Cutting parameter decision-making method for cutter head of shield tunneling machine

Abstract

The invention relates to the technical field of tunnel engineering, in particular to a shield tunneling machine cutterhead cutting parameter decision-making method. According to the method, comprehensive and comprehensive stratum stress characterization and rock-soil cutting flow characterization are obtained by establishing cutterhead rock breaking stress models of various stratums, and final cutterhead parameters are intelligently obtained based on a multi-objective optimization model, a digital twin model and a neural network model in the form of establishing a database. According to the technical scheme, a reliable result can be obtained based on objective data, the representation capability of the finite element model can be expanded, and the credibility is improved.

Description

Technical Field

[0001] This application relates to the technical field of tunnel engineering, and particularly to a decision-making method for the cutting parameters of a shield machine cutter head. Background Art

[0002] The cutter head is the core component of a shield machine. Different combinations of cutting parameters in the cutter head significantly affect the tunneling efficiency of the shield machine and the service life of the cutters.

[0003] Higher requirements are imposed on the cutting parameters under complex geological conditions. In the prior art, the cutter head parameter design methods mostly rely on engineering experience, theoretical formulas or static geological data. These methods ignore the coupling relationship between the cutter spacing, penetration and installation radius, resulting in large errors in the calculation of the cutting specific energy and inability to dynamically match the formation changes. In recent years, the widely used finite element analysis method mostly focuses on a single cutter type, lacking a dynamic coupling model for the combined cutting of pilot cutters and scrapers, making it difficult to reflect the real rock and soil fragmentation process. Moreover, the optimization of model parameters often depends on manual experience, lacking an intelligent decision-making method based on big data, ultimately leading to the inability to dynamically adjust the model according to geological mutations. Summary of the Invention

[0004] This application provides a decision-making method for the cutting parameters of a shield machine cutter head, which solves the deficiencies that the existing finite element model cannot reflect the real rock and soil fragmentation process and cannot dynamically adjust the model according to geological mutations.

[0005] The technical solution of this application is as follows: A decision-making method for the cutting parameters of a shield machine cutter head includes the following steps: S1. Establish a finite element model of the cutter and the rock and soil, where the cutter includes a pilot cutter and a scraper; establish a surface-to-surface contact relationship between the cutter and the rock and soil in the finite model with the cutter as the master surface and the rock and soil as the slave surface, and set the rock and soil friction coefficient for the rock and soil. In addition, parameterize the staggered arrangement of the pilot cutter and the scraper; S2. Adjust the rock and soil friction coefficient to simulate various formations, and simulate the dynamic contact process between the cutter head and the rock and soil under various formations to construct a cutter head rock-breaking force model under various formations; S3. Change the cutter spacing, penetration and cutter installation radius in the cutter head rock-breaking force model under various formations to obtain the three-direction force distribution ratio of the cutter head rock-breaking force model; S4. Based on the three-direction force distribution ratio of the cutter head rock-breaking force model under various formations and the principle of the specific energy of fragmentation, establish a coupling equation between the cutter spacing, penetration and cutter installation radius, and establish a cutter head cutting specific energy model based on the coupling equation; S5. With the three - dimensional force distribution ratio of the cutterhead rock - breaking force model for various strata and the cutting specific energy model as boundary conditions, establish a combined cutting finite - element model of the pilot cutter and the scraper cutter to obtain the tool - cutterhead force characterization and the geotechnical cutting flow characterization under various strata; S6. Establish a parameter - stratum characteristic database based on the tool - cutterhead force characterization and the geotechnical cutting flow characterization under various strata; S7. After dimensionality reduction of the data in the parameter - stratum database, use a multi - objective optimization model and the K - means method for clustering to generate a geological clustering result. Input the geological clustering result into the digital twin model, and predict and output the penetration rate and the cutterhead rotation speed through a neural network model.

[0006] Furthermore, in step S1, select the penalty - function contact algorithm to define the non - linear collision and friction between the tool and the geotechnical material.

[0007] Furthermore, in step S2, use the explicit dynamics method to simulate the dynamic contact process between the cutterhead and the geotechnical material under various strata.

[0008] Furthermore, in step S2, the strata include cobble - sand strata, hard - rock strata, and sand strata. Among them, the dynamic change range of the geotechnical friction coefficient of the cobble - sand strata is [0.3, 0.5), and the random aggregate model is used for the cobble - sand strata, and the particle size range of the cobbles is 20 - 200 mm; the dynamic change range of the geotechnical friction coefficient of the hard - rock strata is [0.1, 0.2); the geotechnical friction coefficient range of the sand strata is [0.2, 0.3).

[0009] Furthermore, in step S2, use the APDL language to write a macro command to parameterize the staggered arrangement of the pilot cutter and the scraper cutter: the edge - inclination angle range of both the pilot cutter and the scraper cutter is 15° - 30°, the spacing range between the pilot cutter and the scraper cutter is 80 mm - 120 mm, and the pilot cutter is arranged in the center according to the cutterhead helix. The scraper cutters are symmetrically distributed on both sides of the spokes in a helix layout covering the full - section cutting path of the cutterhead, and calculate the total cutting force between the tool and the strata based on the contact - force integration.

[0010] Furthermore, the coupling equation in step S4 is: ; In the formula, represents the cutter spacing, represents the penetration rate, represents the tool installation radius, represents the geotechnical stiffness coefficient, Q represents the rock - breaking volume per unit time, represents the cutting specific energy; The formula for the cutterhead cutting specific energy model established in step S4 is as follows: ； In the formula, SEC represents the specific cutting energy, represents the tangential force, represents the normal force, v represents the cutting speed, represents the formation friction correction coefficient, Q represents the rock-breaking volume per unit time.

[0011] Furthermore, in step S5, the formation force characterization includes the critical values of the maximum thrust force, torque, and vibration amplitude of the cutterhead; the geotechnical cutting flow characterization is determined based on the geotechnical particle velocity field and the muck flow path in front of the cutterhead tunneling.

[0012] Furthermore, in step S7, the multi-objective optimization model takes the maximum cutting efficiency and the minimum tool wear rate as the objective functions; The expression formula for the maximum cutting efficiency is as follows: ; In the formula, MRR represents the material removal rate, f 1 represents the cutting efficiency; The expression formula for the minimum tool wear rate is as follows: ; In the formula, R represents the tool installation radius, f 2 represents the tool wear rate.

[0013] Furthermore, the geological clustering results in step S7 include the maximum thrust force, torque, vibration spectrum, geotechnical friction coefficient, and Mohr-Coulomb parameters of the cutterhead.

[0014] Due to the adoption of the above technical solutions, the beneficial effects of the present application are as follows: 1. The present application changes the subjective decision-making in the traditional cutterhead parameter design and the method based on static geological data. By establishing the cutterhead rock-breaking force model for various formations, a comprehensive and complete formation force characterization and geotechnical cutting flow characterization are obtained. In the form of establishing a database, the final cutterhead parameters are intelligently obtained based on the multi-objective optimization model, digital twin model, and neural network model. The technical solution of the present application can obtain reliable results based on objective data, can expand the characterization ability of the finite element model, and improve the credibility.

[0015] 2. The present application defines and simulates the model through penalty functions and realistic dynamics. The penalty function method dynamically adjusts through contact stiffness and penetration, and can effectively handle nonlinear behaviors such as large deformations, separation-recontact of geotechnical materials, especially being suitable for actual tunneling conditions. The present application uses the explicit dynamics method to directly solve the dynamic equation through time integration, and can accurately simulate the transient responses (such as shock wave propagation, inertial effects) of the cutter interacting with the geotechnical materials, differentiating from the deficiencies of traditional static models that can only describe steady-state forces.

[0016] 3. The finite element models of the prior art lack a dynamic coupling model for the combined cutting of pilot cutters and drag cutters, and it is difficult to reflect the real geotechnical fragmentation process. The present application establishes a dynamic coupling model for the combined cutting of pilot cutters and drag cutters, and the dynamic coupling model can quantify the influence of different parameter combinations on the rock-breaking efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and form a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application.

[0018] Figure 1 It is a flowchart of a decision-making method for the cutting parameters of the cutter head of a shield machine provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Based on the background art described above, the present application provides a decision-making method for the cutting parameters of the cutter head of a shield machine. Referring to the attached Figure 1 , the present application includes the following steps: S1. Establish a finite element model of the cutter and the geotechnical material, where the cutter includes a pilot cutter and a drag cutter; establish a surface-to-surface contact relationship between the cutter and the geotechnical material with the cutter as the master surface and the geotechnical material as the slave surface in the finite model, set the geotechnical friction coefficient for the geotechnical material, and parameterize the staggered arrangement of the pilot cutter and the drag cutter.

[0020] The cutter includes a pilot cutter and a drag cutter, while the prior art mostly simulates a single cutter (such as a hob or a drag cutter). In the present application, by combining the pilot cutter and the drag cutter, the working state of the cutter head of the shield machine can be simulated more realistically, and more accurate cutter head force results can be obtained. During the simulation, since the cutter material is rigid and the movement is controlled, it is uniformly set as the master surface.

[0021] It should be noted that the geotechnical friction coefficient is a range, and by setting different friction coefficients, the rolling friction between formation particles and a large surface roughness can be simulated.

[0022] In step S1, the penalty function contact algorithm is selected to define the non-linear collision and friction between the cutter and the rock and soil. During the modeling process, check "Penalty-Based Contact" in the contact properties and input the penalty factor to achieve the definition.

[0023] S2. Adjust the rock and soil friction coefficient to simulate various strata, and simulate the dynamic contact process between the cutter head and the rock and soil under various strata to construct the force model of the cutter head breaking rock under various strata.

[0024] In step S2, the explicit dynamics method is used to simulate the dynamic contact process between the cutter head and the rock and soil under various strata. The explicit dynamics method is default enabled in LS-DYNA and does not need to be selected separately, but parameters such as the time step size, material model, and contact algorithm need to be adapted. When the penetration amount is too large, the penalty factor needs to be increased. When necessary, the friction coefficient is corrected according to the experimental data, and the specific correction method belongs to the well-known technology in the field. In step S2, the strata include cobblestone strata, hard rock strata, and sand strata. Among them, the dynamic change range of the rock and soil friction coefficient of the cobblestone strata is [0.3, 0.5), and the cobblestone strata adopt a random aggregate model, and the particle size range of the cobblestones is 20 - 200 mm; the dynamic change range of the rock and soil friction coefficient of the hard rock strata is [0.1, 0.2); the range of the rock and soil friction coefficient of the sand strata is [0.2 - 0.3). There is also a clay stratum, and the clay stratum is defined by Mohr-Coulomb parameters, such as cohesion of 0.5 MPa and internal friction angle of 20°.

[0025] In step S2, the APDL language is used to write a macro command to parameterize the staggered arrangement of the pilot cutters and the scrapers: the blade inclination angles of the pilot cutters and the scrapers are both in the range of 15° - 30°, the spacing range between the pilot cutters and the scrapers is 80 mm - 120 mm, and the pilot cutters are arranged in the center according to the cutter head helix. The scrapers are symmetrically distributed on both sides of the spokes to cover the helix layout of the full-section cutting path of the cutter head. The total cutting force between the cutter and the strata is calculated based on the contact force integration. The core commands of the APDL script programming include contact pair definition, element table extraction, and integral summation, which belong to the existing technology.

[0026] S3. Change the cutter spacing, penetration, and cutter installation radius in the force model of the cutter head breaking rock under various strata to obtain the three-way force distribution ratio of the force model of the cutter head breaking rock; Summarize the three-way force law through the simulation results of the three-way force ratio under different working conditions.

[0027] In this embodiment, the distribution law of the three-way force is as follows: Tangential force F t : The frictional force in the direction parallel to the contact surface between the cutter and the rock and soil, which is related to the relative sliding speed v and the friction coefficientμ Related

[0028] Normal force F n : The pressure perpendicular to the contact surface, mainly affected by the penetration degree and the geotechnical strength.

[0029] Radial force F r : The lateral force generated by the centrifugal effect during the rotation of the tool, related to the tool installation radius R and the rotational speed ω.

[0030] It is expressed by the mathematical model as: In the formula, represents the geotechnical friction coefficient (0.3 - 0.5 for sand and gravel, 0.1 - 0.2 for hard rock); , respectively represent two contact stiffness coefficients, dynamically adjusted through the penalty function algorithm; , respectively represent two tangential and normal penetration amounts; represents the equivalent mass of the tool, R represents the tool installation radius, ω is the angular velocity of the cutterhead.

[0031] The coupling relationship of the three - dimensional forces is affected by the coupling of the cutter spacing s, the penetration degree p, and the installation radius R, and can be expressed as: S4. Based on the three - dimensional force distribution ratio of the cutterhead rock - breaking force model for various strata and the principle of specific energy of fragmentation, establish the coupling equation among the cutter spacing, the penetration degree, and the tool installation radius, and establish the cutterhead specific energy of cutting model based on the coupling equation.

[0032] The normal force dominates the rock - breaking efficiency: it is necessary to balance the rock - breaking speed and the tool load by optimizing the penetration degree; The tangential force is related to the energy consumption: the friction component directly affects the specific energy of cutting SEC; The radial force affects the stability: an excessive Fr may lead to an increase in cutterhead vibration.

[0033] The coupling equation in step S4 is: ; In the formula, represents the cutter spacing, represents the penetration degree, represents the tool installation radius, represents the geotechnical stiffness coefficient, Q represents the rock - breaking volume per unit time, represents the specific energy of cutting; The expression formula of the cutterhead specific energy of cutting model established in step S4 is as follows: ； In the formula, SEC represents the specific cutting energy, represents the tangential force, represents the normal force, v represents the cutting speed, represents the formation friction correction coefficient, Q represents the rock-breaking volume per unit time.

[0034] The specific cutting energy SEC of the cutter head is the core index to measure the energy efficiency of the cutter head of the shield machine when cutting rock and soil. It is defined as the energy consumed for breaking per unit volume of rock and soil, and is also the core index of the tunneling efficiency of the shield machine. By quantifying the energy consumption for breaking per unit of rock and soil, it guides the optimization of cutter head parameters and the adjustment of formation adaptability.

[0035] S5. Taking the three-way force distribution ratio of the rock-breaking force model of the cutter head in various formations and the specific cutting energy model as boundary conditions, establish a combined cutting finite element model of the pilot cutter and the scraping cutter to obtain the force characterization of the tool-cutter head and the rock and soil cutting flow characterization under various formations.

[0036] In step S5, the force characterization of the tool-cutter head includes the critical values of the maximum thrust, torque, and vibration amplitude of the cutter head; the rock and soil cutting flow characterization is determined based on the rock and soil particle velocity field and the muck flow path in front of the cutter head tunneling.

[0037] The finite element model of the tool and the rock and soil and the combined cutting model are different models, but there is a connection between them. The finite element model of the tool and the rock and soil is used to analyze the rock-breaking law of various types of tools (pilot cutter and scraping cutter) working together, including the influence of tool layout (spacing, edge inclination angle) on cutting efficiency, tool wear, and rock and soil flow Combined cutting finite element model of the pilot cutter and the scraping cutter: Analyze the rock-breaking law of various types of tools (pilot cutter and scraping cutter) working together, including the influence of tool layout (spacing, edge inclination angle) on cutting efficiency, tool wear, and rock and soil flow. The tool and rock and soil model is the basis of the combined model, and the three-way force ratio and specific cutting energy model output by it are used as the input conditions for the combined cutting simulation.

[0038] S6. Establish a parameter-formation characteristic database based on the force characterization of the tool-cutter head and the rock and soil cutting flow characterization in various formations; The parameter-formation characteristic database is a database established by clustering analysis of simulation data through a multi-objective optimization model (such as the NSGA-II algorithm). This database integrates the optimized combination relationships of different formation types (such as cobble stratum, hard rock stratum, sand stratum) and corresponding cutter head cutting parameters (such as cutter spacing, penetration, tool installation radius, etc.), and combines the formation mechanical properties and cutting response data.

[0039] After dimensionality reduction of the data in the parameter-stratum database, a multi-objective optimization model and the K-means method are used for clustering to generate a geological clustering result, and the geological clustering result is input into the digital twin model, and the penetration rate and cutter head rotation speed are predicted and output through a neural network model.

[0040] In step S7, the multi-objective optimization model takes the maximum cutting efficiency and the minimum tool wear rate as the objective functions; The expression formula for the maximum cutting efficiency is as follows: ; In the formula, MRR represents the material removal rate, f 1 represents the cutting efficiency; The expression formula for the minimum tool wear rate is as follows: ; In the formula, R represents the tool installation radius, f 2 represents the tool wear rate.

[0041] The geological clustering result in step S7 includes the maximum cutter head thrust, torque, vibration spectrum, rock and soil friction coefficient, and Mohr-Coulomb parameters.

[0042] Both the digital twin model and the neural network model are existing technologies. By constructing an LSTM prediction network, the cutter head torque, thrust, vibration spectrum, and stratum parameters are input into the LSTM prediction network to output the recommended penetration rate and cutter head rotation speed. The Kalman filter is used to fuse multi-source data to update the digital twin model parameters in real time and dynamically adjust the parameters to match the stratum changes.

[0043] In the present application, the parts not described can be implemented by adopting or referring to the existing technologies.

[0044] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A decision-making method for the cutting parameters of a shield machine cutter head, characterized in that It includes the following steps: S1. Establish a finite element model of the cutter and the rock and soil. The cutter includes a pilot cutter and a scraping cutter. In the finite model, establish a surface-to-surface contact relationship between the cutter and the rock and soil with the cutter as the master surface and the rock and soil as the slave surface, set the rock and soil friction coefficient for the rock and soil, and parameterize the staggered arrangement of the pilot cutter and the scraping cutter; S2. Adjust the rock and soil friction coefficient to simulate various strata, and simulate the dynamic contact process between the cutter head and the rock and soil under various strata to construct a cutter head rock-breaking force model under various strata; S3. Change the cutter spacing, penetration degree, and cutter installation radius in the cutter head rock-breaking force model of various strata to obtain the three-way force distribution ratio of the cutter head rock-breaking force model; S4. Based on the three-way force distribution ratio of the cutter head rock-breaking force model of various strata and the principle of specific energy of fragmentation, establish a coupling equation between the cutter spacing, penetration degree, and cutter installation radius, and establish a cutter head cutting specific energy model based on the coupling equation; S5. Take the three-way force distribution ratio of the cutter head rock-breaking force model of various strata and the cutting specific energy model as boundary conditions, establish a combined cutting finite element model of the pilot cutter and the scraping cutter, and obtain the cutter-cutter head force characterization and rock and soil cutting flow characterization under various strata; S6. Establish a parameter-stratum characteristic database based on the cutter-cutter head force characterization and rock and soil cutting flow characterization of various strata; S7. After dimensionality reduction of the data in the parameter-stratum database, use a multi-objective optimization model and the K-means method for clustering to generate a geological clustering result, input the geological clustering result into the digital twin model, and predict and output the penetration degree and cutter head rotation speed through a neural network model.

2. A decision-making method for cutter head cutting parameters of a shield machine according to claim 1, characterized in that In step S1, a penalty function contact algorithm is selected to define the non-linear collision and friction between the cutter and the rock and soil.

3. A decision-making method for cutter head cutting parameters of a shield machine according to claim 2, characterized in that In step S2, an explicit dynamics method is used to simulate the dynamic contact process between the cutter head and the rock and soil under various strata.

4. A decision-making method for cutter head cutting parameters of a shield machine according to claim 3, characterized in that In step S2, the strata include cobble strata, hard rock strata, and sand strata. Among them, the dynamic change range of the rock and soil friction coefficient of the cobble strata is [0.3, 0.5), and the random aggregate model is used for the cobble strata, and the particle size range of the cobbles is 20-200 mm; the dynamic change range of the rock and soil friction coefficient of the hard rock strata is [0.1, 0.2); the range of the rock and soil friction coefficient of the sand strata is [0.2-0.3).

5. A decision-making method for cutter head cutting parameters of a shield machine according to claim 4, characterized in that In step S2, the macro command is written in APDL language to parameterize the staggered arrangement of the leading cutter and the scraping cutter: the rake angle ranges of both the leading cutter and the scraping cutter are 15° to 30°, the spacing range between the leading cutter and the scraping cutter is 80 mm to 120 mm, and the leading cutter is arranged in the center according to the cutter head helix. The scraping cutters are symmetrically distributed on both sides of the spokes to cover the helix layout of the full-section cutting path of the cutter head. The total cutting force between the cutter and the formation is calculated based on the contact force integration.

6. A decision-making method for the cutting parameters of a shield machine cutter head according to claim 5, characterized in that The coupling equation in step S4 is: ； In the formula, represents the cutter spacing, represents the penetration depth, represents the cutter installation radius, represents the rock and soil stiffness coefficient, and Q represents the rock breaking volume per unit time, represents the specific cutting energy; The expression formula of the cutter head cutting specific energy model established in step S4 is as follows: ； In the formula, SEC represents the specific cutting energy, represents the tangential force, represents the normal force, v represents the cutting speed, represents the formation friction correction coefficient, Q represents the rock-breaking volume per unit time.

7. A decision-making method for the cutting parameters of a shield machine cutter head according to claim 6, characterized in that In step S5, the formation force characterization includes the critical values of the maximum thrust, torque, and vibration amplitude of the cutter head; the geotechnical cutting flow characterization is determined based on the geotechnical particle velocity field and the muck flow path in front of the cutter head tunneling.

8. A decision-making method for the cutting parameters of a shield machine cutter head according to claim 7, characterized in that In step S7, the multi-objective optimization model takes the maximum cutting efficiency and the minimum tool wear rate as the objective functions; The expression formula of the maximum cutting efficiency is as follows: ； Wherein, MRR represents the material removal rate, f 1 represents the cutting efficiency; The expression formula of the minimum tool wear rate is as follows: ； In the formula, R represents the tool mounting radius, f 2 represents the tool wear rate.

9. A decision-making method for the cutting parameters of a shield machine cutter head according to claim 7, characterized in that The geological clustering results in step S7 include the maximum thrust, torque, vibration spectrum, geotechnical friction coefficient, and Mohr-Coulomb parameters of the cutter head.

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