Intermittent spiral heading machine and control method

Abstract

The invention provides an intermittent spiral heading machine and a control method, and relates to the technical field of engineering machinery. According to the method, the tunneling parameters serve as feedback, PI calculation is conducted on the control parameters, the initial control parameters of the next period are obtained, influences of formation resistance, rotation torque and the vibration condition are considered, and the initial control parameters are made to adapt to the actual condition of the current tunneling face. Afterwards, the initial control parameters are optimized through the preset optimization model, and the preset optimization model is obtained by training on the basis of the tunneling parameters and the control parameters in the historical period, so that the actual regulation and control condition in the tunneling process in the historical period is fully considered; therefore, the target control parameters better conform to the actual situation of the current tunneling face, the regulation and control precision of the spiral tunneling machine is improved, high-precision control over the spiral tunneling machine is achieved, the problems of drill bit deviation and unstable torque are solved, and the tunneling efficiency of the spiral tunneling machine is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering machinery, and in particular to an intermittent screw boring machine and a control method thereof. Background Art

[0002] In the engineering fields of tunneling, mining and underground pipeline construction, the widely used tunnel boring machines mainly include shield machines, full-face tunnel boring machines and horizontal spiral drilling machines. These devices are usually used to excavate rock, soil and other strata, and complete the drilling operation of tunneling or underground engineering by mechanical means. However, when the existing tunneling equipment operates under complex geological conditions (such as multi-layer geological structures, hard rock formations, uneven geology, etc.), there are problems such as serious deviation of the tunneling path and low tunneling efficiency.

[0003] The complex and changeable geological environment in the tunnel leads to inaccurate control of the drill bit position, angle and path of the drilling rig. For example, the drill bit thrust required for soft soil and hard rock is different, and the geology in different areas ahead of the excavation is uneven, so the corresponding thrust and speed are different. When the thrust and speed adapted to the soft soil are used to deal with the hard rock, it is easy to cause problems such as drill bit deviation and torque instability, resulting in the excavation path deviating from the predetermined target and reduced excavation efficiency. Summary of the invention

[0004] The present invention provides an intermittent screw boring machine and a control method, which can realize high-precision control of the screw boring machine and improve the boring efficiency of the screw boring machine.

[0005] In the first aspect, the present invention provides a control method for an intermittent spiral boring machine, which includes a spiral drilling machine module, a sensor module and a control module. The method includes: detecting the excavation parameters and control parameters of the spiral drilling machine module, the excavation parameters include formation resistance, rotation torque, vibration frequency and vibration amplitude; the control parameters include propulsion force, rotation speed and drilling path; taking the excavation parameters as feedback, performing PI calculation on the control parameters to obtain the initial control parameters of the next cycle; optimizing the control parameters based on the excavation parameters, control parameters and initial control parameters, and a preset optimization model to obtain the target control parameters of the next cycle, the preset optimization model is obtained by training based on the excavation parameters and control parameters in the historical period; based on the target control parameters, controlling the micro horizontal spiral drilling machine module to excavate.

[0006] In the second aspect, an embodiment of the present invention provides a control module for an intermittent spiral tunneling machine, which includes: a communication unit for detecting tunneling parameters and control parameters of the spiral drilling machine module, the tunneling parameters including formation resistance, rotational torque, vibration frequency and vibration amplitude; control parameters including thrust, rotation speed and drilling path; a processing unit for performing PI calculation on the control parameters with tunneling parameters as feedback to obtain initial control parameters for the next cycle; optimizing the control parameters based on the tunneling parameters, control parameters and initial control parameters, and a preset optimization model to obtain target control parameters for the next cycle, the preset optimization model being obtained by training based on tunneling parameters and control parameters in a historical period; and controlling the micro horizontal spiral drilling machine module to perform tunneling based on the target control parameters.

[0007] In a third aspect, an embodiment of the present invention provides an intermittent spiral tunneling machine, which includes an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor is used to call and run the computer program stored in the memory to perform the steps of the method described in the first aspect and any possible implementation method of the first aspect.

[0008] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and wherein when the computer program is executed by a processor, the steps of the method described in the first aspect and any possible implementation method of the first aspect are implemented.

[0009] The present invention provides an intermittent spiral boring machine and control method. The present invention first uses the excavation parameters as feedback, performs PI calculation on the control parameters, obtains the initial control parameters of the next cycle, and considers the influence of the formation resistance, rotation torque and vibration conditions, so that the initial control parameters adapt to the actual conditions of the current excavation surface. Afterwards, the present invention optimizes the initial control parameters through a preset optimization model. Since the preset optimization model is obtained by training based on the excavation parameters and control parameters in the historical period, the actual control conditions in the excavation process in the historical period are fully considered, so that the target control parameters are more in line with the actual conditions of the current excavation surface, improve the control accuracy of the spiral boring machine, realize high-precision control of the spiral boring machine, avoid the problems of drill bit offset and torque instability, and improve the excavation efficiency of the spiral boring machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0011] Figure 1 It is a structural schematic diagram of an intermittent spiral boring machine provided by an embodiment of the present invention;

[0012] Figure 2 It is a flow chart of a control method for an intermittent screw boring machine provided by an embodiment of the present invention;

[0013] Figure 3 It is a structural schematic diagram of a control module of an intermittent spiral boring machine provided by an embodiment of the present invention;

[0014] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0015] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0016] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be described through specific embodiments in conjunction with the accompanying drawings of the present invention.

[0017] like Figure 1 As shown, an embodiment of the present invention provides an intermittent screw boring machine, which includes a screw drilling machine module, a sensor module and a control module.

[0018] The auger drill module, i.e. the micro horizontal auger drill module, is used to drive the rotation and propulsion of the auger drill head. The micro horizontal auger drill module includes a high-rigidity micro transmission unit, a servo electric control drive unit and a micro auger drill head unit.

[0019] The high-rigidity micro transmission unit is composed of a multi-stage gear transmission assembly. The gear assembly is made of high-strength alloy material and drives the rotation and propulsion of the spiral drill bit through multi-stage precision transmission. The design of each gear has been precisely geometrically optimized to ensure the high efficiency and stability of the transmission system under high load conditions. The multi-stage transmission design ensures that the rotation and propulsion of the drill bit can adapt to different formation conditions by reducing torque loss step by step.

[0020] The servo electronic drive unit monitors the drill position and angle in real time through a high-resolution encoder, and dynamically adjusts the drill movement in combination with a closed-loop control algorithm.

[0021] The closed-loop control algorithm is used to adjust the motion path and rotation speed of the drill bit in real time. Closed-loop control refers to correcting operating errors through a feedback system, and the formula is as follows:

[0022]

[0023] Among them, u(t) is the control output, e(t) is the error between the target value and the actual value, Kp is the proportional gain, Ki is the integral gain, and Kd is the differential gain.

[0024] For example, the embodiment of the present invention can calculate the gap (error) between the current state of the drill bit and the target state in real time based on the drilling speed, torque and vibration data monitored by the sensor. Through the PID algorithm, the control system dynamically adjusts the propulsion force and drilling speed to keep the drill bit in the best state at all times, thereby preventing equipment damage or deviation from the path due to pressure fluctuations or torque anomalies.

[0025] The micro spiral drill unit has a multi-layer wear-resistant alloy coating on its surface, which increases the service life of the drill bit and reduces the risk of wear during drilling. A spiral blade is provided on the surface of the drill bit. The geometry of the spiral blade is carefully designed to enable it to efficiently cut different types of geological materials (such as rock, sand, etc.) during drilling, and transport the generated debris along the spiral groove on the surface of the drill bit to the chip removal module.

[0026] The geometry of the spiral blade is designed as follows:

[0027] Soft or mixed formations: Spiral angle: 35° to 45°. Front angle: 20° to 25°, back angle: 10°. Pitch: 120mm to 150mm. Spiral groove depth: 15mm to 20mm. This configuration helps improve chip removal efficiency and reduce friction between the drill bit and the formation, suitable for rapid drilling in soft soil or mixed geology.

[0028] Hard formation: Spiral angle: 15° to 25°. Front angle: 5° to 10°, back angle: 5° to 8°. Pitch: 30mm to 50mm. Spiral groove depth: 5mm to 10mm. This configuration provides better cutting stability and can reduce friction and resistance encountered during drilling, suitable for rock and hard formations.

[0029] The sensor monitoring module is used to monitor the real-time operating parameters of pressure, torque and vibration during drilling. The sensor monitoring module includes a pressure sensor, a torque sensor and a vibration sensor.

[0030] The pressure sensor is installed near the drill bit and is used to detect in real time the formation resistance encountered by the drill bit during drilling. When pressure changes are detected, the sensor will feed back to the control module to adjust the thrust or drilling speed to prevent excessive load or drill bit jamming.

[0031] The torque sensor is integrated on the drive shaft and is used to detect real-time torque changes on the drive shaft. The torque sensor data plays an important role in determining whether the drill bit encounters hard materials in the formation or the drill bit is stuck, and is dynamically adjusted through the control system.

[0032] The vibration sensor is installed in the transmission mechanism to detect the vibration frequency and amplitude during drilling. Through the vibration data, the control system can determine whether the drilling is stable and adjust the drilling parameters or issue a fault alarm in time when abnormal vibration occurs.

[0033] The control module is connected to the sensor monitoring module and is used to adjust the control parameters of the drill bit according to the feedback data of the sensor monitoring module. The control parameters include drilling speed, propulsion force and drilling path.

[0034] The control module includes a multi-parameter real-time control unit, an adaptive control unit, a path planning unit and an anomaly detection unit.

[0035] The multi-parameter real-time control unit adjusts the thrust, speed and drilling path of the drill bit in real time according to the pressure, torque and vibration data fed back by the sensor; the unit automatically adjusts the thrust, speed and drilling path of the drill bit according to the control algorithm. The unit can use fuzzy control algorithm to handle complex drilling situations. The fuzzy control rules are as follows:

[0036]

[0037] Where u is the control output, μ i is the membership function, f i is the control rule. This formula is used to deal with control decisions under uncertainty and fuzzy conditions.

[0038] Implementation of fuzzy control rules: The fuzzy controller outputs appropriate control instructions (such as drilling speed and thrust adjustment) based on the input fuzzy variables, such as pressure, torque, vibration, etc. of the drill bit. Each input variable can be fuzzified into a fuzzy language set such as "low, medium, high" according to its value.

[0039] Rule example: Assuming the input variables are "Pressure" and "Torque", and the output variables are "Drilling Speed" and "Thrust Force", the fuzzy control rule can be defined as:

[0040] Rule 1: If pressure is high and torque is high, then drilling speed is low and thrust is low.

[0041] Rule 2: If pressure is low and torque is medium, then drilling speed is high and thrust is medium.

[0042] Rule 3: If vibration is high, then the drilling rate is reduced.

[0043] Fuzzy reasoning process: The fuzzy controller calculates the actual drilling speed and thrust based on the current sensor feedback data through fuzzification, rule reasoning and defuzzification. In this way, the roadheader can smoothly adjust the operating parameters when the formation conditions are uncertain.

[0044] The adaptive control unit, based on the deep learning algorithm, optimizes the drilling parameters by analyzing the formation feedback data and makes real-time adjustments based on the actual drilling status. Through the deep neural network (DNN), the adaptive control unit can analyze the formation feedback data and adjust the propulsion force and speed. The loss function of DNN is defined as follows:

[0045]

[0046] Among them, L(θ): loss function, which represents the error between the predicted output of the neural network and the real data; N: number of samples; yi: actual drilling parameters (such as optimal thrust or drilling speed); f(xi; θ): predicted output calculated by the neural network based on the input xi, where θ is the weight parameter of the model.

[0047] For example, in the embodiment of the present invention, during the operation of an intermittent screw boring machine, the DNN dynamically updates the model parameter θ based on historical drilling data and real-time sensor feedback (such as pressure, torque, and vibration). By minimizing the loss function, the DNN can output more accurate control parameters such as drilling speed and thrust under different formation conditions to ensure the high efficiency of the equipment in complex formations.

[0048] The path planning unit uses a reinforcement learning algorithm to calculate the real-time optimized drilling path through the Bellman equation; the Bellman equation is as follows:

[0049]

[0050] Among them, V(s) is the value of state s, that is, the comprehensive benefit of performing drilling actions under the current formation state, R(s,a) is the immediate reward value after performing action a, which represents the drilling effect brought by the action under the current formation (such as smooth passage of the path, avoiding obstacles, etc.), γ is the discount factor, which is used to balance current benefits and future benefits, and P(s′|s,a) is the state transition probability, which is the probability of the system transferring from state s to state s′ after performing action a, representing the possible changes under different formation conditions. This algorithm is used to update the drilling path in real time to avoid obstacles.

[0051] Application in tunnel boring machines: The reinforcement learning algorithm uses data collected by sensors to evaluate the effect of each step in the drilling process and predict the potential impact of different operations (such as adjusting the drill bit angle and changing the propulsion force). The path planning unit uses this algorithm to adjust the drill bit path in real time to avoid uneven formations such as rock cracks and hard obstacles to ensure the optimization of the drilling path.

[0052] The fuzzy control rules are responsible for outputting adjustment instructions according to the fuzzy language set when the real-time feedback data fluctuates, so that parameters such as drilling speed and thrust can be flexibly adjusted under uncertain or complex geological conditions.

[0053] The loss function of DNN is used to train the adaptive control model to ensure that the drilling machine adjusts the thrust and drilling speed according to historical data and real-time feedback during actual operation, thereby minimizing drill bit wear and improving drilling efficiency.

[0054] The Bellman equation is used in path planning to calculate the optimal drilling path according to different conditions, so as to bypass complex stratum structures and achieve efficient and safe drilling.

[0055] The anomaly detection unit analyzes sensor data through the support vector machine (SVM) model, detects abnormal operating conditions, and automatically adjusts operating parameters. The decision function of SVM is:

[0056]

[0057] Where x: input data (such as torque, pressure, vibration), y: i The corresponding label (normal or abnormal), α i is the coefficient of the support vector, K(xi,x) is the kernel function used to calculate the similarity between different inputs, and b is the bias.

[0058] Application in roadheaders: SVM identifies drill wear, load changes in the drive train, and abnormal vibration patterns by analyzing real-time data from sensors. When an abnormality is detected, the control module automatically adjusts operating parameters and issues an alarm to prevent further damage to the equipment.

[0059] In some embodiments, the adaptive control unit also includes a deep neural network, which analyzes formation characteristics through a multi-layer perceptron model and adjusts the drilling parameters of the drill bit according to real-time formation feedback data.

[0060] The control module also includes a self-learning unit, which gradually optimizes the parameter adjustment model under different geological conditions based on historical drilling data collected in real time.

[0061] The self-learning unit optimizes the model based on historical drilling data. Through the self-learning algorithm, the self-learning unit can improve the system's adaptability to different geological conditions during continuous operation. The self-learning process can be described as:

[0062]

[0063] Among them, θ is the model parameter, η is the learning rate, is the gradient of the loss function, which represents the weight update after each training.

[0064] The intermittent screw boring machine further comprises an automatic chip removal module, which is used to remove the debris generated during the drilling process.

[0065] The automatic chip removal module includes a spiral chip removal unit and an automatic cleaning unit. The spiral chip removal unit is connected to the spiral drill bit and is provided with a high-friction spiral groove structure for removing chips during the drilling process; the structure transports the chips backward from the drill bit through rotation during the drilling process and removes them through the chip removal channel.

[0066] Integrated design of spiral blade and chip removal structure: The spiral blade is not only responsible for cutting formation materials, but also has the function of chip removal. The spiral blade is designed with a special spiral groove. The geometry of the spiral groove (such as pitch, groove depth, etc.) is carefully designed to smoothly discharge the cut debris from the borehole during drilling. The cut rock, soil and other materials are taken away from the drill bit along the spiral groove and discharged from the borehole through the chip removal channel.

[0067] Double helix structure: To improve chip removal efficiency, the spiral chip removal unit can be designed as a double helix structure, that is, two or more interlaced spiral grooves are arranged on the drill bit. The double helix design can remove the debris faster during the rotation of the drill bit and reduce the chip removal resistance. This design is particularly suitable for use in highly viscous soils or water-bearing formations.

[0068] Chip removal channel

[0069] Channel design: The chip removal channel is a key part of the automatic chip removal module, and its design directly affects the efficiency of chip removal. The chip removal channel is usually connected to the spiral chip removal unit. The diameter and length of the channel are designed according to the diameter and depth of the drill hole to ensure that there is no accumulation or blockage during chip removal.

[0070] Friction optimization of the inner wall of the channel: The inner wall of the chip removal channel has been specially treated with friction to reduce the resistance of the chips in the channel and ensure that the chips can be discharged smoothly. The inner wall surface is usually made of low-friction materials, such as coated wear-resistant steel or special plastics, to prevent drill chips from being retained in the chip removal channel.

[0071] Automatic cleaning unit, including mechanical scraper and airflow assisted chip removal layer, is used to prevent the accumulation of chips in the chip removal channel. The scraper is used to clean the chips accumulated in the chip removal channel.

[0072] Mechanical scraper: The automatic cleaning unit is equipped with a mechanical scraper system, which is installed in the chip removal channel and is responsible for regularly cleaning the accumulated debris in the chip removal channel. The scraper slides along the inner wall of the channel to physically clean the adhered or accumulated debris. The scraper is made of high-strength wear-resistant materials, such as cemented carbide or polymer composite materials, and can work stably for a long time in a high-wear environment.

[0073] Automatic start-stop mechanism: The cleaning process of the mechanical scraper is controlled by the system's intelligent start-stop mechanism. When the sensor detects that the accumulation of debris in the chip removal channel reaches a certain threshold, the system automatically starts the cleaning unit. When the scraper passes through the chip removal channel, it cleans out the accumulated chips in the channel in time to prevent the accumulation of debris from causing blockage.

[0074] The automatic chip removal module also includes an airflow assist unit, which is used to assist chip removal through high-pressure gas during drilling, blow away fine debris that is difficult to remove mechanically, ensure that the chip removal channel always remains unobstructed, and prevent debris from accumulating in the chip removal channel.

[0075] The air assist layer provides additional chip removal power through high-pressure air, which is particularly suitable for deep drilling or environments where debris is prone to accumulation. The system can effectively blow away fine debris in the channel to prevent channel blockage.

[0076] High-pressure gas supply system: The airflow assist layer is equipped with a high-pressure gas supply system, which usually uses compressed air or other gases. The gas enters the chip removal channel through a specially designed airflow channel, and the high-pressure airflow is used to blow the fine debris out of the chip removal channel.

[0077] Adjustable airflow: The airflow-assisted system can dynamically adjust the airflow pressure and speed according to the drilling depth, geological conditions and debris particle size, ensuring that the airflow-assisted chip removal effect can adapt to different geological conditions. For example, when the system is discharging clay or wet soil, the airflow speed may need to be increased, while in dry formations, the airflow speed can be appropriately reduced.

[0078] Optimized airflow direction: The design of the airflow assist layer takes into account the direction and distribution of the airflow. The airflow inlet position and angle are optimized to ensure that the airflow can effectively cover the entire cross-section of the chip removal channel, thereby maximizing the dispersion and cleaning of accumulated debris.

[0079] Sensor monitoring and feedback mechanism

[0080] To ensure that the chip removal module can continue to operate efficiently under different operating conditions, the system is equipped with multiple sensors to monitor the patency of the chip removal channel.

[0081] Pressure sensor: Installed in the chip discharge channel, it monitors the pressure of chip discharge in real time. If it detects that the chip discharge pressure is abnormally high, the system will automatically start the airflow auxiliary layer and mechanical scraper.

[0082] Chip flow monitoring sensor: monitors the chip flow through the chip removal channel. When the flow decreases or there is a tendency for clogging, the system will adjust the chip removal speed or start the cleaning device.

[0083] Feedback control mechanism: Based on the data feedback from the sensor, the control system can dynamically adjust the rotation speed of the spiral chip removal unit and the air pressure of the airflow assist layer to ensure that the chip removal channel always remains unobstructed.

[0084] Specific design and data of automatic chip removal module

[0085] Spiral Chip Conveyor Unit: Spiral Flute Width: Range: 10mm to 30mm. 10mm to 15mm: Suitable for hard formations to ensure that the drill strength is not reduced due to too wide a flute while still being able to evacuate chips effectively.

[0086] 20mm to 30mm: Suitable for softer or mixed formations, where wider grooves can increase chip evacuation.

[0087] Spiral groove depth: Range: 5mm to 20mm (consistent with the design of the spiral blade). 5mm to 10mm: Suitable for hard formations, this depth is enough to gradually discharge the debris during cutting, but will not weaken the overall strength of the drill bit. 10mm to 20mm: Suitable for soft formations or mixed geological conditions, the groove depth helps to speed up the chip removal speed.

[0088] Double spiral design: Spiral number: 2 to 3 spiral grooves, staggered on the drill surface, to enhance chip removal ability. 2 spiral grooves: suitable for general hard formations, to ensure a stable chip removal path. 3 spiral grooves: suitable for deep or soft formations, to increase the number of chip removal channels and improve chip removal efficiency.

[0089] Chip removal channel: Channel diameter: Range: 50mm to 200mm (designed according to the diameter of the drill hole). 50mm to 100mm: Suitable for small diameter drilling projects, usually used for smaller-scale drilling. 100mm to 200mm: Suitable for large diameter drilling, especially large-scale projects such as tunnel excavation, to ensure that the debris can be discharged quickly.

[0090] Channel length: Range: 500mm to 5000mm (designed according to the excavation depth). 500mm to 2000mm: Suitable for shallow drilling projects, the channel length is shorter and the debris accumulation is less. 2000mm to 5000mm: For deep drilling, the longer channel can ensure that the debris is discharged smoothly and will not be blocked even in complex geological conditions.

[0091] Channel inner wall friction coefficient: Range: 0.15 to 0.30 (using treated low friction material).

[0092] Lower friction coefficient (such as 0.15): suitable for efficient chip removal and reducing the retention of debris in the channel. It is usually used in formations that are prone to blockage, such as clay.

[0093] Higher friction coefficient (such as 0.30): suitable for formations with hard debris. Under such conditions, slightly higher friction helps control the discharge of debris but will not cause blockage.

[0094] Automatic cleaning unit: The size of the mechanical scraper: Range: The diameter is 90% to 95% of the channel diameter. For example, for a chip removal channel with a diameter of 100mm, the scraper diameter can be 90mm to 95mm, ensuring that the scraper can fully contact the inner wall and clean up most of the debris.

[0095] Scraper material thickness: Range: 5mm to 10mm. 5mm: Suitable for cleaning soft formations, the scraper is light and flexible. 10mm: Suitable for high-intensity chip removal in hard formations, wear-resistant and strong.

[0096] Cleaning cycle: Range: Start every 30 minutes to 120 minutes (automatically adjusted according to sensor feedback). 30 minutes: For formations with low chip removal efficiency or rapid chip accumulation to ensure that the channel is not blocked. 120 minutes: For formations with smooth chip removal to reduce unnecessary cleaning actions.

[0097] Airflow assisted layer: High pressure gas pressure: Range: 0.5MPa to 1.5MPa. 0.5MPa to 1.0MPa: Applicable to conventional soft formations, low pressure airflow can effectively discharge small debris. 1.0MPa to 1.5MPa: Applicable to deep or hard formations, high pressure airflow can more effectively clean the debris in the chip removal channel.

[0098] Air velocity: Range: 10m / s to 30m / s. 10m / s to 15m / s: Suitable for soft, loose soils, moderate air velocity can expel debris. 20m / s to 30m / s: Used in hard or wet and sticky formations, in these cases higher air velocity can prevent debris from adhering to the inner wall of the channel and effectively avoid blockage.

[0099] Airflow direction and angle: The airflow enters the chip removal channel at an angle of 30° to 45°, consistent with the direction of the spiral groove, ensuring that the airflow is consistent with the direction of chip discharge, maximizing the chip removal effect.

[0100] Sensor monitoring and feedback mechanism: Pressure sensor monitoring range: Range: 10kPa to 100kPa (used to monitor the pressure of debris accumulation in the chip removal channel). 10kPa to 50kPa: Suitable for smoother chip removal environment, can detect light accumulation of debris. 50kPa to 100kPa: Suitable for environments where the chip removal channel is easily blocked, the sensor can detect high pressure accumulation and trigger the cleaning system. Chip flow monitoring sensor range: Range: 5kg / h to 100kg / h (depending on the formation and the speed of chip generation).

[0101] 5kg / h to 20kg / h: Suitable for softer formations or loose soil. 50kg / h to 100kg / h: Suitable for hard rock or large volume debris discharge environment, ensuring that the system can adjust the chip discharge speed or start the airflow auxiliary layer in time.

[0102] The intermittent screw boring machine also includes a lubrication and cooling module. The lubrication and cooling module is used to keep the temperature and friction of the boring machine within a preset range through cooling and lubrication. The cooling system is responsible for controlling the temperature of the drill bit and servo drive system to prevent the equipment from failing due to high temperature. The system adopts a dual-circuit structure to cool key components separately.

[0103] The lubrication and cooling module includes a cooling circuit unit and a lubrication unit. The cooling circuit unit is used to cool the auger bit and the servo drive system. The cooling circuit unit consists of a dual-circuit structure, each circuit serves the cooling needs of different components; the unit is designed with a dual-circuit structure, which is used to cool the auger bit and the servo drive system. Each circuit is specially designed to ensure that the cooling needs of different components can be met. The flow rate and temperature of the coolant are adjusted by an automatic control system to prevent the equipment from running too long at high temperatures and causing wear. One circuit is specifically used to cool the auger bit, and the other is used to cool the servo drive system. Each circuit operates independently and is equipped with sensors and controllers to achieve dynamic temperature regulation.

[0104] Cooling circuit 1 (auger drill bit): This circuit provides cooling for the drill bit, which can quickly absorb heat during the cutting process of the drill bit to prevent excessive temperature from causing material performance degradation or excessive wear of the cutting edge. Coolant flow rate: 3L / min to 10L / min (automatically adjusted according to the operating temperature of the drill bit). Lower flow rate (3L / min to 5L / min): Suitable for general geological conditions, the temperature is controlled within an acceptable range. Higher flow rate (6L / min to 10L / min): Suitable for high friction formations, or to keep the drill bit temperature stable during long-term continuous operation.

[0105] Cooling circuit 2 (servo drive system): used to cool the servo motor and transmission mechanism. By reducing the temperature, the drive system is prevented from overheating and causing failure or accuracy problems. Coolant flow rate: 2L / min to 6L / min (adjusted according to the load of the servo system). Low flow rate (2L / min to 4L / min): suitable for servo system operation under normal load. High flow rate (4L / min to 6L / min): suitable for high load conditions, where additional cooling is required to ensure that the servo system does not overheat.

[0106] The control of coolant temperature is very important. The cooling system is equipped with a temperature sensor and a regulation mechanism to dynamically adjust the coolant temperature to ensure that it remains within the appropriate range. Coolant temperature range: 10°C to 50°C.

[0107] 10℃ to 20℃: Used in high-temperature drilling scenarios to quickly reduce the device temperature.

[0108] 30℃ to 50℃: The temperature range under normal operation, ensuring that the equipment operating temperature is within the optimal range to avoid material performance degradation.

[0109] Heat recovery device: A heat recovery device can also be integrated into the cooling system to recover the waste heat generated by the auger bit and use it to preheat the coolant, thereby improving energy efficiency. Heat recovery efficiency: 30% to 50%.

[0110] Lower efficiency (30%): used for general drilling operations, mainly for energy conservation.

[0111] Higher efficiency (50%): Suitable for long-term working environment, the heat recovery system can effectively reduce energy consumption and reduce the temperature regulation cost of the coolant.

[0112] The lubrication unit automatically adjusts the amount of lubricant injection based on real-time friction monitoring results. The lubrication unit's sensors monitor the friction conditions in the system in real time and adjust the lubricant injection according to the preset friction coefficient range to ensure continuous and stable operation of the equipment.

[0113] The main function of the lubrication system is to reduce the friction between the drill bit and the formation and the transmission mechanism, thereby reducing equipment wear and extending equipment life. The design of the lubrication system must be able to adapt to changes in different geological conditions and ensure that the equipment operates in the best condition through real-time adjustment.

[0114] Active lubrication unit: The lubrication system automatically adjusts the amount of lubricant sprayed based on the real-time feedback data from the sensor (such as friction coefficient and temperature) to ensure that the surface friction of the equipment is maintained within a reasonable range. The lubricant is sprayed directly to the part where the spiral blade contacts the formation and the key parts of the transmission system. Lubricant spray volume: 10mL / min to 50mL / min.

[0115] 10mL / min to 20mL / min: Suitable for soft or low-wear formations with low lubrication requirements.

[0116] 30mL / min to 50mL / min: Suitable for high-wear or hard formations that require more lubricant to reduce friction.

[0117] Lubricant type: Depending on the geological conditions and operating environment, the lubrication system can use different types of lubricants, such as high-viscosity lubricants or solid lubricants. High-viscosity lubricants: suitable for high-load operations, able to maintain stable lubrication performance under high temperature and high pressure environments. Viscosity grades: ISOVG220 to ISOVG460.

[0118] ISOVG220: Suitable for medium load conditions, can reduce blade wear and ensure smooth drilling.

[0119] ISOVG460: Suitable for high-load and high-temperature working conditions, especially in hard rock formations, and can effectively protect the transmission system and drill bit.

[0120] Solid lubricants: such as graphite or molybdenum disulfide, are suitable for extreme environments, especially when working in high temperature or chemically corrosive environments.

[0121] Sensor monitoring and feedback mechanism: The lubrication and cooling module is equipped with multiple sensors to monitor the friction and temperature conditions during equipment operation, ensuring that the system automatically adjusts the injection amount of lubricant and the flow rate of coolant based on real-time data.

[0122] Temperature sensor: used to monitor the temperature of the drill bit, servo system and coolant in real time to ensure that each component remains within the optimal operating temperature range. Temperature sensor measurement range: 0℃ to 150℃. Drill bit temperature monitoring: When the temperature exceeds 60℃, the cooling system automatically increases the flow rate to prevent the equipment from failing due to overheating. Servo system temperature monitoring: Ensure that the servo motor temperature remains below 50℃ to avoid efficiency loss due to overheating.

[0123] Friction sensor: The friction sensor can detect the friction coefficient between the drill bit and the formation and the transmission system, and timely feedback the friction status so that the lubrication system can adjust the lubricant injection amount in real time. Friction coefficient monitoring range: 0.05 to 0.50. 0.05 to 0.20: suitable for environments with less friction and lower lubricant requirements. 0.30 to 0.50: suitable for high friction environments, such as hard formations or high-load operations, and the lubrication system automatically increases the lubricant injection amount.

[0124] The intermittent spiral tunneling machine provided by the present invention realizes high-precision control of the drill bit position, angle and drilling path through the precise coordination of the micro horizontal spiral drilling machine module and the servo electric control drive system, ensuring the stable and efficient operation of the drill bit under various complex formation conditions, which not only improves the tunneling efficiency but also increases the life of the equipment.

[0125] The present invention introduces a deep neural network algorithm and an adaptive control unit, which can automatically adjust the drilling speed, thrust and drilling path of the drill bit according to real-time formation feedback and historical data. Compared with the existing fixed parameter excavation method, this adaptive adjustment improves the adaptability of the equipment under different geological conditions and ensures the stability and continuity of the drilling process. The deep neural network analyzes the formation characteristics through a multi-layer perceptron model and adjusts the drilling parameters of the drill bit according to the real-time formation feedback data.

[0126] The automatic chip removal module of the present invention is designed with a spiral chip removal channel and an airflow auxiliary layer, which can efficiently remove chips during drilling, prevent chips from accumulating and blocking the channel, and ensure smooth chip removal. Compared with traditional chip removal systems, the chip removal efficiency of the present invention is significantly improved, reducing the frequency of equipment downtime and maintenance caused by chip accumulation.

[0127] based on Figure 1 The intermittent auger shown, such as Figure 2 As shown, an embodiment of the present invention provides a control method for an intermittent screw boring machine. The control method includes steps S101-S104.

[0128] S101, detecting the excavation parameters and control parameters of the spiral drilling machine module.

[0129] In the embodiment of the present application, the drilling parameters include formation resistance, rotation torque, vibration frequency and vibration amplitude. The control parameters include propulsion force, rotation speed and drilling path.

[0130] S102, using the excavation parameters as feedback, performing PI calculation on the control parameters to obtain the initial control parameters for the next cycle.

[0131] As a possible implementation manner, step S102 may be specifically implemented as steps S1021 - S1022 .

[0132] S1021. Determine a control error based on the excavation parameters and the control parameters.

[0133] S1022. Perform PI calculation based on the control error to determine the initial control parameters for the next cycle.

[0134] S103, based on the excavation parameters, control parameters and initial control parameters, and a preset optimization model, the control parameters are optimized to obtain target control parameters for the next cycle.

[0135] In the embodiment of the present application, the preset optimization model is obtained by training based on the excavation parameters and control parameters in the historical period.

[0136] As a possible implementation manner, step S103 may be specifically implemented as steps S1031 - S1032 .

[0137] S1031, generating a tunneling vector based on the tunneling parameter, the control parameter and the initial control parameter;

[0138] S1032. Determine the target control parameters for the next cycle based on the tunneling vector and the preset optimization model.

[0139] S104, based on the target control parameters, controlling the micro horizontal auger drilling machine module to perform excavation.

[0140] As a possible implementation manner, step S104 may be specifically implemented as steps S1041 - S1042 .

[0141] S1041. Determine a target area on the current excavation surface based on the drilling path in the target control parameters.

[0142] S1042, control the micro horizontal spiral drilling machine module to move to the target area.

[0143] S1043. Based on the thrust and rotation speed in the target control parameters, determine the target rotation speed and target thrust of the drill bit in the micro horizontal auger drilling machine module.

[0144] S1044, controlling the operating state of the drill bit in the micro horizontal spiral drilling machine module to a target rotation speed and a target propulsion force.

[0145] S1045, control the micro horizontal spiral drilling machine module to dig forward.

[0146] The present invention provides a control method for an intermittent spiral boring machine. First, the excavation parameters are used as feedback, and the control parameters are calculated by PI to obtain the initial control parameters of the next cycle. The influence of the formation resistance, the rotation torque and the vibration is considered, so that the initial control parameters are adapted to the actual situation of the current excavation surface. Afterwards, the present invention optimizes the initial control parameters through a preset optimization model. Since the preset optimization model is obtained by training based on the excavation parameters and the control parameters in the historical period, the actual regulation and control situation in the excavation process in the historical period is fully considered, so that the target control parameters are more in line with the actual situation of the current excavation surface, the regulation and control accuracy of the spiral boring machine is improved, the high-precision control of the spiral boring machine is realized, the drill bit offset and torque instability problems are avoided, and the excavation efficiency of the spiral boring machine is improved.

[0147] Optionally, the control method for an intermittent screw boring machine provided in an embodiment of the present invention further includes steps S201 to S207 before step S103.

[0148] S201. Obtaining the tunneling parameters and control parameters of the intermittent screw tunneling machine in the historical period.

[0149] S202, dividing the excavation parameters and control parameters in the historical period into time windows to obtain the excavation parameters and control parameters in multiple periods.

[0150] S203: Perform PI calculation based on the excavation parameters and control parameters of the first cycle to obtain initial control parameters of the second cycle.

[0151] In some embodiments, the first cycle is any cycle among a plurality of cycles, and the second cycle is a cycle next to the first cycle.

[0152] S204. Determine the excavation vector of the first cycle based on the excavation parameters and control parameters of the first cycle and the initial control parameters of the second cycle.

[0153] S205. Determine target control parameters of the second cycle based on the excavation parameters of the second cycle.

[0154] S206, constructing a plurality of training samples by taking the excavation vector of each cycle in the plurality of cycles as input and taking the target control parameter of the next cycle of each cycle as output.

[0155] S207: Based on multiple training samples, neural network training is performed to obtain a preset optimization model.

[0156] Exemplarily, step S207 may be specifically implemented as steps A1-A3.

[0157] A1. Based on multiple training samples, neural network training is performed to obtain an initial model.

[0158] A2. Use the initial model as the teacher model and the model with the same depth as the initial model as the student model to construct a teacher-student model.

[0159] A3. Based on multiple training samples, knowledge distillation training is performed on the student model in the teacher-student model to obtain a preset optimization model.

[0160] In this way, the present invention obtains a preset optimization model by training a neural network on historical data, which fully considers the actual control conditions during the excavation process in the historical period, makes the target control parameters more in line with the actual conditions of the current excavation face, and improves the control accuracy of the spiral tunnel boring machine.

[0161] Optionally, the control method of the intermittent screw boring machine provided in the embodiment of the present invention further includes steps S301-S303.

[0162] S301, monitoring the real-time friction coefficient of the micro horizontal auger drilling machine module.

[0163] S302: Determine the lubricant injection amount based on the real-time friction coefficient and the preset friction coefficient range.

[0164] S303: Control lubricant injection based on the lubricant injection amount.

[0165] The lubrication and cooling module of the present invention has a dual-circuit cooling system, which can independently cool the auger bit and the servo drive system, ensuring that each key component works within a suitable temperature range. The lubrication unit automatically adjusts the injection amount of lubricant based on real-time friction monitoring data, reducing friction loss and extending the service life of key components.

[0166] Optionally, the control method of the intermittent screw boring machine provided in the embodiment of the present invention further includes steps S401-S402.

[0167] S401. Determine the working condition of the intermittent screw boring machine based on the vibration frequency and the vibration amplitude.

[0168] In some embodiments, the operating condition includes normal operation or abnormal operation.

[0169] S402: If the intermittent screw tunneling machine operates abnormally, a fault diagnosis is performed on the intermittent screw tunneling machine based on the tunneling parameters and a preset support vector machine model to obtain a fault type.

[0170] In some embodiments, the fault type includes excessive drill bit wear, abnormal torque, or excessive vibration.

[0171] The present invention uses support vector machines (SVM) to analyze sensor data, and can issue an alarm and automatically adjust parameters in time when abnormal conditions such as drill bit wear, abnormal torque or excessive vibration occur to prevent further development of faults. This real-time abnormality detection and self-adjustment capability significantly reduces the maintenance cost of the equipment and extends the service life of the equipment.

[0172] Exemplarily, an embodiment of the present invention provides an operation method of an intermittent screw boring machine, which includes steps S1-S8.

[0173] S1. Startup and initial setup

[0174] Control module to start the intermittent auger:

[0175] Before starting, the operator first checks whether the system power supply is normal and ensures that the hardware and software of each module are connected in place. After the system starts, the control module begins to initialize each submodule to ensure that the sensor monitoring module, servo electronic control drive system and adaptive control unit are in normal operation.

[0176] Check the system status and the connection status of each sensor:

[0177] The system performs a self-check, checking the status of the pressure sensor, torque sensor and vibration sensor one by one to ensure that the signal transmission between all sensors and the control module is normal. If any connection failure is found, the system will prompt the operator to check and repair it.

[0178] Set the initial drilling parameters through the control module:

[0179] The operator inputs the initial drilling parameters, including drilling speed, thrust and drilling path, through the human-machine interface (HMI). These parameters are preset according to the current geological conditions and optimized through historical data, empirical models and engineering standards. After receiving the input, the control module initializes the motion control system of the drill bit to ensure the applicability of the initial parameters in actual operation.

[0180] S2. Drilling process monitoring

[0181] Start the Micro Auger Drilling Machine module:

[0182] The operator presses the start button, and the servo-electric drive unit starts to drive the spiral drill to rotate and advance. The system collects the position and angle of the drill in real time and starts drilling according to the initial parameters.

[0183] The sensor monitoring module monitors the operating parameters during drilling in real time:

[0184] After the sensor monitoring module is activated, pressure sensors, torque sensors and vibration sensors begin to monitor key operating parameters during drilling in real time. The system uses data feedback from these sensors to identify formation conditions, drill bit status and equipment health.

[0185] Specific monitoring content:

[0186] Pressure sensor: monitors the formation resistance of the drill bit. According to different geological conditions, the system adjusts the propulsion force in real time through sensor feedback data to ensure that the drill bit is not excessively hindered or stuck by the formation.

[0187] Torque sensor: monitors the torque changes on the drive shaft to ensure the stability of the transmission system and avoid drive shaft breakage due to excessive torque.

[0188] Vibration sensor: monitors the frequency and amplitude of vibration during drilling to ensure a smooth drilling process. If the vibration frequency is abnormal, the system will issue a warning and take appropriate measures.

[0189] S3, adaptive adjustment of control module

[0190] Start the control module, including a multi-parameter real-time control unit:

[0191] After the system is started, the multi-parameter real-time control unit in the control module continuously analyzes the data fed back by the sensors, including parameters such as pressure, torque and vibration. Based on these feedbacks, the system adjusts the thrust, drilling speed and drilling path of the drill bit in real time, so that the equipment can maintain efficient and stable drilling under complex geological conditions.

[0192] Enable adaptive control unit, optimized based on deep neural network:

[0193] The adaptive control unit analyzes the real-time formation characteristics and drilling status through a deep neural network (DNN) and automatically optimizes the drilling parameters based on the model. The unit can dynamically adjust the thrust and speed according to different geological conditions to ensure that the drill bit always works in the optimal state.

[0194] The path planning unit uses reinforcement learning algorithms to optimize the path:

[0195] The path planning unit in the control module uses the reinforcement learning algorithm and the Bellman equation to calculate the optimal drilling path. The system monitors obstacles in the drilling path (such as hard rocks, cracks, etc.) in real time and automatically adjusts the path to avoid these obstacles, ensuring that the drill bit passes through complex formations smoothly.

[0196] S4. Anomaly detection and processing

[0197] The anomaly detection unit analyzes sensor data using a support vector machine:

[0198] After the abnormality detection unit is started, the support vector machine (SVM) analyzes the sensor data collected in real time, including pressure, torque and vibration data. Based on this data, the system diagnoses the operating status of the equipment and detects whether there are any abnormalities.

[0199] Detection and handling of abnormal operating conditions: The system can detect the following abnormal conditions:

[0200] Excessive drill bit wear: When the vibration frequency or drill bit torque fed back by the sensor is abnormal, the system determines that the drill bit may be worn.

[0201] Abnormal torque: When the torque sensor detects excessive torque, it may indicate a problem with the drive shaft, and the system immediately adjusts the torque output to prevent damage.

[0202] Excessive vibration: When the vibration sensor detects high-frequency vibration, the system determines that the drilling process is unstable and may need to reduce the drilling speed or adjust the drilling path.

[0203] When the above anomalies are detected, the anomaly detection unit will automatically adjust the control parameters and send an alarm to the operator through the control module to remind the operator to take further inspection or intervention measures.

[0204] S5, automatic chip removal

[0205] Start the automatic chip removal module to remove the chips through the spiral chip removal unit:

[0206] After the automatic chip removal module is started, the spiral chip removal unit and the spiral drill head work synchronously, and the system discharges the debris generated during the drilling process through the chip removal channel. The chip removal process is synchronized with the drilling operation to ensure that the drill cuttings around the drill bit will not block the drill hole.

[0207] Automatic cleaning unit activates mechanical scraper and airflow assist unit:

[0208] When debris accumulation is detected in the chip removal channel, the automatic cleaning unit starts. The mechanical scraper starts to physically clean the chip removal channel to scrape away the accumulated debris in the channel. At the same time, the airflow assist unit starts high-pressure gas to blow the fine debris out of the chip removal channel by blowing, ensuring that the chip removal channel always remains unobstructed.

[0209] S6. Lubrication and cooling

[0210] Start the lubrication and cooling module, and the cooling circuit unit works:

[0211] The system starts the lubrication and cooling module, and effectively cools the auger bit and servo drive system through the cooling circuit unit. The coolant flows through the drill bit and the drive system through the dual-circuit system, ensuring that the operating temperature of the equipment remains within the set range, preventing equipment wear or failure due to overheating.

[0212] Start the lubrication unit and automatically adjust the lubricant injection amount:

[0213] The lubrication unit automatically adjusts the amount of lubricant sprayed based on real-time feedback from the friction sensor. The lubrication unit increases or decreases the amount of lubricant sprayed in a timely manner according to the friction state of the system to ensure that the friction between the drill bit and the transmission system is maintained within a reasonable range and to extend the life of the equipment.

[0214] S7, self-learning and optimization

[0215] Start the self-learning unit to optimize based on historical drilling data collected in real time:

[0216] The self-learning unit collects various data during the drilling process in real time during the operation of the equipment, and learns and optimizes the drilling parameters under different geological conditions. The module will gradually optimize the parameter model according to the performance of the drill bit under different formation conditions, so that the system can automatically select the best drilling parameters in subsequent operations.

[0217] Progressively improving drilling strategies through deep neural networks:

[0218] The system's self-learning unit gradually improves the drilling strategy through a deep neural network. The algorithm can optimize drilling speed, thrust and path planning based on historical data and real-time feedback, improving the system's performance in complex geological conditions.

[0219] S8, stop and close

[0220] After completing the scheduled drilling task, gradually reduce the drill bit speed and propulsion force:

[0221] When the predetermined drilling depth is reached or the drilling task is completed, the system will gradually reduce the speed and thrust of the drill bit to prevent sudden stops from causing equipment damage or material deformation. The control module will adjust the speed based on real-time data to ensure that the system stops safely.

[0222] Stop the operation of the sensor monitoring module and the lubrication and cooling module:

[0223] After the drill stops, the sensor monitoring module stops real-time monitoring of operating parameters, and the lubrication and cooling modules also stop working. The operator should conduct a preliminary inspection of the equipment at this stage to ensure that there are no abnormal conditions.

[0224] Shut down all modules and inspect system components for wear:

[0225] Finally, the operator shuts down each module of the system and checks and records the wear of key components such as the drill bit, transmission system, cooling system, etc. The system automatically generates an operation report for the operator to perform subsequent maintenance.

[0226] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0227] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0228] Figure 3 The schematic diagram of the structure of a control module of an intermittent screw boring machine provided by an embodiment of the present invention is shown. The control module 500 includes a communication unit 501 and a processing unit 502 .

[0229] The communication unit 501 is used to detect the drilling parameters and control parameters of the auger drilling module. The drilling parameters include formation resistance, rotation torque, vibration frequency and vibration amplitude; the control parameters include propulsion force, rotation speed and drilling path;

[0230] The processing unit 502 is used to perform PI calculation on the control parameters with the excavation parameters as feedback to obtain the initial control parameters of the next cycle; optimize the control parameters based on the excavation parameters, the control parameters and the initial control parameters, and a preset optimization model to obtain the target control parameters of the next cycle, wherein the preset optimization model is obtained by training based on the excavation parameters and control parameters in the historical period; and control the micro horizontal auger drill module to perform excavation based on the target control parameters.

[0231] Figure 4 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the electronic device 600 includes: a processor 601, a memory 602, and a computer program 603 stored in the memory 602 and executable on the processor 601. When the processor 601 executes the computer program 603, the steps in the above-mentioned method embodiments are implemented, for example Figure 2 Alternatively, when the processor 601 executes the computer program 603, the functions of each module / unit in the above-mentioned device embodiments are realized, for example, Figure 3 The functions of the communication unit 501 and the processing unit 502 are shown.

[0232] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A control method for an intermittent screw boring machine, characterized in that: The intermittent screw boring machine comprises a screw drilling machine module, a sensor module and a control module, and the method comprises: Detecting the drilling parameters and control parameters of the auger drilling module, wherein the drilling parameters include formation resistance, rotation torque, vibration frequency and vibration amplitude; and the control parameters include propulsion force, rotation speed and drilling path; Taking the excavation parameters as feedback, PI calculation is performed on the control parameters to obtain the initial control parameters of the next cycle; Based on the excavation parameters, control parameters and initial control parameters, and a preset optimization model, the control parameters are optimized to obtain target control parameters for the next cycle, wherein the preset optimization model is obtained by training based on the excavation parameters and control parameters in the historical period; Based on the target control parameters, the micro horizontal auger drilling machine module is controlled to perform excavation.

2. The control method of an intermittent screw boring machine according to claim 1, characterized in that: The method of performing PI calculation on the control parameter by taking the excavation parameter as feedback to obtain the initial control parameter of the next cycle includes: determining a control error based on the excavation parameter and the control parameter; Based on the control error, PI calculation is performed to determine the initial control parameters for the next cycle.

3. The control method of an intermittent screw boring machine according to claim 1, characterized in that: The control parameter optimization is performed based on the excavation parameters, control parameters and initial control parameters, and a preset optimization model to obtain target control parameters for the next cycle, including: Generate a driving vector based on the driving parameter, the control parameter and the initial control parameter; Based on the excavation vector and the preset optimization model, the target control parameters for the next cycle are determined.

4. The control method of an intermittent screw boring machine according to claim 1, characterized in that: Before optimizing the control parameters based on the excavation parameters, the control parameters and the initial control parameters and the preset optimization model to obtain the target control parameters for the next cycle, the method further includes: Obtain the excavation parameters and control parameters of intermittent screw boring machines in the historical period; Divide the excavation parameters and control parameters in the historical period into time windows to obtain the excavation parameters and control parameters in multiple periods; Based on the excavation parameters and control parameters of the first cycle, PI calculation is performed to obtain initial control parameters of the second cycle; the first cycle is any cycle among the multiple cycles, and the second cycle is the next cycle of the first cycle; Determine the excavation vector of the first cycle based on the excavation parameters and control parameters of the first cycle and the initial control parameters of the second cycle; Determining target control parameters of the second cycle based on the excavation parameters of the second cycle; Taking the excavation vector of each cycle in a plurality of cycles as input and the target control parameter of the next cycle of each cycle as output, a plurality of training samples are constructed; Based on the multiple training samples, neural network training is performed to obtain the preset optimization model.

5. The control method of an intermittent screw boring machine according to claim 4, characterized in that: The performing of neural network training based on the plurality of training samples to obtain the preset optimization model comprises: Based on the multiple training samples, neural network training is performed to obtain an initial model; The initial model is used as a teacher model, and a model with the same depth as the initial model is used as a student model to construct a teacher-student model; Based on the multiple training samples, knowledge distillation training is performed on the student model in the teacher-student model to obtain the preset optimization model.

6. The control method of an intermittent screw boring machine according to claim 1, characterized in that: The step of controlling the micro horizontal auger drilling machine module to perform excavation based on the target control parameter comprises: Determining a target area on the current excavation surface based on the drilling path in the target control parameter; Controlling the micro horizontal auger drilling machine module to move to the target area; Based on the thrust and rotation speed in the target control parameters, determining the target rotation speed and target thrust of the drill bit in the micro horizontal auger drilling machine module; Controlling the operating state of the drill bit in the micro horizontal auger drilling machine module to the target rotation speed and target propulsion force; The micro horizontal auger drilling machine module is controlled to dig forward.

7. The control method of an intermittent screw boring machine according to claim 1, characterized in that: The method further comprises: Monitoring the real-time friction coefficient of the micro horizontal auger drilling machine module; Determining a lubricant injection amount based on the real-time friction coefficient and a preset friction coefficient range; Based on the lubricant injection amount, lubricant injection is controlled.

8. The control method of an intermittent screw boring machine according to claim 1, characterized in that: The method further comprises: Based on the vibration frequency and the vibration amplitude, determining the working condition of the intermittent screw boring machine, wherein the working condition includes normal working or abnormal working; If the intermittent screw boring machine operates abnormally, a fault diagnosis is performed on the intermittent screw boring machine based on the boring parameters and a preset support vector machine model to obtain a fault type, which includes excessive wear of the drill bit, abnormal torque or excessive vibration.

9. A control module for an intermittent screw boring machine, characterized in that: include: A communication unit, used to detect the drilling parameters and control parameters of the auger drilling module, wherein the drilling parameters include formation resistance, rotation torque, vibration frequency and vibration amplitude; and the control parameters include thrust, rotation speed and drilling path; A processing unit, used to perform PI calculation on the control parameter with the excavation parameter as feedback to obtain the initial control parameter of the next cycle; Based on the excavation parameters, control parameters and initial control parameters, as well as a preset optimization model, control parameter optimization is performed to obtain target control parameters for the next cycle, wherein the preset optimization model is obtained by training based on excavation parameters and control parameters in a historical period; based on the target control parameters, the micro horizontal auger drilling rig module is controlled to perform excavation.

10. An intermittent screw boring machine, characterized in that: The intermittent screw boring machine includes an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor is used to call and run the computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 8.

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