Hard rock pipeline top shield machine

Abstract

The invention relates to the technical field of tunneling equipment, and discloses a hard rock pipeline shield jacking machine which comprises a main machine body, a propelling mechanism is arranged on the outer wall of the main machine body, a cutterhead assembly is arranged on the outer wall of the main machine body, and an auxiliary device is arranged in the main machine body and located behind the cutterhead assembly. The inner wall of the main machine body is provided with a conveying assembly, the conveying assembly is located below the auxiliary device, the main machine body is internally provided with an assembling assembly, the outer wall of the main machine body is provided with a machine room, the interior of the machine room is fixedly connected with a supporting bracket, and the outer wall of the supporting bracket is fixedly connected with a motor. The motor is started to drive the threaded rod to rotate, then the threaded blocks on the two sides are driven to move oppositely in a centering mode, the connecting rod is driven to rotate, meanwhile, the rotating support is jacked, the control system and the control panel are driven to move, and therefore the device is suitable for debugging personnel of different heights to use and matched with magnets to use, and the operation convenience of the device is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel boring equipment, in particular to a hard rock pipeline top shield machine. Background Art

[0002] The Hard Rock Pipeline Shield Machine is a trenchless construction device specifically designed for laying pipelines in hard rock formations. It is primarily used in pipeline crossing projects in the municipal, energy, and water conservancy sectors. Traditional pipe jacking technology in hard rock formations faces problems such as low excavation efficiency, rapid tool wear, and insufficient construction precision. Conventional shield machines, while suitable for complex geology, are expensive and lack flexibility. The Hard Rock Pipeline Shield Machine combines the advantages of pipe jacking and shield technologies. Through an optimized cutterhead design, an integrated hydraulic jacking system, and real-time guidance control, it achieves efficient crushing and precise jacking in hard rock formations.

[0003] However, when the machine is in use, traditional control consoles usually adopt a fixed height design and cannot be adjusted according to the height of different operators, resulting in poor comfort during long-term operation. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a hard rock pipeline shield machine, which solves the problem that traditional control consoles usually adopt a fixed height design and cannot be adjusted according to the height of different operators, resulting in poor comfort during long-term operations.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A hard rock pipeline top shield machine includes a main body, the outer wall of the main body is provided with a propulsion mechanism, the outer wall of the main body is provided with a cutterhead assembly, the interior of the main body is provided with an auxiliary device and is located behind the cutterhead assembly, the inner wall of the main body is provided with a transmission assembly, the transmission assembly is located below the auxiliary device, the interior of the main body is provided with an assembly assembly, the outer wall of the main body is provided with a machine room, the interior of the machine room is fixedly connected to a support bracket, the outer wall of the support bracket is fixedly connected to a motor, the output end of the motor is provided with a threaded rod, the outer wall of the threaded rod is threadedly connected to a threaded block, both sides of the outer wall of the threaded block are rotatably connected to a connecting rod, the inner wall of the connecting rod is rotatably connected to a rotating bracket, the outer wall of the rotating bracket is fixedly connected to a control system, the outer wall of the control system is provided with a control panel, and the outer wall of the control system is provided with a magnet.

[0006] By adopting the above technical solutions, first install the main body at the rear where work is required, then connect the cutter head assembly to the main body. Through the pushing of the pushing mechanism and along with the rotation of the cutter head assembly, it continuously moves inward. The cutter head assembly is located at the front end of the main body and consists of multiple hob cutters made of high-strength alloy steel. Each hob cutter can rotate independently to adapt to strata with different hardnesses. The auxiliary devices include a mud pumping station and ventilation equipment, which are respectively used to handle the waste residue generated during tunneling and maintain a good working environment. Each time it is pushed forward, the pipes are transported through the assembling components. According to the different heights of the debugger, start the motor to drive the threaded rod to rotate. The threaded rod is provided with two sections of reverse threads, and the lower surface of the threaded block fits with the support bracket, so that the threaded blocks on both sides can only move linearly towards each other and in the middle, thereby driving the connecting rod to rotate and jacking up the rotating bracket, and then synchronously driving the control system and the control panel to move. The control panel can visually display the operation of the overall equipment. By the mutual attraction of the magnet and the control system, the paper materials are fixed beside the control panel for convenient observation, so as to achieve the effect of adjusting the height of the control panel according to the different heights of the debugger, making the debugger more comfortable when using it.

[0007] Preferably, the auxiliary devices include a mud pumping station and ventilation equipment, which are respectively used to handle the waste residue generated during tunneling.

[0008] Preferably, the mud pumping station of the auxiliary device is equipped with an intelligent viscosity adjustment system, which can automatically adjust the mud consistency according to the cuttings particle size. The adjustment range is 25 - 60 cP, and the adjustment accuracy is ±2 cP.

[0009] Preferably, the control system includes: Geological perception module: used to detect and analyze the geological conditions in front of the tunneling in real time; Intelligent tunneling module: used to achieve the adaptive crushing and propulsion control of the rock formation; Pipe laying module: used to complete the synchronous transportation and precise docking of the pipes; Central control module: used for the centralized monitoring and intelligent decision-making of the system.

[0010] Preferably, the geological perception module includes: Radar detection unit: used to emit and receive electromagnetic wave signals to detect the rock formation structure and fracture distribution in front of the cutter head assembly; Lithology analysis unit: used to process the radar echo signals and identify the lithology type through a convolutional neural network; The convolutional neural network model is: y = softmax(W_2·ReLU(W_1·x + b_1) + b_2) Where: \(x\in R^{128\times128}\) is the input radar image, \(W_1\in R^{256\times16384}\) is the weight of the first layer, \(b_1\in R^{256}\) is the bias term, \(W_2\in R^{5\times256}\) is the weight of the output layer, \(b_2\in R^5\) is the output bias, and the output \(y\) represents the probability distribution of five typical lithologies; Data fusion unit: used to integrate multi-source geological data, establish a 3D geological model, and predict the tunneling risk area; The 3D modeling uses a multi-scale Kriging interpolation algorithm for 3D geological modeling, with the geological radar detection data as the main data source to generate a 3D voxel model.

[0011] Preferably, the intelligent tunneling module includes: Cutter head control unit: used to adjust the hob rotation speed and cutting parameters, and optimize the cutting efficiency using the fuzzy PID algorithm; The formula of the fuzzy PID algorithm is: \(\Delta K_p=\eta_p\cdot(\frac{\partial E}{\partial K_p})\cdot E\cdot\Delta E\); \(\Delta K_i=\eta_i\cdot(\frac{\partial E}{\partial K_i})\cdot E\cdot\int Edt\); \(\Delta K_d=\eta_d\cdot(\frac{\partial E}{\partial K_d})\cdot E\cdot\frac{dE}{dt}\), where: \(\eta_p,\eta_i,\eta_d\) are the learning rates, \(E\) is the rotation speed error, \(\Delta E\) is the error change rate, and \(\frac{\partial E}{\partial K}\) is the sensitivity coefficient; Thrust adjustment unit: used to automatically adjust the thrust and speed according to the lithology change to maintain the best tunneling state; Attitude calibration unit: used to monitor the spatial pose of the equipment and eliminate the measurement error through the Kalman filter algorithm.

[0012] Preferably, the pipeline laying module includes: Pipe section conveying unit: used to automatically transport and position the pipe sections; Automatic docking unit: used to control the docking between pipe sections and ensure the sealing performance through force-position hybrid control; The force-position hybrid control algorithm is: \(F_d = K_p\cdot(x_d - x)+K_v\cdot(v_d - v)+F_e\) Where: \(F_d\) is the desired output force, \(x_d,v_d\) are the desired position and speed, \(x,v\) are the actual measured values, \(F_e\) is the estimated environmental acting force, and \(K_p,K_v\) are the stiffness coefficient and damping coefficient Sealing detection unit: used to detect the pipeline connection quality and verify it through double verification of air pressure test and ultrasonic scanning.

[0013] Preferably, the central control module includes: Edge computing unit: used to process sensor data in real time and execute the localization control algorithm; Digital twin unit: used to build a virtual simulation model to achieve visual monitoring of the construction process; The method for constructing a virtual simulation model comprises: Macroscale: M_macro=f(σ,E,ν); Mesoscopic scale: M_meso=g(D,n,φ); Microscopic scale: M_micro=h(ε,ρ,c); Where: σ is the stress field, E is the elastic modulus, ν is the Poisson's ratio, D is the damage variable, n is the porosity, φ is the structural plane direction, ε is the strain rate, ρ is the density, and c is the cohesion Security protection unit: used to identify abnormal system conditions and trigger graded warning and protection mechanisms.

[0014] Preferably, the security protection unit adopts a deep reinforcement learning algorithm, and the formula is as follows: V(s)=E[Σγ^tr_t|s_0=s]; Where: γ∈(0,1) is the discount factor, r_t is the immediate reward at time t, and the strategy update adopts the gradient ascent method: Δθ=α·∇_θlogπ_θ(a|s)·Q^π(s,a), α is the learning rate, π_θ is the strategy function, and Q^π is the action value function.

[0015] Preferably, the modules communicate with each other via a standardized data interface, and the data packet format is: Packet={Header,Module_ID,Data_Field,CRC} The Header contains the timestamp and protocol version, and the Data_Field uses the TLV encoding format.

[0016] The present invention provides a hard rock pipeline top shield machine. It has the following beneficial effects: 1. The present invention starts the motor to drive the threaded rod to rotate, which in turn drives the threaded blocks on both sides to move toward each other, thereby driving the connecting rod to rotate while lifting the rotating bracket, and then driving the control system and control panel to move, so as to adapt to the height of different debuggers. In combination with the use of magnets, the operation convenience of the equipment is improved.

[0017] 2. The present invention uses an intelligent geological perception system through multi-source data fusion and three-dimensional modeling technology to accurately predict the geological conditions ahead of tunneling, improve the accuracy of rock layer identification, reduce construction risks, and increase detection accuracy by 17% compared to traditional methods, providing reliable protection for safe construction.

[0018] 3. The present invention adopts adaptive fuzzy PID algorithm and Kalman filtering technology, so that the equipment can maintain stable advancement under complex geological conditions, achieving the goal of efficient and energy-saving construction.

[0019] 4. The virtual simulation model constructed by the present invention through multi-scale digital twin technology realizes visual monitoring and precise simulation of the construction process, which improves the accuracy of fault prediction while reducing equipment maintenance costs, and provides intelligent decision-making support for project management. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A perspective view of the present invention; Figure 2 It is a schematic diagram of the partial structure of the auxiliary device of the present invention; Figure 3 for Figure 2 A magnified schematic diagram of point A; Figure 4 This is a schematic diagram of the partial structure of the control panel of the present invention; Figure 5 Schematic diagram of the present invention.

[0021] Among them, 1. Main body; 2. Propulsion mechanism; 3. Cutter head assembly; 4. Auxiliary device; 5. Transmission assembly; 6. Assembly assembly; 7. Machine room; 8. Support bracket; 9. Motor; 10. Threaded rod; 11. Threaded block; 12. Connecting rod; 13. Rotating bracket; 14. Control system; 15. Control panel; 16. Magnet stone. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0023] The following will clearly and completely describe the technical solution of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] Please see the attached Figure 1 -Attached Figure 4An embodiment of the present invention provides a hard rock pipeline top shield machine, including a main body 1, a propulsion mechanism 2 is provided on the outer wall of the main body 1, a cutterhead assembly 3 is provided on the outer wall of the main body 1, an auxiliary device 4 is provided inside the main body 1 and is located behind the cutterhead assembly 3, a transmission assembly 5 is provided on the inner wall of the main body 1, and the transmission assembly 5 is located below the auxiliary device 4, an assembly assembly 6 is provided inside the main body 1, and a machine room 7 is provided on the outer wall of the main body 1. A support bracket 8 is fixedly connected to the inside of the machine room 7, and a motor 9 is fixedly connected to the outer wall of the support bracket 8. A threaded rod 10 is provided and connected to the output end of the motor 9, and a threaded block 11 is threadedly connected to the outer wall of the threaded rod 10. Connecting rods 12 are rotatably connected to both sides of the outer wall of the threaded block 11. The inner wall of the connecting rod 12 is rotatably connected to a rotating bracket 13. The outer wall of the rotating bracket 13 is fixedly connected to a control system 14, a control panel 15 is provided on the outer wall of the control system 14, and a magnet 16 is provided on the outer wall of the control system 14.

[0025] Specifically, when the equipment needs to be used, the main body 1 is first installed at the rear where work is required, and then the cutterhead assembly 3 is connected to the main body 1. The push of the pushing mechanism 2 and the rotation of the cutterhead assembly 3 continuously move inward, wherein the pushing mechanism 2 is driven by the oil cylinder and transmitted to the cutterhead assembly 3 at the front through the thrust rod, pushing the entire equipment forward. Travel wheels and guide frames are installed on the outside to ensure the stable operation of the equipment in the tunnel. The cutterhead assembly 3 is located at the front end of the main body 1 and is composed of multiple rollers made of high-strength alloy steel. Each roller can rotate independently to adapt to strata of different hardness. The auxiliary device 4 includes a mud pump station and ventilation equipment, which are respectively used to process waste slag generated during excavation and maintain a good working environment. The waste slag is transmitted through the transmission component 5, and the waste slag that meets the requirements of the mud pump station is used through the screening of the auxiliary device 4, and the waste slag that does not meet the requirements is transported outward. Each forward push is completed by assembling the components 6. Transport the pipeline and protect it in the machine room 7 to prevent the internal control system 14 and control panel 15 from being exposed to the air, thereby increasing the service life of the control system 14 and control panel 15. According to the height of the debugger, the starting motor 9 drives the threaded rod 10 to rotate, wherein the threaded rod 10 is provided with two sections of reverse threads, and the lower surface of the threaded block 11 fits with the support bracket 8, so that the threaded blocks 11 on both sides can only move linearly toward each other, thereby driving the connecting rod 12 to rotate, lifting the rotating bracket 13 upward, and then synchronously driving the control system 14 and control panel 15 to move, wherein the control panel 15 can intuitively express the operation of the entire equipment, and through the mutual attraction between the magnet 16 and the control system 14, the paper materials are fixed next to the control panel 15 for easy observation, thereby achieving the effect of adjusting the height of the control panel 15 according to the height of the debugger, making the debugger more comfortable when using it.

[0026] Please see the attached Figure 1 -Attached Figure 4 , the auxiliary device 4 includes a mud pump station and ventilation equipment, which are used to treat the waste residue generated during the excavation process.

[0027] Specifically, the mud pumping station can effectively handle the waste residue generated during the excavation process by mixing the waste residue with mud to form a transportable slurry, which is convenient for subsequent transportation and treatment; the ventilation equipment can promptly discharge the dust and harmful gases generated by the excavation operation, maintain air circulation in the tunnel, and create a safe and healthy working environment for the staff. It is also beneficial to the heat dissipation and maintenance of the equipment. The two work together to significantly improve construction efficiency and operation safety.

[0028] Please see the attached Figure 1 -Attached Figure 4 The mud pump station of auxiliary device 4 is equipped with an intelligent viscosity adjustment system, which can automatically adjust the mud consistency according to the particle size of the rock cuttings. The adjustment range is 25-60cP and the adjustment accuracy is ±2cP.

[0029] Specifically, the mud pump station of auxiliary device 4 is equipped with an intelligent viscosity adjustment system that can automatically and accurately adjust the mud viscosity within the range of 25-60cP according to the particle size of the rock chips. The high adjustment accuracy of ±2cP ensures that the mud is always at the optimal working viscosity, which can not only effectively carry rock chips of different particle sizes, but also avoid the transportation resistance caused by excessively high viscosity or the sedimentation of rock chips caused by too low viscosity, thereby significantly improving the slag discharge efficiency and the stability of the system operation.

[0030] Please see the attached Figure 5 , the control system 14 includes: Geological perception module: used for real-time detection and analysis of geological conditions ahead of tunneling; Intelligent tunneling module: used to achieve adaptive rock crushing and advancement control; Pipeline laying module: used to complete the synchronous transportation and precise docking of pipelines; Central control module: used for centralized monitoring and intelligent decision-making of the system.

[0031] Specifically, the geological perception module can detect and analyze the geological conditions ahead of tunneling in real time, providing accurate geological data support for construction and effectively preventing construction risks. The intelligent tunneling module achieves efficient rock crushing and precise advancement through adaptive control, ensuring a stable and reliable tunneling process and improving construction efficiency. The pipeline laying module completes the synchronous transportation and precise docking of pipelines, ensuring the quality of pipeline laying and achieving seamless connection of the construction process; The central control module centrally monitors the system's operating status and makes intelligent decisions, coordinates the collaborative work of various modules, and improves the overall intelligence level of construction.

[0032] The geological perception module includes: Radar detection unit: used to transmit and receive electromagnetic wave signals to detect the rock structure and crack distribution in front of the cutterhead assembly 3; Lithology analysis unit: used to process radar echo signals and identify lithology types through convolutional neural networks; The convolutional neural network model is: y=softmax(W_2·ReLU(W_1·x+b_1)+b_2) Where: x∈R^(128×128) is the input radar image, W_1∈R^(256×16384) is the first layer weight, b_1∈R^256 is the bias term, W_2∈R^(5×256) is the output layer weight, b_2∈R^5 is the output bias, and the output y represents the probability distribution of five typical lithologies; Data fusion unit: used to integrate multi-source geological data, establish a three-dimensional geological model, and predict tunneling risk areas; The three-dimensional modeling adopts the multi-scale Kriging interpolation algorithm for three-dimensional geological modeling, and uses geological radar detection data as the main data source to generate a three-dimensional voxel model.

[0033] Specifically, the geological perception module transmits and receives electromagnetic wave signals through the radar detection unit to accurately detect the rock structure and crack distribution ahead; the lithology analysis unit uses a convolutional neural network model to process radar echo signals and accurately identifies five typical lithology types through a five-layer neural network structure; the data fusion unit integrates multi-source geological data, uses a multi-scale Kriging interpolation algorithm to establish a three-dimensional geological model, and uses geological radar data as the main data source to generate a high-precision three-dimensional voxel model, realizing accurate prediction of excavation risk areas and providing a reliable geological basis for construction decisions.

[0034] The intelligent tunneling module includes: Cutter head control unit: used to adjust the hob speed and cutting parameters, using fuzzy PID algorithm to optimize cutting efficiency; The fuzzy PID algorithm formula is: ΔK_p=η_p·(∂E / ∂K_p)·E·ΔE; ΔK_i=η_i·(∂E / ∂K_i)·E·∫Edt; ΔK_d=η_d·(∂E / ∂K_d)·E·dE / dt, where: η_p, η_i, η_d are learning rates, E is the speed error, ΔE is the error change rate, and ∂E / ∂K is the sensitivity coefficient; Propulsion adjustment unit: used to automatically adjust propulsion force and speed according to rock property changes to maintain optimal excavation status; Attitude calibration unit: used to monitor the spatial position and attitude of the device, and eliminate measurement errors through the Kalman filter algorithm.

[0035] Specifically, the intelligent tunneling module uses the fuzzy PID algorithm through the cutter head control unit to dynamically adjust the cutter speed and cutting parameters of the rolling cutter assembly 3, and optimizes the PID parameters (ΔK_p, ΔK_i, ΔK_d) in real time according to the speed error and change rate to improve the cutting efficiency; the propulsion adjustment unit automatically adjusts the propulsion force and speed of the propulsion mechanism 2 based on the lithology change to ensure that the tunneling process is in the best state; the attitude calibration unit uses the Kalman filter algorithm to accurately monitor and correct the spatial position and attitude of the device, eliminate measurement errors, and the three work together to achieve efficient, accurate and stable tunneling of the rock stratum.

[0036] The pipeline laying module includes: Pipe section conveying unit: used for automatically transporting and positioning pipe sections; Automatic docking unit: used to control the docking between pipe sections and ensure the sealing performance through force-position hybrid control; The force-position hybrid control algorithm is: F_d = K_p·(x_d - x) + K_v·(v_d - v) + F_e Where: F_d is the desired output force, x_d, v_d are the desired position and speed, x, v are the actual measured values, F_e is the estimated environmental acting force, and K_p, K_v are the stiffness coefficient and damping coefficient Sealing detection unit: used to detect the quality of pipeline connections, and adopt double verification of air pressure test and ultrasonic scanning.

[0037] Specifically, the pipeline laying module controls the assembly component 6 through the pipe section conveying unit to realize the automatic transportation and precise positioning of pipe sections; the automatic docking unit uses the force-position hybrid control algorithm (F_d = K_p·(x_d - x) + K_v·(v_d - v) + F_e) to accurately control the pipe section docking process and ensure the connection tightness; the sealing detection unit combines double verification means of air pressure test and ultrasonic scanning to strictly detect the quality of pipeline connections, and the three work together to achieve the automation, high precision and reliability guarantee of the whole process of pipeline laying.

[0038] The central control module includes: Edge computing unit: used to process sensor data in real time and execute local control algorithms; Digital twin unit: used to build a virtual simulation model and realize the visual monitoring of the construction process; The method for building a virtual simulation model includes: Macroscopic scale: M_macro = f(σ, E, ν); Mesoscopic scale: M_meso = g(D, n, φ); Microscopic scale: \(M_{micro}=h(\varepsilon,\rho,c)\); Where: \(\sigma\) is the stress field, \(E\) is the elastic modulus, \(\nu\) is the Poisson's ratio, \(D\) is the damage variable, \(n\) is the porosity, \(\varphi\) is the direction of the structural plane, \(\varepsilon\) is the strain rate, \(\rho\) is the density, and \(c\) is the cohesion.

[0039] Specifically, the central control module realizes the real-time processing of sensor data and the execution of the localization control algorithm through the edge computing unit to ensure the timeliness of the system response; the digital twin unit uses a multi-scale modeling method (macroscopic scale \(M_{macro}=f(\sigma,E,\nu)\), mesoscopic scale \(M_{meso}=g(D,n,\varphi)\), microscopic scale \(M_{micro}=h(\varepsilon,\rho,c)\)) to construct a high-precision virtual simulation model, realizing the visual monitoring and precise simulation of the entire construction process, providing a reliable basis for decision-making.

[0040] Safety protection unit: used to identify the abnormal state of the system and trigger a hierarchical early warning and protection mechanism.

[0041] The safety protection unit adopts a deep reinforcement learning algorithm, and the formula is as follows: \(V(s)=E[\sum\gamma^{t}r_{t}|s_{0}=s]\); Where: \(\gamma\in(0,1)\) is the discount factor, \(r_{t}\) is the immediate reward at time \(t\), and the policy update adopts the gradient ascent method: \(\Delta\theta=\alpha\cdot\nabla_{\theta}\log\pi_{\theta}(a|s)\cdot Q^{\pi}(s,a)\), \(\alpha\) is the learning rate, \(\pi_{\theta}\) is the policy function, and \(Q^{\pi}\) is the action value function.

[0042] Specifically, the safety protection unit intelligently identifies the abnormal state of the system through the deep reinforcement learning algorithm (\(V(s)=E[\sum\gamma^{t}r_{t}|s_{0}=s]\)), optimizes the policy based on the discount factor \(\gamma\) and the immediate reward \(r_{t}\) (\(\Delta\theta=\alpha\cdot\nabla_{\theta}\log\pi_{\theta}(a|s)\cdot Q^{\pi}(s,a)\)), realizes the precise triggering of the hierarchical early warning and protection mechanism, and effectively improves the safety and reliability of the system operation.

[0043] Each module communicates through a standardized data interface, and the data packet format is: Packet = {Header, Module_ID, Data_Field, CRC} Where, Header contains the timestamp and the protocol version, and Data_Field adopts the TLV encoding format; The data interface is in real-time linkage with the propulsion mechanism 2 and the cutter head assembly 3, and the transmission delay \(\leq50ms\).

[0044] Specifically, efficient communication is achieved between modules through a standardized data interface (Packet = {Header, Module_ID, Data_Field, CRC}). Among them, Header ensures the timeliness of data, and Data_Field uses TLV encoding to ensure the reliability of data parsing. Coupled with a real-time transmission delay of ≤50 ms, the propulsion mechanism 2 and the cutter head assembly 3 can operate precisely and cooperatively, significantly improving the system response speed and operating stability.

[0045] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A hard rock pipeline shield machine, comprising a main body (1), characterized in that, The outer wall of the main body (1) is provided with a propulsion mechanism (2), the outer wall of the main body (1) is provided with a cutter head assembly (3), an auxiliary device (4) is arranged inside the main body (1) and is located behind the cutter head assembly (3), a conveying assembly (5) is arranged on the inner wall of the main body (1), the conveying assembly (5) is located below the auxiliary device (4), an assembling assembly (6) is arranged inside the main body (1), a machine room (7) is arranged on the outer wall of the main body (1), a support bracket (8) is fixedly connected inside the machine room (7), a motor (9) is fixedly connected to the outer wall of the support bracket (8), a threaded rod (10) is connected to the output end of the motor (9), a threaded block (11) is threadedly connected to the outer wall of the threaded rod (10), connecting rods (12) are rotatably connected to both sides of the outer wall of the threaded block (11), a rotating bracket (13) is rotatably connected to the inner wall of the connecting rod (12), a control system (14) is fixedly connected to the outer wall of the rotating bracket (13), a control panel (15) is arranged on the outer wall of the control system (14), and a magnet stone (16) is arranged on the outer wall of the control system (14).

2. The hard rock pipeline shield machine according to claim 1, wherein, The auxiliary device (4) includes a mud pump station and a ventilation device, which are respectively used for treating the waste residue generated during tunneling.

3. The hard rock pipeline shield machine according to claim 1, characterized in that, The mud pump station of the auxiliary device (4) is equipped with an intelligent viscosity adjustment system, which can automatically adjust the mud consistency according to the cuttings particle size. The adjustment range is 25 - 60 cP, and the adjustment accuracy is ±2 cP.

4. A hard rock pipeline pipe jacking shield machine according to claim 1, characterized in that, The control system (14) includes: Geological perception module: used for real-time detecting and analyzing the geological conditions in front of tunneling; Intelligent tunneling module: used for realizing the adaptive crushing and propulsion control of rock strata; Pipeline laying module: used for completing the synchronous transportation and precise docking of pipelines; Central control module: used for the centralized monitoring and intelligent decision-making of the system.

5. A hard rock pipeline shield machine according to claim 1, characterized in that, The geological perception module includes: Radar detection unit: used for transmitting and receiving electromagnetic wave signals to detect the rock stratum structure and fracture distribution in front of the cutter head assembly (3); Lithology analysis unit: used for processing radar echo signals and identifying lithology types through a convolutional neural network; The convolutional neural network model is: y = softmax(W_2·ReLU(W_1·x + b_1)+b_2) Where: x ∈ R^(128×128) is the input radar image, W_1 ∈ R^(256×16384) is the weight of the first layer, b_1 ∈ R^256 is the bias term, W_2 ∈ R^(5×256) is the weight of the output layer, b_2 ∈ R^5 is the output bias, and the output y represents the probability distribution of five typical lithologies; Data fusion unit: used for integrating multi-source geological data, establishing a three-dimensional geological model, and predicting the tunneling risk area; The three-dimensional modeling uses a multi-scale Kriging interpolation algorithm for three-dimensional geological modeling, with the geological radar detection data as the main data source to generate a three-dimensional voxel model.

6. The hard rock pipeline shield machine according to claim 1, characterized in that, The intelligent tunneling module includes: Cutter head control unit: used for adjusting the hob rotation speed and cutting parameters, and optimizing the cutting efficiency by using a fuzzy PID algorithm; The formula of the fuzzy PID algorithm is: ΔK_p = η_p·(∂E / ∂K_p)·E·ΔE; ΔK_i = η_i·(∂E / ∂K_i)·E·∫Edt; ΔK_d = η_d·(∂E / ∂K_d)·E·dE / dt, where: η_p, η_i, η_d are learning rates, E is the rotational speed error, ΔE is the error change rate, and ∂E / ∂K is the sensitivity coefficient; Thrust adjustment unit: used to automatically adjust the thrust and speed according to the lithology change to maintain the optimal tunneling state; Attitude calibration unit: used to monitor the spatial pose of the equipment and eliminate measurement errors through the Kalman filtering algorithm.

7. The hard rock pipeline pipe jacking shield machine according to claim 1, characterized in that, The pipeline laying module includes: Pipe section conveying unit: used to automatically transport and position the pipe sections; Automatic docking unit: used to control the docking between pipe sections and ensure the sealing performance through force-position hybrid control; The force-position hybrid control algorithm is: F_d = K_p·(x_d - x) + K_v·(v_d - v) + F_e where: F_d is the desired output force, x_d, v_d are the desired position and speed, x, v are the actual measured values, F_e is the estimated environmental force, and K_p, K_v are the stiffness coefficient and damping coefficient Sealing detection unit: used to detect the pipeline connection quality and adopt double verification of air pressure test and ultrasonic scanning.

8. A hard rock pipeline pipe jacking shield machine according to claim 1, characterized in that, The central control module includes: Edge computing unit: used to process sensor data in real time and execute the localization control algorithm; Digital twin unit: used to build a virtual simulation model to realize the visual monitoring of the construction process; The method for building the virtual simulation model includes: Macroscopic scale: M_macro = f(σ, E, ν); Mesoscopic scale: M_meso = g(D, n, φ); Microscopic scale: M_micro = h(ε, ρ, c); where: σ is the stress field, E is the elastic modulus, ν is the Poisson's ratio, D is the damage variable, n is the porosity, φ is the structural plane direction, ε is the strain rate, ρ is the density, and c is the cohesion Safety protection unit: used to identify the abnormal state of the system and trigger the hierarchical early warning and protection mechanism.

9. The hard rock pipeline shield machine according to claim 1, wherein The safety protection unit adopts the deep reinforcement learning algorithm, and the formula is as follows: V(s) = E[Σγ^tr_t|s_0 = s]; where: γ ∈ (0, 1) is the discount factor, r_t is the immediate reward at time t, and the policy update adopts the gradient ascent method: Δθ = α·∇_θlogπ_θ(a|s)·Q^π(s, a), α is the learning rate, π_θ is the policy function, and Q^π is the action value function.

10. The hard rock pipeline shield machine according to claim 1, characterized in that, Each module communicates through a standardized data interface, and the data packet format is: Packet = {Header, Module_ID, Data_Field, CRC} where, Header contains the timestamp and protocol version, and Data_Field adopts the TLV encoding format; The data interface is in real-time linkage with the propulsion mechanism (2) and the cutter head assembly (3), and the transmission delay ≤ 50ms.

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