Shield / TBM (tunnel boring machine) adaptive type selection auxiliary decision-making system

Abstract

The invention provides a shield / TBM (tunnel boring machine) adaptive type selection auxiliary decision-making system, and belongs to the field of shield machine type selection. According to the system, by integrating geological exploration reports and design file data uploaded by users, the most suitable main parameters such as shield tunneling machine types, cutterhead diameters, hinging modes and cutter configuration are automatically determined. Wherein the data processing and analysis not only comprises an expert judgment implementation method, but also comprises a shield tunneling machine adaptability knowledge base analysis implementation method. According to the parameters and the model selection report template, the system can synthesize a detailed model selection suggestion report, and allows a user to edit, preview and download by himself / herself. The system can effectively improve the accuracy and efficiency of model selection of the shield tunneling machine, avoids errors caused by human factors, and has very high practical value.

Description

Technical Field

[0001] The invention belongs to the field of shield machine selection, and more specifically relates to a shield / TBM adaptive selection auxiliary decision-making system. Background Art

[0002] In tunnel engineering and other underground projects, a Tunnel Boring Machine (TBM) is a device used for tunnel excavation. Its working principle is to use the cutter head at the front end of the TBM to cut the stratum, and then transfer the excavated soil and rocks to the rear of the tunnel through the conveyor belt at the rear. At the same time, the tunnel wall is reinforced with pipe segments to ensure the stability of the tunnel.

[0003] At present, the selection of shield machines is mainly based on the experience and intuitive judgment of designers or engineers, and is mostly done manually. This method is not only inefficient but also prone to errors. In addition, different geological environments and different engineering application scenarios require the selection of different types and specifications of shield machines. How to choose the most suitable shield machine according to the engineering environment and conditions has become a challenge.

[0004] When selecting a shield machine, it is necessary to consider both geological conditions (such as stratum type, groundwater, geological structure, etc.) and the special needs of the project (such as tunnel length, diameter, depth; construction period and cost constraints, etc.). However, most of the existing shield machine selection methods are based on empirical rules and cannot fully consider the mutual influence of various factors. Sometimes the experience of professionals may also be biased, so the selected shield machine may not necessarily achieve the best effect.

[0005] Therefore, it is necessary to develop a system that can automatically select shield machines according to the engineering environment and actual needs, so as to improve engineering efficiency and accuracy, reduce risks and save costs. Based on this demand, the present invention proposes a shield / TBM adaptive selection auxiliary decision-making system combined with artificial intelligence, which intelligently selects shield machines and greatly improves work efficiency and selection accuracy. Summary of the invention

[0006] The present invention aims to solve the problem that the existing shield machine selection method is too dependent on manual experience and intuitive judgment, and the selection efficiency is low and prone to errors. By combining artificial intelligence technology, according to various engineering parameters of geological survey reports and design documents, the most suitable shield machine model, cutterhead diameter, articulation method, tool configuration and other main parameters are automatically analyzed and recommended, and a selection recommendation report is generated to improve the accuracy and efficiency of shield machine selection, reduce the risk of misselection, and better meet the actual needs of different projects.

[0007] In order to achieve the above object, the present invention adopts the following technical solution: the system comprises:

[0008] User data input, including geological survey reports and design documents, is uploaded to the system using Excel;

[0009] Data processing and analysis to determine the main parameters of shield machine type, cutterhead diameter, articulation method, and cutter configuration;

[0010] Selection recommendation generation: synthesize the selection recommendation report based on the selection parameters and selection report template, and allow users to edit the selection report, preview the selection report, and download the selection report.

[0011] In one solution, the data processing and analysis includes using artificial intelligence technology to dynamically adjust and optimize the expert judgment implementation method and the shield machine adaptability knowledge base analysis implementation method;

[0012] The implementation process is:

[0013] (1) Data collection: Collect historical experience data on shield machine selection, including shield machine type, cutterhead diameter, articulation method, cutter configuration information, and the reasons and environmental conditions for selecting these configurations;

[0014] (2) Data preprocessing: clean the collected data, remove invalid and abnormal data, and normalize the data;

[0015] (3) Model training: Select a support vector machine and use the preprocessed data to train the model. During the training process, the model parameters will be continuously adjusted and optimized to make the model's prediction results closer and closer to the actual values.

[0016] (4) Model prediction: When selecting a TBM, input the current environment and condition data, and the model will predict the most appropriate TBM configuration based on this data;

[0017] (5) Result feedback: Based on the prediction results, the user chooses whether to configure the shield machine according to the prediction results. The system will continuously optimize the prediction model based on user feedback and actual usage.

[0018] In one embodiment, the expert judgment implementation method includes:

[0019] (1) Determination of shield machine type;

[0020] (2) Determination of cutter head diameter;

[0021] Use the segment outer diameter-cutter head diameter comparison table in the design file for mapping;

[0022] (3) Determination of articulation mode;

[0023] According to the horizontal curve turning radius in the design document, if it is ≤250m, active articulation is recommended;

[0024] (4) Tool configuration;

[0025] Based on the average uniaxial compressive strength of the section, if it is ≤30MPa, configure soft soil tools; if it is >30MPa, configure hard rock tools.

[0026] In one solution, the shield machine adaptability knowledge base analysis implementation method rules are as follows:

[0027] (1) Cutter type, tool configuration, cutter opening rate, and maximum cutter speed;

[0028] (2) Main drive form;

[0029] The main drive type is an important reference, and electric drive or hydraulic drive can be manually selected;

[0030] (3) Rated torque, breakaway torque, and maximum working pressure;

[0031] Match the cases of the same machine type, cutter head diameter ±0.5m, and currently selected main drive form from historical cases, and extract the range of rated torque, escape torque, and maximum working pressure;

[0032] (4)Host parameters.

[0033] In one solution, the shield machine type determination specifically includes:

[0034] According to the sections filled in the geological survey report, the selection is carried out respectively, and the selection basis is:

[0035] If the average permeability coefficient is less than 10e-7m / s, an earth pressure balance shield machine should be selected; if it is greater than 10e-4m / s, a slurry balance shield machine should be selected;

[0036] If the stratum type is ① clay, ② muddy sand, ③ fine sand, an earth pressure balance shield machine is selected; if it is ⑧ pebble layer, ⑦ coarse gravel layer or ⑥ medium-fine gravel layer, a slurry balance shield machine is selected;

[0037] If the average groundwater pressure is greater than 3 bar, a slurry shield machine should be used;

[0038] If there is a risk source of crossing rivers, lakes or seas, and the cutter head diameter is greater than 10m, a slurry shield machine should be selected.

[0039] In one solution, the specific rules for selecting the disc form, tool configuration, disc opening rate, and maximum disc speed are as follows:

[0040] Match historical cases by stratum type, such as the current bidding section includes ①②③ strata:

[0041] a) Give priority to complete formation matching, and match historical cases with the same formations ①, ②, and ③. If a match is found, compare the cutterhead form, tool configuration, cutterhead opening rate, and maximum cutterhead speed of the case or multiple cases;

[0042] b) If a) fails to match, perform decomposition matching, such as searching for case 1 of strata ① and ② and case 2 of strata ③, and extracting the interval range;

[0043] c) If none of the above matches, the rules are as follows:

[0044] The cutterhead type is determined based on the stratum: for stratum ① clay-⑥ medium-fine gravel layer, a spoke-type cutterhead is used; for stratum ⑦ coarse gravel layer-⑨ full-section hard rock, a panel-type cutterhead is used; for stratum where there is an intersection of the first two or ⑩ composite stratum, a composite cutterhead is used.

[0045] The cutter disc opening rate is determined based on the cutter disc type: 70% to 75% for spoke cutter discs; 30% to 45% for compound cutter discs; less than 30% for panel cutter discs;

[0046] If tool configuration / maximum tool disc speed cannot be matched with a case, leave it blank.

[0047] In one embodiment, the host parameters are as follows:

[0048] a) Front shield diameter, matching historical cases with the same cutter head diameter, extracting the front shield diameter, or leaving it blank if none;

[0049] b) Maximum tunneling speed / maximum thrust / main bearing diameter / main engine weight / main engine length / cutterhead drive power / total power / other configurations, matching shield machine model, cutterhead diameter ±0.5m, and the same main drive type currently selected, extract the range;

[0050] c) Foam, only earth pressure balance shield machine has it, if it is a slurry shield machine, it is empty; for earth pressure shield machine matching shield machine model, cutter head diameter ±0.5m, and the same main drive form currently selected, extract the interval range.

[0051] Beneficial effects of the present invention:

[0052] The shield / TBM adaptive selection auxiliary decision-making system of the present invention can automatically process and analyze data and generate a detailed selection recommendation report, thereby making the shield machine selection process more efficient and accurate. The system adopts advanced information processing and analysis technology to avoid errors caused by human factors and improve the reliability of the results. In addition, users can intuitively view the selection suggestions, edit and modify them at any time, making the decision-making process more flexible. Under complex geological conditions, the system can still provide accurate suggestions. In general, this system optimizes the shield machine selection process, improves the efficiency and accuracy of decision-making, saves manpower and time costs, and has high application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a system block diagram of the present invention;

[0054] Figure 2 Flow chart for shield machine selection;

[0055] Figure 3 This is the artificial intelligence selection flow chart of the present invention. DETAILED DESCRIPTION

[0056] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0057] Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used in the present invention in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0058] like Figure 1 The shield / TBM adaptive selection auxiliary decision-making system includes: user data input, including geological survey reports and design documents, which are uploaded to the system using Excel.

[0059] The process of the shield selection adaptability auxiliary decision-making tool is that the user fills in the Excel template according to the geological survey report, design documents, etc., and uploads it to the system. The system gives recommended selections based on the solidified selection experience and matching historical cases, including machine model, cutterhead diameter, etc. The user can generate a selection recommendation report with one click. The overall process of the shield selection module is as follows Figure 2 shown.

[0060] It supports users to select the interval of the project that has been entered. The information of this interval is displayed on the left. After clicking "Evaluation Calculation", the stratigraphic statistics chart and the recommended main selection results are given on the right.

[0061] The model selection is based on the provided logic. If there is a model conflict within a segment, a pop-up window will appear for the user to confirm. If the model results are different between different segments, the user can adjust the priority by themselves, and the model with the highest priority will prevail.

[0062] After the selection is confirmed, click "View Selection Results" and the parameter summary results will be displayed on one page. Click "Generate Report" on this page to jump to the page of the shield selection recommendation report.

[0063] Based on the information entered or imported by the user, the system calculates the interval length and proportion and displays it in a pie chart. The main parameters of the shield machine model, cutter head diameter, articulation method, and tool configuration are determined based on selection experience.

[0064] Data processing and analysis to determine the main parameters of the shield machine type, cutter head diameter, articulation method, and tool configuration. The data processing and analysis includes the use of artificial intelligence technology to dynamically adjust and optimize the expert judgment implementation method and the shield machine adaptability knowledge base analysis implementation method;

[0065] (1) Selection of artificial intelligence

[0066] like Figure 3 As shown, the implementation process is:

[0067] (1) Data collection: Collect historical experience data on shield machine selection, including shield machine model, cutterhead diameter, articulation method, cutter configuration information, as well as the reasons and environmental conditions for selecting these configurations.

[0068] Collect historical shield machine selection data, each data contains the parameters to be predicted, such as shield machine type, cutter head diameter, articulation method, cutter configuration, etc., as well as the reasons for selecting these parameters and environmental conditions, such as stratum type, permeability coefficient, etc. This can be expressed as an n-dimensional vector X = (x1, x2, ..., xn) T To represent these environmental conditions, use an m-dimensional vector Y = (y1, y2, ..., ym) T to represent the parameters to be predicted.

[0069] (2) Data preprocessing: Clean the collected data, remove invalid and abnormal data, and normalize the data.

[0070] Before training, the data must be preprocessed. Numerical data needs to be normalized so that it is within a uniform numerical range. Common normalization methods include MinMax normalization.

[0071] For MinMax normalization, the formula is:

[0072] x'=(x-min) / (max-min)

[0073] Here, min and max are the minimum and maximum values ​​of the data, μ is the mean of the data, and σ is the standard deviation of the data.

[0074] (3) Model training: Select a support vector machine and use the preprocessed data to train the model. During the training process, the model parameters will be continuously adjusted and optimized so that the model's prediction results are closer and closer to the actual values.

[0075] For support vector machines (SVM), the goal is to find a hyperplane that maximizes the interval between positive and negative samples. This problem can be transformed into a constrained optimization problem:

[0076] min 1 / 2||w|| 2

[0077] sty i (w*x i +b)≥1, i=1,...,N

[0078] Among them, w and b are the hyperplane parameters to be determined, yi and xi are the label and feature of a training data, and N is the number of samples.

[0079] By solving the above optimization problem, we can get the values ​​of w and b, and thus determine the hyperplane. The solution method is usually SMO algorithm or gradient descent.

[0080] (4) Model prediction: When selecting a TBM, input the current environment and condition data, and the model will predict the most appropriate TBM configuration based on this data.

[0081] After obtaining the hyperplane, predict the new data X:

[0082] f(X)=w T *X+b

[0083] This is the basic form of the prediction function, where w and b are the hyperplane parameters obtained during training.

[0084] (5) Result feedback: Based on the prediction results, the user chooses whether to configure the shield machine according to the prediction results. The system will continuously optimize the prediction model based on user feedback and actual usage.

[0085] The model predicts the result Y'=f(X). The user can choose whether to configure the shield machine according to the predicted result. The system will continuously optimize the prediction model based on user feedback and actual usage. The optimization process generally uses the gradient descent method to adjust the model parameters to minimize the gap between the predicted result and the actual result.

[0086] (2) Methods for implementing expert judgment.

[0087] 1) Determine the type of shield machine

[0088] There are many factors to consider when choosing a shield machine. The discussion rules and priorities are as follows:

[0089] Step 1: Select the type of each section according to the geological survey report. The selection basis is:

[0090] If the average permeability coefficient is <10e-7m / s, an earth pressure balance shield machine is selected; if it is >10e-4m / s, a slurry balance shield machine is selected; in other cases, no judgment is made for the time being. [The unit of the permeability coefficient imported from the table is m / d, which needs to be converted to m / s, 1m / d=86400m / s]

[0091] If the stratum type is ① clay, ② mud and sand, ③ fine sand, an earth pressure balance shield machine shall be selected; if it is ⑧ pebble layer, ⑦ coarse gravel layer or ⑥ medium and fine gravel layer, a slurry balance shield machine shall be selected; other situations will not be judged for the time being.

[0092] If the average groundwater pressure is greater than 3 bar, a slurry shield machine is selected; others are not judged for the time being.

[0093] If there is any conflict between the above, the user will be prompted to make a judgment.

[0094] Step 2: If there are risk sources of crossing rivers, lakes, or seas, and the cutter head diameter is greater than 10m, a slurry shield machine should be selected.

[0095] Step 3: After the above selection, the results are summarized:

[0096] If the selection results are consistent, the selection results will be given directly;

[0097] If the selection results conflict, the user is prompted to adjust the priority by himself, and the highest priority will prevail;

[0098] If the model has not been selected at this time, the earth pressure balance shield machine is preferred based on economic considerations.

[0099] The default priority is: Key points > Section 1 > Section 2 >......

[0100] Step 4: Summarize the above and give the selection results of shield machine models

[0101] 2) Determination of cutter head diameter

[0102] Use the comparison table of segment outer diameter – cutter head diameter in the design file for mapping (the comparison table is maintained by the user). If no match is found, it will be empty.

[0103] 3) Determination of articulation method

[0104] According to the turning radius of the flat curve in the design document, if it is ≤250m, active articulation is recommended; otherwise, leave it blank.

[0105] 4) Tool configuration

[0106] Based on the average uniaxial compressive strength of the section, if it is ≤30MPa, configure soft soil tools; if it is >30MPa, configure hard rock tools.

[0107] (3) Implementation method of shield machine adaptability knowledge base analysis

[0108] 1) Cutter type, tool configuration, cutter opening rate, and maximum cutter speed

[0109] Match historical cases by stratum type, such as the current bidding section includes ①②③ strata:

[0110] a) Give priority to complete formation matching, and match historical cases with the same formations ①, ②, and ③. If a match is found, compare the cutterhead form, tool configuration, cutterhead opening rate, and maximum cutterhead speed of the case or multiple cases;

[0111] b) If a) fails to match, perform decomposition matching, such as searching for case 1 of strata ① and ② and case 2 of strata ③, and extracting the interval range;

[0112] c) If none of the above matches, the rules are as follows:

[0113] The cutterhead type is determined based on the stratum: for stratum ① clay-⑥ medium-fine gravel layer, a spoke-type cutterhead is used; for stratum ⑦ coarse gravel layer-⑨ full-section hard rock, a panel-type cutterhead is used; for stratum where there is an intersection of the first two or ⑩ composite stratum, a composite cutterhead is used.

[0114] The blade opening rate is determined based on the blade type: 70% to 75% for spoke blades; 30% to 45% for compound blades; and less than 30% for panel blades.

[0115] If tool configuration / maximum tool disc speed cannot be matched with a case, leave it blank.

[0116] 2) Main drive type

[0117] The main drive type is an important reference. The user manually selects electric drive or hydraulic drive. The results are different in the two modes, and hydraulic drive is selected by default.

[0118] 3) Rated torque, escape torque, maximum working pressure

[0119] Match historical cases with cases of the same machine type, cutter head diameter ±0.5m, and currently selected main drive form, and extract the range of rated torque, escape torque, and maximum working pressure.

[0120] 4) Host parameters

[0121] a) Front shield diameter, match historical cases with exactly the same cutter head diameter, extract the front shield diameter, or leave it blank if none exists.

[0122] b) Maximum tunneling speed / maximum thrust / main bearing diameter / main machine weight / main machine length / cutter drive power / total power / other configurations, matching the shield machine model, cutter diameter ±0.5m, and the case with the same currently selected main drive type, extract the range.

[0123] c) Foam, only earth pressure balance shield machine has it, if it is a slurry shield machine, it is empty; for earth pressure shield machine matching shield machine model, cutter head diameter ±0.5m, and the same main drive form currently selected, extract the interval range.

[0124] (3) Selection results

[0125] Shield Tunneling Machine Selection Sample Table

[0126]

[0127]

[0128] Selection recommendation generation: synthesize the selection recommendation report based on the selection parameters and selection report template, and allow users to edit the selection report, preview the selection report, and download the selection report.

[0129] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0130] It should be understood that the detailed description of the technical solutions of the present invention by means of the preferred embodiments is illustrative rather than restrictive. A person skilled in the art may modify the technical solutions described in the embodiments, or replace some of the technical features by equivalents, based on reading the specification of the present invention; and these 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.

Claims

1. A shield / TBM adaptive selection auxiliary decision-making system, characterized by: The system comprises: User data input, including geological survey reports and design documents, is uploaded to the system using Excel; Data processing and analysis to determine the main parameters of shield machine type, cutterhead diameter, articulation method, and cutter configuration; Selection recommendation generation: synthesize the selection recommendation report based on the selection parameters and selection report template, and allow users to edit the selection report, preview the selection report, and download the selection report.

2. The shield / TBM adaptive selection auxiliary decision-making system according to claim 1, characterized in that: The data processing and analysis include the use of artificial intelligence technology to dynamically adjust and optimize the expert judgment implementation method and the shield machine adaptability knowledge base analysis implementation method; The implementation process is: (1) Data collection: Collect historical experience data on shield machine selection, including shield machine type, cutterhead diameter, articulation method, cutter configuration information, and the reasons and environmental conditions for selecting these configurations; (2) Data preprocessing: clean the collected data, remove invalid and abnormal data, and normalize the data; (3) Model training: Select a support vector machine and use the preprocessed data to train the model. During the training process, the model parameters will be continuously adjusted and optimized to make the model's prediction results closer and closer to the actual values. (4) Model prediction: When selecting a TBM, input the current environment and condition data, and the model will predict the most appropriate TBM configuration based on this data; (5) Result feedback: Based on the prediction results, the user chooses whether to configure the shield machine according to the prediction results. The system will continuously optimize the prediction model based on user feedback and actual usage.

3. The shield / TBM adaptive selection auxiliary decision-making system according to claim 2 is characterized by: The expert judgment implementation method includes: (1) Determination of shield machine type; (2) Determination of cutter head diameter; Use the segment outer diameter-cutter head diameter comparison table in the design file for mapping; (3) Determination of articulation mode; According to the horizontal curve turning radius in the design document, if it is ≤250m, active articulation is recommended; (4) Tool configuration; Based on the average uniaxial compressive strength of the section, if it is ≤30MPa, configure soft soil tools; if it is >30MPa, configure hard rock tools.

4. The shield / TBM adaptive selection auxiliary decision-making system according to claim 2 is characterized by: The shield machine adaptability knowledge base analysis implementation method rules are as follows: (1) Cutter type, tool configuration, cutter opening rate, and maximum cutter speed; (2) Main drive form; The main drive type is an important reference, and electric drive or hydraulic drive can be manually selected; (3) Rated torque, breakaway torque, and maximum working pressure; Match the cases of the same machine type, cutter head diameter ±0.5m, and currently selected main drive form from historical cases, and extract the range of rated torque, escape torque, and maximum working pressure; (4)Host parameters.

5. The shield / TBM adaptive selection auxiliary decision-making system according to claim 3 is characterized by: The shield machine type determination specifically includes: According to the sections filled in the geological survey report, the selection is carried out respectively, and the selection basis is: If the average permeability coefficient is less than 10e-7m / s, an earth pressure balance shield machine should be selected; if it is greater than 10e-4m / s, a slurry balance shield machine should be selected; If the stratum type is ① clay, ② muddy sand, ③ fine sand, an earth pressure balance shield machine is selected; if it is ⑧ pebble layer, ⑦ coarse gravel layer or ⑥ medium-fine gravel layer, a slurry balance shield machine is selected; If the average groundwater pressure is greater than 3 bar, a slurry shield machine should be used; If there is a risk source of crossing rivers, lakes or seas, and the cutter head diameter is greater than 10m, a slurry shield machine should be selected.

6. The shield / TBM adaptive selection auxiliary decision-making system according to claim 4 is characterized by: The specific rules for selecting the disc form, tool configuration, disc opening rate, and maximum disc speed are as follows: Match historical cases by stratum type, such as the current bidding section includes ①②③ strata: a) Give priority to complete formation matching, and match historical cases with the same formations ①, ②, and ③. If a match is found, compare the cutterhead form, tool configuration, cutterhead opening rate, and maximum cutterhead speed of the case or multiple cases; b) If a) fails to match, perform decomposition matching, such as searching for case 1 of strata ① and ② and case 2 of strata ③, and extracting the interval range; c) If none of the above matches, the rules are as follows: The cutterhead type is determined based on the stratum: for stratum ① clay-⑥ medium-fine gravel layer, a spoke-type cutterhead is used; for stratum ⑦ coarse gravel layer-⑨ full-section hard rock, a panel-type cutterhead is used; for stratum with an intersection of the first two or ⑩ composite stratum, a composite cutterhead is used; The cutter disc opening rate is determined based on the cutter disc type: 70% to 75% for spoke cutter discs; 30% to 45% for compound cutter discs; less than 30% for panel cutter discs; If tool configuration / maximum tool disc speed cannot be matched with a case, leave it blank.

7. The shield / TBM adaptive selection auxiliary decision-making system according to claim 4 is characterized by: The host parameters are as follows: a) Front shield diameter, matching historical cases with the same cutter head diameter, extracting the front shield diameter, or leaving it blank if none; b) Maximum tunneling speed / maximum thrust / main bearing diameter / main engine weight / main engine length / cutterhead drive power / total power / other configurations, matching shield machine model, cutterhead diameter ±0.5m, and the same main drive type currently selected, extract the range; c) Foam, only earth pressure balance shield machine has it, if it is a slurry shield machine, it is empty; for earth pressure shield machine matching shield machine model, cutter head diameter ±0.5m, and the same main drive form currently selected, extract the interval range.

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