Tunnel intelligent sensing drilling machine

Abstract

The invention discloses a tunnel intelligent sensing drilling machine, which relates to the technical field of tunnel engineering construction, and comprises a drilling machine main body, an intelligent sensing module, a data acquisition module, a data transmission module, a central processing unit and a decision support module, the intelligent sensing module is integrated on the drilling machine body and used for monitoring drilling data. The data acquisition module is connected with the intelligent sensing module and is used for acquiring drilling data and preprocessing the drilling data; the data transmission module is used for transmitting the preprocessed drilling data to the central processing unit in real time; and the central processing unit performs data interaction with the decision support module, generates an optimized construction scheme, generates a control instruction and sends the control instruction to an execution mechanism of the drilling machine main body. According to the invention, automatic sensing and accurate adjustment of construction parameters can be realized in a complex underground environment, and potential safety hazards are significantly reduced; the construction efficiency is improved, and manual operation errors and resource waste are reduced; and scientific and reliable construction is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel engineering construction, and more specifically, to a tunnel intelligent perception drilling rig. Background Art

[0002] In modern tunnel engineering construction, with the continuous growth of the demand for transportation infrastructure construction and underground space development, the scale of tunnel engineering has been expanding, and the construction scenarios have become increasingly complex. Traditional drilling rigs mainly rely on the experience of operators for manual control. In a construction environment with relatively stable geological conditions, the basic construction progress can still be guaranteed by the skilled skills of the operators. However, currently, tunnel engineering often needs to pass through extreme geological regions such as karst landforms, water-rich fault zones, and high in-situ stress rock areas. The underground environment is complex and changeable, and the dynamic changes of geological parameters pose a major challenge to safe construction.

[0003] Therefore, how to provide a tunnel intelligent perception drilling rig that can perceive and quickly respond to changes in underground conditions in real time, improve construction efficiency, and reduce potential safety hazards is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention provides a tunnel intelligent perception drilling rig, which realizes the automatic adjustment of operation parameters according to the underground environment through the integration of multiple sensors and intelligent algorithm analysis, so as to ensure efficient and safe tunnel construction.

[0005] To achieve the above object, the present invention adopts the following technical solutions: A tunnel intelligent perception drilling rig, comprising: a drilling rig main body, an intelligent perception module, a data acquisition module, a data transmission module, a central processing unit, and a decision support module; The intelligent perception module is integrated into the drilling rig main body and is used to monitor drilling data; The data acquisition module is connected to the intelligent perception module and is used to collect drilling data and preprocess the drilling data; The data transmission module is used to transmit the preprocessed drilling data to the central processing unit in real time; The central processing unit conducts data interaction with the decision support module, generates an optimized construction plan, and generates control instructions to be sent to the actuator of the drilling rig main body.

[0006] Preferably, the decision support module uses a genetic algorithm and a particle swarm optimization algorithm to optimize the construction plan.

[0007] Preferably, the central processing unit includes a multi-core ARM processor with a main frequency of 1.8 GHz, 8 GB of RAM, 128 GB of SSD storage, and an embedded Linux operating system.

[0008] Preferably, the intelligent sensing module includes: a geological sensor, a temperature sensor, a humidity sensor, and a pressure sensor; which respectively measure the resistivity of the drilled formation, the temperature of the drill bit cutting area and the surrounding formation, the humidity value of the soil or gas, and the pressure value during the drilling process.

[0009] Preferably, the geological sensor uses a resistivity sensor and is arranged at the front end or the front side of the edge of the drill bit; The temperature sensor uses a PT100 platinum resistance temperature sensor and is arranged inside the drill bit near the cutting area; The humidity sensor uses a capacitive humidity sensor and is arranged on the outer side of the drill bit; The pressure sensor uses a piezoresistive pressure sensor and is arranged at the rear of the drill bit or at the connection with the drill pipe.

[0010] Preferably, the central processing unit uses a neural network model to perform real-time analysis on the collected data, and the neural network model includes a convolutional neural network and a recurrent neural network.

[0011] Preferably, it further includes a display module. The display module is connected to the central processing unit. The display screen of the display module is a 7-inch touch liquid crystal screen with a resolution of 800×480 pixels.

[0012] Through the above technical solutions, compared with the prior art, the present invention discloses a tunnel intelligent sensing drill rig, including: a drill rig main body, an intelligent sensing module, a data acquisition module, a data transmission module, a central processing unit, and a decision support module; the intelligent sensing module is integrated in the drill rig main body for monitoring drilling data; the data acquisition module is connected to the intelligent sensing module for acquiring drilling data and preprocessing the drilling data; the data transmission module is used to transmit the preprocessed drilling data to the central processing unit in real time; the central processing unit exchanges data with the decision support module to generate an optimized construction plan and generate control instructions to be sent to the actuator of the drill rig main body. The present invention can achieve automatic sensing and precise adjustment of construction parameters in a complex underground environment, significantly reducing potential safety hazards; improving construction efficiency, reducing manual operation errors and resource waste; achieving scientific and reliable construction, and performing real-time monitoring and feedback through an intelligent analysis system. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0014] Figure 1 Schematic diagram of the internal structure and connections of the power transmission part of the drill rig provided by the embodiment of the present invention.

[0015] Figure 2 Schematic diagram of the drilling process of the drill rig provided by the embodiment of the present invention, as well as the monitored drilling parameters and data transmission. Specific embodiments

[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] The embodiment of the present invention discloses a tunnel intelligent sensing drill rig, including: a drill rig main body, an intelligent sensing module, a data acquisition module, a data transmission module, a central processing unit, and a decision support module; The intelligent sensing module is integrated into the drill rig main body and is used to monitor drilling data; The data acquisition module is connected to the intelligent sensing module and is used to acquire drilling data and preprocess the drilling data; The data transmission module is used to transmit the preprocessed drilling data to the central processing unit in real time; The central processing unit exchanges data with the decision support module, generates an optimized construction plan, and generates a control instruction to be sent to the actuator of the drill rig main body.

[0018] Specifically, the main body parameters of the tunnel intelligent sensing drill rig include: total weight: 5000 kg; maximum drilling diameter: 1200 mm; drilling depth range: 0 to 1000 m; main machine size: 2500 mm × 1500 mm × 1800 mm (length × width × height); propulsion system: the propulsion method is hydraulic propulsion; the maximum propulsion force is 2000 kN; power system: motor power: 75 kW; working voltage: 380 V.

[0019] Specifically, the intelligent sensing module includes: a geological sensor, a temperature sensor, a humidity sensor, and a pressure sensor; respectively measure the resistivity of the drilled formation, the temperature of the drill bit cutting area and the surrounding formation, the humidity value of the soil or gas, and the pressure value during the drilling process.

[0020] Specifically, due to the limited space of the drill bit, it is necessary to reasonably arrange the positions of each sensor. In the drill bit design, the reasonable layout of the sensors is crucial for protecting the equipment and accurately measuring geological parameters. The sensors can be arranged in different parts of the drill bit.

[0021] Specifically, a geological sensor: It can be embedded at the front end of the drill bit to measure the resistivity of soil or rock in real time during drilling to determine geological characteristics.

[0022] Position of the geological sensor (resistivity sensor): It can be embedded at the front end of the drill bit or on the front side of the drill bit edge. Protection measures: Design a protective cover around the sensor to protect it from the direct impact generated during drilling. Avoid exposing it to areas in direct contact with soil or rock, especially under harder geological conditions. Advantage: The front-end position enables it to collect resistivity data of the drilled formation in real time and directly, helping to obtain geological characteristic information in a timely manner.

[0023] Temperature sensor: Placed inside the drill bit, close to the cutting area, to monitor the temperature change of the drill bit in real time.

[0024] Humidity sensor: It can be integrated on a certain side of the drill bit to detect the humidity of the surrounding soil or moisture.

[0025] Pressure sensor: Placed in an area where the pressure during drilling can be detected, usually at the rear of the drill bit or at the connection part with the drill pipe.

[0026] Specifically, the geological sensor uses a resistivity sensor, which is set at the front end or the front side of the edge of the drill bit; and is equipped with a protective cover; measurement range: 0 - 2000 Ω·m; accuracy: ±1%; The temperature sensor uses a PT100 platinum resistance temperature sensor, which is set inside the drill bit close to the cutting area; is encapsulated with high-temperature resistant materials and equipped with a heat dissipation structure; measurement range: -50°C to 200°C; accuracy: ±0.5°C; Position of the temperature sensor: It should be placed at an internal position close to the cutting area to ensure that the temperature change during the cutting process can be directly monitored. Protection measures: Encapsulate it with high-temperature resistant materials to cope with the high temperature during the cutting process of the drill bit, and a heat dissipation structure can also be set to slow down the overheating of the sensor. Advantage: Real-time monitoring of the temperature change can effectively avoid equipment damage caused by overheating and improve the drilling efficiency.

[0027] The humidity sensor uses a capacitive humidity sensor, which is set on the outer side of the drill bit (towards the direction of moisture contact), and is encapsulated with waterproof materials to prevent short circuits; measurement range: 0% - 100% relative humidity; accuracy: ±3%; Position of the humidity sensor: It can be integrated on a certain outer side of the drill bit, towards the direction where it may come into contact with moisture or wet soil. Protection measures: Encapsulate the sensor with waterproof materials to prevent moisture from directly causing short circuits or damage. At the same time, ensure that its position will not be blocked by the cutting movement of the drill bit. Advantage: This position helps to obtain the humidity of the surrounding environment in real time, which is helpful for understanding soil characteristics and the suitability of drilling.

[0028] The pressure sensor uses a piezoresistive pressure sensor and is set at the rear of the drill bit or the connection with the drill pipe. It has an anti-seismic structure and is protected from exposure to the cutting surface. Measurement range: 0 - 10 MPa; Accuracy: ±0.5%; Position of the pressure sensor: Placed at the rear of the drill bit or the connection with the drill pipe to monitor the reverse pressure change. Protection measures: The pressure sensor should have an anti-seismic structure and should not be directly exposed to the cutting surface to prevent damage under high pressure and high friction. At the same time, optimize the position to avoid interference with other sensors. Advantage: It can accurately monitor the pressure change during drilling, helping to judge the working state of the drill bit and the formation characteristics.

[0029] Comprehensively consider wiring and signal transmission: During the layout process, the wiring of sensor signals and data transmission need to be considered, and try to avoid high-temperature and high-pressure areas to ensure signal stability. Avoid mutual interference: A certain distance should be maintained between sensors to avoid electromagnetic interference and mechanical interference during operation, ensuring the accuracy of data. Regular calibration: All sensors should be calibrated before use and at certain time intervals to ensure the accuracy and reliability of data. Such a layout design can maximize the protection of sensors and at the same time ensure that key parameters during drilling can be accurately monitored, thereby improving the efficiency and safety of drilling.

[0030] All sensors are connected to the central processing unit through a data acquisition module to ensure real-time data transmission and fast response.

[0031] Specifically, each sensor is connected to the central processing unit (CPU) through a data acquisition module. The data acquisition module can be a microcontroller or data acquisition card with multi-channel input, capable of receiving signals from different sensors simultaneously.

[0032] Signal preprocessing: To ensure the accuracy of the collected data, it may be necessary to preprocess the sensor signals, such as amplification, filtering, and analog-to-digital conversion (ADC). Adapting different types of signals (analog and digital) is the key.

[0033] Specifically, the data transmission module uses wireless / wired communication: The data acquisition module can transmit data to the central processing unit through wireless communication (such as Bluetooth, Wi-Fi) or wired communication (such as USB, RS-485). Wireless communication can reduce the interference of connecting cables, especially when the drilling depth increases.

[0034] Real-time data processing: The central processing unit is responsible for receiving, processing, and analyzing sensor data, and converting the results into available information, such as real-time display, alarm triggering, etc.

[0035] Specifically, the processor of the central processing unit is a multi-core ARM processor with a main frequency of 1.8 GHz, a memory of 8 GB RAM, a storage of 128 GB SSD, and an operating system of embedded Linux operating system.

[0036] AI algorithm: Real-time analysis of the collected data, and genetic algorithm and particle swarm optimization algorithm are used for real-time construction optimization. The computer can perform real-time monitoring or automatic feedback control according to the changes in sensor data.

[0037] Specifically, the decision support module uses genetic algorithm and particle swarm optimization algorithm to optimize the construction plan. The decision support module has a data storage capacity of 1 TB.

[0038] The decision support system is used to generate an optimized construction plan, and its parameters include: historical data storage; storage capacity: 1 TB; data backup period: full backup every 24 hours; optimization algorithm: genetic algorithm and particle swarm optimization algorithm are used to optimize the construction plan.

[0039] Specifically, the main steps of the genetic algorithm are as follows: 1) Population initialization: Randomly generate a set of potential solutions, called "individuals" or "chromosomes". Each individual represents a complete construction plan.

[0040] 2) Fitness evaluation: For each individual, calculate the fitness value according to the predefined objective function (such as cost, construction period, resource utilization rate, etc.). The fitness value reflects the quality of each plan.

[0041] 3) Selection operation: Select individuals to enter the next generation according to the fitness value. Common methods include roulette wheel selection, tournament selection, etc. Individuals with higher fitness have a higher probability of being selected to retain their excellent characteristics.

[0042] 4) Crossover operation: Cross the selected individuals to generate new individuals (offspring). The crossover operation simulates the recombination of genes in the biological inheritance process to produce new solutions. Common crossover methods include single-point crossover, two-point crossover, etc.

[0043] 5) Mutation operation: Randomly mutate the newly generated individuals to increase the diversity of the population and avoid premature convergence to local optimal solutions. Mutation can be achieved by randomly adjusting some values of individual genes.

[0044] 6) Replacement: Replace the new generation of individuals with the current population to form a new population.

[0045] 7) Termination condition: Set termination conditions (such as reaching the maximum number of generations, the fitness reaching a certain threshold, etc.) to determine when the algorithm stops.

[0046] The main steps of the particle swarm optimization algorithm are as follows: 1) Initialization: Randomly generate a group of particles (i.e., potential solutions), and each particle has a position and a velocity. The position represents the current solution, and the velocity is used to adjust the position of the particle. The velocity update formula is: .

[0047] 2) Fitness evaluation: Calculate the fitness value of each particle, similar to the genetic algorithm.

[0048] 3) Personal best and global best: Each particle remembers its historical best position (personal best) and the best position of the entire particle swarm (global best).

[0049] 4) Velocity update: Update the velocity of the particle according to the personal best and the global best.

[0050] 5) Position update: Adjust the position of the particle according to the updated velocity: ; 6) Termination condition: Similar to the genetic algorithm, set a termination condition to determine when to stop the optimization process.

[0051] Specifically, it further includes a display module, which is connected to the central processing unit. The display screen of the display module is a 7-inch touch liquid crystal screen with a resolution of 800×480 pixels. The function module includes real-time data monitoring, audible and visual alarm, and operation record functions.

[0052] The embodiment of the present invention provides a tunnel drilling rig integrating advanced sensing and intelligent decision-making technologies, aiming to optimize the tunnel construction efficiency and safety in complex underground environments. Through the above-mentioned detailed parameters and technical solutions, the tunnel intelligent sensing drilling rig of the embodiment of the present invention can significantly improve the safety and efficiency of tunnel construction, and at the same time provide a practical solution for the intelligent development of tunnel engineering, with broad market application prospects.

[0053] In a specific embodiment of the present invention, as Figure 1 shown, the internal structure and connection schematic diagram of the power transmission part of the drilling rig shows the internal structure and connection relationship of the power transmission part of the tunnel intelligent sensing drilling rig. From left to right: Motor: Located on the far left, it is the power source of the entire power transmission system and provides power for the operation of the drilling rig.

[0054] Coupling: Connects the motor and the T-shaped screw, plays a role in transmitting power, and ensures that the power can be smoothly transmitted from the motor to the T-shaped screw.

[0055] T-shaped screw: On the right side of the coupling, it converts the rotational motion of the motor into a linear motion through its own rotation, thereby pushing the drilling rig to perform a propulsion action.

[0056] Guide rail: Arranged in parallel with the T-shaped screw rod, it provides guidance for the advancing movement of the drill rig, ensuring the linearity and stability of the movement.

[0057] T-shaped nut: Matches with the T-shaped screw rod. When the T-shaped screw rod rotates, the T-shaped nut moves linearly along the screw rod, driving other components of the drill rig to move.

[0058] Pressure sensor: Located near the T-shaped nut, it is used to monitor the pressure situation during the advancement process and obtain drilling pressure data.

[0059] Rotating bearing: Plays a role in supporting and reducing the friction of rotating components, making the power transmission process smoother.

[0060] As Figure 2 shown, it is a schematic diagram of the drilling process of the drill rig and the monitored drilling parameters and data transmission, presenting the drilling process of the drill rig, the monitored drilling parameters, and the relevant situation of data transmission.

[0061] Drilling process: From left to right, the impact piston generates impact force through reciprocating motion, strikes the shank end, the shank end transmits the impact force to the drill rod, and the drill rod then drives the drill bit to break the rock, achieving drilling. At the same time, the drill rig has advancing and rotating actions. Advancing makes the drill bit continuously approach the rock, and rotation assists the drill bit in breaking the rock. In addition, cuttings are generated during the drilling process and are discharged by flushing.

[0062] Monitoring of drilling parameters: Multiple sensors are arranged to monitor the drilling parameters, including the pressure sensor monitoring the impact pressure and drilling pressure, as well as the monitoring of parameters such as drilling speed, rotation speed, and rotation pressure. In addition, humidity sensors, geological sensors, and temperature sensors are also provided near the drill bit to sense information such as humidity, geological conditions, and temperature at the drilling site.

[0063] Data transmission: The optical-electronic speed sensor collects speed data and transmits it to the speed module. The speed module transmits the data to the computer through a USB cable. The computer can also perform network connection through a network cable to achieve further data transmission or interaction with other devices. In addition, the power supply module provides power support for the entire system.

[0064] In this specification, each embodiment is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0065] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent perception drill for tunnels, characterized in that, Including: A drilling rig main body, an intelligent sensing module, a data acquisition module, a data transmission module, a central processing unit, and a decision support module; The intelligent sensing module is integrated within the drilling rig main body and is used to monitor drilling data; The data acquisition module is connected to the intelligent sensing module, is used to acquire drilling data, and preprocesses the drilling data; The data transmission module is used to transmit the preprocessed drilling data to the central processing unit in real time; The central processing unit interacts with the decision support module, generates an optimized construction plan, and generates control instructions to be sent to the actuator of the drilling rig main body.

2. The intelligent perception tunnel drilling rig according to claim 1, wherein The decision support module uses a genetic algorithm and a particle swarm optimization algorithm to optimize the construction plan.

3. The intelligent perception tunnel drilling rig according to claim 1, characterized in that, The central processing unit includes a multi-core ARM processor with a main frequency of 1.8 GHz, 8 GB of RAM, 128 GB of SSD storage, and an embedded Linux operating system.

4. The intelligent perception tunnel drilling rig according to claim 1, characterized in that, The intelligent sensing module includes: a geological sensor, a temperature sensor, a humidity sensor, and a pressure sensor; they respectively measure the resistivity of the drilled formation, the temperature of the drill bit cutting area and the surrounding formation, the humidity value of the soil or gas, and the pressure value during the drilling process.

5. The intelligent perception tunnel drilling rig according to claim 4, characterized in that, The geological sensor uses a resistivity sensor and is set at the front end or the front side of the edge of the drill bit; The temperature sensor uses a PT100 platinum resistance temperature sensor and is set inside the drill bit near the cutting area; The humidity sensor uses a capacitive humidity sensor and is set on the outer side of the drill bit; The pressure sensor uses a piezoresistive pressure sensor and is set at the rear of the drill bit or at the connection with the drill pipe.

6. The intelligent tunnel perception drill according to claim 1, characterized in that, The central processing unit uses a neural network model to perform real-time analysis on the acquired data, and the neural network model includes a convolutional neural network and a recurrent neural network.

7. The intelligent perception tunneling drill according to claim 1, wherein It further includes a display module. The display module is connected to the central processing unit, and the display screen of the display module is a touch liquid crystal screen.

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