laser parts includes a laser emitter and a laser receiver oppositely arranged, and the five groups of laser parts are fixed on the side of the scanning arm at equal intervals. 3. The tunnel face stability monitoring and rock mass parameter prediction device according to claim 1, characterized in that, the scanning arm realizes the up and down scanning of the tunnel and the comprehensive scanning of the face, and the face The scanning frequency of the stability monitoring system is 400HZ. 4. The tunnel face stability monitoring and rock mass parameter prediction device according to claim 1, characterized in that, the outer periphery of the drilling arm is fixed with various data information for monitoring and recording when the drill bit breaks rock The drilling acoustic monitoring system is connected with the central control room by signal, and the central control room receives, transmits and processes various data transmitted by the drilling acoustic monitoring system. 5. The tunnel face stability monitoring and rock mass parameter prediction device according to claim 4, characterized in that, the outer periphery of the drilling arm is also fixed with a drilling speed, drilling speed, drilling A drilling parameter monitoring system for drilling pressure and drilling torque, the drilling parameter monitoring system is connected with the central control room for signals, and the central control room receives, transmits and processes the drilling speed, drilling pressure and drilling into the torque. 6. A method for operating a tunnel face stability monitoring and rock mass parameter prediction device, using the tunnel face stability monitoring and rock mass parameter prediction device according to claims 1-5, characterized in that it comprises Follow the steps below: S1: open the central control room; S2: Control the crawler vehicle through the central control room to move the tunnel face stability monitoring and rock mass parameter prediction device to the target position, and move the drilling arm to the drilling position; S3: Turn on the drilling acoustic monitoring system, the drilling parameter monitoring system and the tunnel face stability monitoring system, and set the target drilling depth; S4: The drill pipe starts to drill, and records the drilling speed parameters, drilling pressure parameters, drill bit torque parameters and various data when the drill bit breaks the rock; S5: The central control room receives and processes various data and parameters and analyzes them to complete the prediction of rock mass parameters. 7. The operation method of the tunnel face stability monitoring and rock mass parameter prediction device according to claim 6, characterized in that, in said S5, various data and parameters are fused by a least squares support vector machine And analyze to complete the prediction of rock mass parameters. 8. The operation method of the tunnel face stability monitoring and rock mass parameter prediction device according to claim 6, characterized in that, the central control room receives data from the tunnel face stability monitoring system and monitors the entire operation in real time. When the natural vibration frequency of the rock mass on the face face drops sharply, the central control room will immediately give an early warning to the dangerous rock mass.

Images