A device for monitoring tunnel face stability and predicting rock mass parameters and its operation method.

Abstract

This invention provides a device for monitoring the stability of a tunnel face and predicting rock mass parameters, and its operating method. It belongs to the field of tunnel construction and exploration technology. The device includes a tunnel tracked vehicle, a central control room, a drilling arm, and a scanning arm. The drilling arm includes a drill rod and a drill bit. A stability monitoring system is installed on the side of the scanning arm. A drilling acoustic monitoring system and a drilling parameter monitoring system are fixed to the outer periphery of the drilling arm. The operating method includes the following steps: 1) Open the central control room; 2) Move to the target position; 3) Open each system and set the drilling depth; 4) The drill rod begins drilling, and information such as the drill rod drilling speed, drilling pressure, drill bit torque, rock mass vibration frequency, and rock mass natural frequency are acquired; 5) The central control room receives the data and completes the prediction. This invention receives the above data and parameters through the central control room and, based on a least squares support vector machine system fusion analysis, accurately predicts the compressive strength, tensile strength, and internal friction angle of the drilled rock mass.

Description

Technical Field

[0001] This invention belongs to the field of tunnel construction and exploration technology, and particularly relates to a device for monitoring the stability of the tunnel face and predicting rock mass parameters, and its operation method. Background Technology

[0002] In tunnel construction exploration technology, drilling process monitoring technology monitors changes in drill rod (head) parameters by installing monitoring devices on the drilling rig, reflecting the hardness of the drilled rock and soil layers to a certain extent. However, the parameters selected by drilling process monitoring technology are mostly drilling speed, drill bit pressure, drilling torque, etc., which can only qualitatively reflect the hardness of the strata. At the same time, rockfalls often occur during drilling, posing a high risk. Furthermore, existing technologies cannot quickly and accurately evaluate the parameters and stability of the rock mass at the tunnel face. Summary of the Invention

[0003] The purpose of this invention is to provide a device for monitoring the stability of a tunnel face and predicting rock mass parameters, and its operation method. The device is characterized by including a tunnel tracked vehicle, a central control room fixed above the tunnel tracked vehicle, a drilling arm movably fixed to the front of the central control room, and a scanning arm movably fixed to the top of the central control room.

[0004] The drilling arm includes a drill rod and a drill bit fixed to the end of the drill rod. The side of the scanning arm is equipped with a face stability monitoring system for monitoring and recording the basic conditions of the face and the vibration frequency of the rock mass at the face.

[0005] The working face stability monitoring system includes multiple laser emitters and laser receivers, all of which are connected to the central control room via signal transmission.

[0006] The tunnel face stability monitoring and rock mass parameter prediction device controls the movement of the tunnel tracked vehicle, drilling arm, and scanning arm through a laser control room, and receives, transmits, and processes data from the tunnel face stability monitoring system.

[0007] Furthermore, there are five laser emitters and five laser receivers. The five laser emitters and laser receivers are divided into five groups of laser components. Each group of laser components includes a laser emitter and a laser receiver arranged opposite each other. The five groups of laser components are fixed at equal intervals on the side of the scanning arm.

[0008] Furthermore, the scanning arm enables vertical scanning of the tunnel and a full scan of the tunnel face, with the scanning frequency of the tunnel face stability monitoring system being 400 Hz.

[0009] Furthermore, a drilling acoustic monitoring system is fixed to the outer periphery of the drilling arm to monitor and record various data information when the drill bit breaks rock. The drilling acoustic monitoring system is connected to the central control room, which receives, transmits and processes various data transmitted by the drilling acoustic monitoring system.

[0010] Furthermore, a drilling parameter monitoring system is fixed to the outer periphery of the drilling arm to monitor and record the drilling speed, drilling pressure, and drilling torque of the drill pipe. The drilling parameter monitoring system is connected to the central control room, which receives, transmits, and processes the drilling speed, drilling pressure, and drilling torque.

[0011] A method for operating a tunnel face stability monitoring and rock mass parameter prediction device includes the following steps:

[0012] S1: Open the central control room;

[0013] S2: Control the tracked 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;

[0014] S3: Turn on the drilling acoustic monitoring system, drilling parameter monitoring system and tunnel face stability monitoring system, and set the target drilling depth;

[0015] S4: Drilling begins; record the drilling speed parameters, drilling pressure parameters, drill bit torque parameters, and various data when the drill bit breaks rock.

[0016] S5: The central control room receives, processes, and analyzes various data and parameters to predict rock mass parameters.

[0017] Furthermore, in S5, various data and parameters are fused and analyzed using a least-squares support vector machine to predict rock mass parameters.

[0018] Furthermore, the central control room receives data from the tunnel face stability monitoring system and monitors the vibration of the rock mass across the entire tunnel face in real time. When the natural vibration frequency of the rock mass at the tunnel face drops sharply, the central control room immediately issues an early warning for the dangerous rock mass.

[0019] Compared with the prior art, the beneficial effects of the present invention are mainly reflected in:

[0020] 1. By acquiring parameters during the drilling process and sound pressure information of rock breaking in the borehole through this invention, and by fusing and analyzing these data through a least squares support vector machine system, it is possible to accurately predict the compressive strength, tensile strength, internal friction angle, and other values ​​of the drilled rock mass. It is also possible to monitor the vibration frequency of the rock mass at the entire working face in real time and provide real-time early warning of dangerous rock masses caused by drilling disturbances at the working face. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of a tunnel face stability monitoring and rock mass parameter prediction device according to the present invention;

[0022] Figure 2 This is a schematic diagram of the relationship between drilling response and compressive strength established based on SVM.

[0023] Figure 3 This is a schematic diagram of the training matrix of the present invention;

[0024] Figure 4 This is a schematic diagram of the test matrix for this invention;

[0025] Figure 5 This is a schematic diagram illustrating the normalization process of the received data according to the present invention;

[0026] Figure 6 This is a fitness curve diagram for the present invention.

[0027] The components include: 1. Laser emitter; 2. Laser receiver; 3. Drilling acoustic monitoring system; 4. Drill bit; 5. Drill arm; 6. Drilling parameter monitoring system; 7. Scanning arm; 8. Central control room; and 9. Tunnel tracked vehicle. Detailed Implementation

[0028] The following will describe in more detail, with reference to the schematic diagram, a device for monitoring the stability of the tunnel face and predicting rock mass parameters and its operation method. The diagram illustrates a preferred embodiment of the invention. It should be understood that those skilled in the art can modify the invention described herein while still achieving the beneficial effects of the invention. Therefore, the following description should be understood as being of general knowledge to those skilled in the art and is not intended to limit the invention.

[0029] like Figure 1 As shown, the present invention provides a device for monitoring the stability of the tunnel face and predicting rock mass parameters, which consists of four parts: a tunnel tracked vehicle 9, a central control room 8, a drilling arm 5, and a scanning arm 7.

[0030] Among them, the movement of the tunnel tracked vehicle 9 control device can adapt to a variety of complex geological conditions.

[0031] Central Control Room 8: Drives and controls the movement of the tracked vehicle, drilling arm 5, and scanning arm 7 via motors and electric motors. It integrates the vehicle and robotic arm movement control system, tunnel face stability monitoring and rock mass parameter prediction system, and least squares support vector machine system fusion analysis system. It can also receive, transmit, and process data from the drilling acoustic monitoring system 3, drilling parameter monitoring system 6, and tunnel face stability monitoring system.

[0032] Drilling arm 5: Located in front of the central control room 8, it is capable of breaking and drilling into high-strength rock.

[0033] Scanning arm 7: Located at the top of the central control room 8 and extending forward, it can perform a full scan of the working face. Scanning arm 7 can perform vertical scanning at a frequency of 400 Hz.

[0034] The drilling arm 5 is equipped with a drilling acoustic monitoring system 3 and a drilling parameter monitoring system 6 on its outer periphery, and the tunnel face stability monitoring system is installed on the side of the scanning arm 7.

[0035] 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.

[0036] The drilling parameter monitoring system 6 can monitor and record the drilling speed, drilling pressure, and drilling torque of the drill pipe.

[0037] The tunnel face stability monitoring system consists of five sets of laser elements arranged at equal intervals. Each set of laser elements includes a laser transmitter 1 and a laser receiver 2, which can monitor and record the basic conditions of the tunnel face and the vibration frequency of the rock mass at the tunnel face.

[0038] Embodiments of the present invention also provide a method for monitoring tunnel face stability and predicting rock mass parameters, comprising the following steps:

[0039] Step 1: Activate Central Control Room 8;

[0040] Step 2: Control the tracked vehicle to a suitable position and move the drilling arm 5 to the target drilling position;

[0041] Step 3: Activate the data from the drilling acoustic monitoring system 3, the drilling parameter monitoring system 6, and the tunnel face stability monitoring system;

[0042] Step 4: Set the target drilling depth, start drilling with the drill rod, and record data such as drill rod drilling speed, drilling pressure, drill bit torque, sound, frequency, sound pressure when the drill bit breaks rock, rock vibration frequency, and natural frequency of the rock mass.

[0043] Step 5: The central control room receives and processes data recorded by the drilling acoustic monitoring system 3 and the drilling parameter monitoring system 6, including drill pipe drilling speed, drilling pressure, drill bit torque, sound, frequency, and sound pressure during rock breaking, as well as rock vibration frequency and natural rock frequency information. Based on the least squares support vector machine system, this data is fused and analyzed to predict the compressive strength, tensile strength, and density of the drilled rock mass. The specific analysis process is as follows:

[0044] The particle swarm optimization (PSO) least squares (SVM) algorithm is configured with the following parameters: fitness threshold e, particle dimension n, population size m, number of iterations P, learning factors c1 and c2, and inertia factor ε. The initial solution space position x of each particle is randomly assigned. i0 And the initial velocity v of the particle i0 Most of the samples obtained from the data were used as training samples for the particle swarm optimization least squares SVM model, with a few examples selected as test samples. To avoid the influence of inconsistent data dimensionality and improve training speed, the training samples were normalized to the interval [0, 1]. The test samples were predicted by the support vector machine model corresponding to each particle vector, and the prediction error of the test samples was used as the individual fitness value, reflecting the generalization and prediction ability of the support vector model.

[0045] Where n is the number of particle samples participating in the particle swarm optimization least squares LS-SVM training, y j d and y j These are the training output value of the least squares support vector machine and the expected output value of the particle, respectively.

[0046] The fitness value calculated for each particle is compared with the fitness value of the current individual's optimal solution. If S i If (x) < pbesti, then replace the current particular optimal solution with a particle, i.e., pbesti = S. i (x), xpbesti = xi. The fitted values ​​of the current individual optimal solution for each particle and the current population optimal fitness value are compared. If pbesti < gbesti, then the original population optimal solution is replaced by the particle, i.e., gbesti = pbesti, xgbesti = xi. After calculating the entire particle swarm, it is determined whether the termination condition is met. If not, a new particle swarm is generated, and the process returns to the initial step. If the termination condition is met, the calculation ends, and the result is output. Based on the principle of PSOLSSVM, an input matrix composed of rotational speed (N), drilling speed (V), drilling pressure (F), drilling torque (M), and drilling sound level (Leq) is established, along with an output matrix composed of uniaxial compressive strength (Rc), tensile strength (Rm), and density, as shown below. Figure 2 As shown. In Matlab software, call the PS0LSSVM program to generate the training matrix as shown. Figure 3 As shown, the test matrix is ​​as follows Figure 4 As shown, normalization is performed, such as... Figure 5 As shown, after processing, machine learning (training) and prediction are performed. When the fitness curve flattens out, as... Figure 6 As shown, this completes machine learning (training) and prediction.

[0047] Furthermore, the central control room 8 receives data from the tunnel face stability monitoring system and monitors the vibration of the rock mass across the entire tunnel face in real time. When the natural vibration frequency of the rock mass at a certain point on the tunnel face drops sharply, the control room immediately issues an early warning for the dangerous rock mass.

[0048] The above are merely preferred embodiments of the present invention and do not constitute any limitation on the present invention. Any equivalent substitutions or modifications made by those skilled in the art to the technical solutions and content disclosed in the present invention without departing from the scope of the present invention shall be deemed to have remained within the protection scope of the present invention.

Claims

1. A device for monitoring tunnel face stability and predicting rock mass parameters, characterized in that, It includes a tunnel tracked vehicle, a central control room fixed above the tunnel tracked vehicle, a drilling arm movably fixed to the front side of the central control room, and a scanning arm movably fixed to the top of the central control room; The drilling arm includes a drill rod and a drill bit fixed to the end of the drill rod. The side of the scanning arm is equipped with a face stability monitoring system for monitoring and recording the basic conditions of the face and the vibration frequency of the rock mass at the face. The working face stability monitoring system includes multiple laser emitters and laser receivers, all of which are connected to the central control room via signal transmission. The tunnel face stability monitoring and rock mass parameter prediction device controls the movement of the tunnel tracked vehicle, drilling arm and scanning arm through the central control room, and receives, transmits and processes the data of the tunnel face stability monitoring system. 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 components. The five groups of laser components are fixed at equal intervals on the side of the scanning arm. The scanning frequency of the face stability monitoring system is 400 Hz; A drilling acoustic monitoring system is fixed to the outer periphery of the drilling arm for monitoring and recording various data information when the drill bit breaks rock. The drilling acoustic monitoring system is connected to the central control room, which receives, transmits and processes various data transmitted by the drilling acoustic monitoring system. The drilling arm is also fixed with a drilling parameter monitoring system for monitoring and recording the drilling speed, drilling pressure and drilling torque of the drill rod. The drilling parameter monitoring system is connected to the central control room, which receives, transmits and processes the drilling speed, drilling pressure and drilling torque.

2. The tunnel face stability monitoring and rock mass parameter prediction device according to claim 1, characterized in that, Each set of laser components includes a laser emitter and a laser receiver positioned opposite each other.

3. The tunnel face stability monitoring and rock mass parameter prediction device according to claim 1, characterized in that, The scanning arm enables vertical scanning of the tunnel and full scanning of the tunnel face.

4. 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 as described in any one of claims 1-3, characterized in that, Includes the following steps: S1: Open the central control room; S2: Control the tracked 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, drilling parameter monitoring system and tunnel face stability monitoring system, and set the target drilling depth; S4: Drilling begins; record 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, processes, and analyzes various data and parameters to predict rock mass parameters.

5. The operating method of the tunnel face stability monitoring and rock mass parameter prediction device according to claim 4, characterized in that, In step S5, the rock mass parameters are predicted by fusing and analyzing various data and parameters using a least-squares support vector machine.

6. The operating method of the tunnel face stability monitoring and rock mass parameter prediction device according to claim 4, characterized in that, The central control room receives data from the tunnel face stability monitoring system and monitors the vibration of the rock mass across the entire tunnel face in real time. When the natural vibration frequency of the rock mass at the tunnel face drops sharply, the central control room immediately issues an early warning for the dangerous rock mass.

Images