Tunnel boring machine tool configuration method based on geological data

Abstract

The invention relates to the technical field of tunneling, and discloses a tunneling machine tool configuration method based on geological data. According to the method, rock core samples are obtained in a geological radar and geological exploration mode, according to physical and mechanical properties of rocks, the rocks are classified into hard rocks, soft rocks and other types, strength distribution diagrams of different stratums are drawn, the influence of the rock types on cutter selection is analyzed, and a hob or a cutter head or a scraper is selected according to the different rock types. Selecting a corresponding material to improve the wear resistance of the cutter, determining the shape and the size of the cutter, calculating the average compressive strength, the shear strength, the cutting force, the cutting rate and the wear rate of the cutter, determining the number and the arrangement mode of the cutter according to the analysis and calculation results, and determining the number and the arrangement mode of the cutter according to the geological data and the cutter performance. And calculating the tunneling efficiency and the cost benefit of the optimal cutter configuration, analyzing the tunneling efficiency and the cost benefit of the tunneling machine after the cutter configuration, and selecting an optimal cutter configuration scheme.

Description

Technical Field

[0001] The invention relates to the technical field of tunnel boring, and in particular to a tunnel boring machine tool configuration method based on geological data. Background Art

[0002] The tunnel boring machine cutter is the front-end operating part of the tunnel boring machine, which is responsible for directly cutting and crushing rocks and providing the necessary power for tunnel excavation. The cutter exerts shear and compression on the underground rocks by rotating and feeding, breaking them into small pieces. This process is especially important for cutting strong rocks. The performance of the cutter directly affects the excavation efficiency. Reliable cutter configuration can effectively reduce the risk of cutter wear and collapse, enhance the safety of the entire excavation process, and reduce the downtime caused by equipment failure. Under complex and changeable geological conditions, optimized cutter configuration can effectively improve the adaptability of the tunnel boring machine to different strata, making construction more flexible.

[0003] Currently, the tool configuration of tunnel boring machines often relies on personal experience and data estimation. The tool configuration scheme under this method is not the most reasonable, resulting in low excavation efficiency and cost waste. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a tunnel boring machine tool configuration method based on geological data, which has the ability to obtain core samples through geological radar and geological exploration, analyze and determine the types of soil and rock, collect the compressive strength, shear strength, elastic modulus and Poisson's ratio of the rock, record the thickness, distribution and interlayer relationship of the strata, including groundwater level, flow velocity, permeability and groundwater chemical properties, classify the rock into hard rock, soft rock and other types according to its physical and mechanical properties, draw strength distribution maps of different strata, analyze the influence of rock type on tool selection, select hobs or cutter heads or scrapers according to different rock types, select corresponding materials to improve the wear resistance of the tool, determine the shape and size of the tool, and The average compressive strength Pkqd, shear strength Jqqd, cutting force Djqx, cutting rate Qxsl and wear rate Msxl of the tool are calculated. The number and arrangement of the tools are determined based on the above analysis and calculation results. The excavation efficiency Jjxl and cost-effectiveness Cbxy of the optimal tool configuration are calculated based on the geological data and tool performance. The excavation efficiency and cost-effectiveness of the tunnel boring machine after the tool configuration are analyzed, and the optimal tool configuration scheme is selected. This method abandons the tool configuration based on personal experience and data estimation, and selects the optimal tool configuration scheme based on the detailed calculation and analysis of geological data and tool parameters. It has the advantages of improving the working efficiency of the tunnel boring machine and reducing cost waste, thus solving the above problems.

[0005] To achieve the above object, the present invention provides the following technical solution: a tunnel boring machine tool configuration method based on geological data, comprising the following steps:

[0006] S1. Obtain core samples through geological radar and geological exploration, analyze and determine the types of soil and rocks, collect the compressive strength, shear strength, elastic modulus and Poisson's ratio of rocks, and record the thickness, distribution and interlayer relationship of strata;

[0007] S2. Classify rocks into hard rock, soft rock and other types according to their physical and mechanical properties, draw strength distribution maps of different strata, and analyze the impact of rock types on tool selection;

[0008] S3. Select the hob, cutter head or scraper according to different rock types, select the corresponding material to improve the wear resistance of the tool, determine the shape and size of the tool, and calculate the average compressive strength Pkqd, shear strength Jqqd, cutting force Djqx, cutting rate Qxsl and wear rate Msxl of the tool;

[0009] S4. Determine the number and arrangement of the cutters based on the above analysis and calculation results, and calculate the tunneling efficiency Jjxl and cost-effectiveness Cbxy of the optimal cutter configuration based on geological data and cutter performance;

[0010] S5. Analyze the tunneling efficiency and cost-effectiveness of the tunnel boring machine after tool configuration and select the optimal tool configuration solution.

[0011] Preferably, the formula for calculating the average compressive strength Pkqd of the tool in S3 is as follows:

[0012]

[0013] In the formula, Pkqd represents the average compressive strength of the tool, n represents the number of tools, Kyqd i It represents the compressive strength of the i-th tool. The summation formula represents the summation of the tool compressive strength, calculated from the first data to the n-th data, and then divided by the number of tools n to obtain the average compressive strength of the tool.

[0014] Preferably, the formula for calculating the tool shear strength Jqqd in S3 is as follows:

[0015]

[0016] In the formula, Jqqd represents the shear strength of the tool, Pkqd represents the average compressive strength of the tool, Txml represents the elastic modulus of the material, and Jqml represents the shear modulus of the material, which is measured by the instrument. The formula is divided by 2 to indicate that the relationship between shear strength and normal stress is nonlinear. Represents a dimensionless ratio.

[0017] Preferably, the formula for calculating the cutting force Djqx of the tool in S3 is as follows:

[0018] Djqx=Ka c *Qxd*

[0019] In the formula, Djqx represents the cutting force of the tool, Ka c represents the cutting resistance coefficient, Qxsd represents the cutting depth, and Kd represents the cutting width.

[0020] Preferably, the formula for calculating the cutting rate Qxsl by S3 is as follows:

[0021] Qxsl=Djzs*Dc*π

[0022] In the formula, Qxsl represents the cutting rate, Djzs represents the tool speed, Dc represents the tool diameter, and π represents 3.1415.

[0023] Preferably, the formula for calculating the wear rate Msxl in S3 is as follows:

[0024]

[0025] In the formula, Msxl represents the wear rate, V w represents the wear volume, and t represents the usage time.

[0026] Preferably, the formula for calculating the tunneling efficiency Jjxl of the optimal tool configuration in S4 is as follows:

[0027]

[0028] In the formula, Jjxl represents the excavation efficiency of the optimal tool configuration, Jjcd represents the excavation length, and Wcsj represents the time required to complete the excavation.

[0029] Preferably, the formula for calculating the cost-effectiveness Cbxy in S4 is as follows:

[0030]

[0031] In the formula, Cbxy represents cost-effectiveness, Jdsy represents the benefits brought by excavation, and C represents the total cost generated by the tool configuration and its use.

[0032] Preferably, S5 analyzes the tunneling efficiency and cost-effectiveness of the tunnel boring machine after the tool configuration and selects the optimal tool configuration scheme in the following manner:

[0033] When the excavation efficiency and cost-effectiveness of the optimal tool configuration are both greater than 90%, it means that the tool selection is optimal at this time, otherwise it returns to S2 for a new round of calculation and analysis.

[0034] Compared with the prior art, the present invention provides a method for configuring the cutter of a tunnel boring machine based on geological data, which has the following beneficial effects:

[0035] The present invention obtains core samples by means of geological radar and geological exploration, analyzes and determines the types of soil and rock, collects the compressive strength, shear strength, elastic modulus and Poisson's ratio of the rock, records the thickness, distribution and interlayer relationship of the stratum, including groundwater level, flow velocity, permeability and groundwater chemical properties, classifies the rock into hard rock, soft rock and other types according to its physical and mechanical properties, draws strength distribution diagrams of different strata, analyzes the influence of rock type on tool selection, selects a hob or a cutter head or a scraper according to different rock types, selects corresponding materials to improve the wear resistance of the tool, determines the shape and size of the tool, and calculates the average compressive strength Pk of the tool qd, tool shear strength Jqqd, tool cutting force Djqx, cutting rate Qxsl and wear rate Msxl. The number and arrangement of tools are determined according to the above analysis and calculation results. The excavation efficiency Jjxl and cost-effectiveness Cbxy of the optimal tool configuration are calculated according to the geological data and tool performance. The excavation efficiency and cost-effectiveness of the tunnel boring machine after the tool configuration are analyzed, and the optimal tool configuration scheme is selected. This method abandons the tool configuration based on personal experience and data estimation, and selects the optimal tool configuration scheme based on the detailed calculation and analysis of geological data and tool parameters, which improves the working efficiency of the tunnel boring machine and reduces cost waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the steps of the method of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] At present, the tool configuration of tunnel boring machines often relies on personal experience and data estimation. The tool configuration scheme under this method is not the most reasonable, resulting in low excavation efficiency and cost waste. Therefore, a tunnel boring machine tool configuration method based on geological data is proposed. Please refer to Figure 1 , the method comprises the following steps:

[0039] S1. Obtain core samples through geological radar and geological exploration, analyze and determine the types of soil and rocks, collect the compressive strength, shear strength, elastic modulus and Poisson's ratio of rocks, and record the thickness, distribution and interlayer relationship of strata;

[0040] By combining geological radar with traditional geological exploration methods, detailed information about underground rock and soil can be obtained efficiently and accurately, so as to provide a scientific basis for subsequent engineering analysis and design. In this process, geological radar technology is first used to detect underground structures, obtain three-dimensional images and trends of underground strata, and identify the thickness, distribution and interlayer relationship of rock and soil layers. Geological radar has the advantages of strong penetration ability and fast imaging speed. It can comprehensively evaluate the underground situation without destroying the original geological structure, and discover potential geological faults, buried objects and hydrological conditions;

[0041] After obtaining radar data, we further combined field geological exploration to obtain core samples through drilling. During the drilling process, we used high-precision drilling rigs and adjusted drilling parameters according to the characteristics of different geological layers to ensure the integrity and representativeness of the samples. The core samples obtained were analyzed in the laboratory to measure the physical and mechanical properties of different rocks and soils, including key indicators such as compressive strength, shear strength, elastic modulus, and Poisson's ratio. These parameters are crucial for evaluating the bearing capacity and stability of rock and soil and avoiding safety hazards in subsequent projects.

[0042] Through data recording and processing, more systematic stratigraphic information can be obtained, including thickness changes, main mineral components, porosity, density and their interrelationships of each rock layer. This comprehensive method not only improves the accuracy and efficiency of geotechnical exploration, but also provides reliable basic data for engineering design, thereby better adapting to local geological conditions.

[0043] S2. Classify rocks into hard rock, soft rock and other types according to their physical and mechanical properties, draw strength distribution maps of different strata, and analyze the impact of rock types on tool selection;

[0044] The criteria for classifying rocks into hard rock, soft rock and other types are as follows:

[0045] Rocks with compressive strength greater than 100Mpa, elastic modulus greater than 50Gpa, and Poisson’s ratio in the range of 0.2-0.3 are classified as hard rocks;

[0046] Rocks with a compressive strength greater than or equal to 10Mpa and less than or equal to 100Mpa, an elastic modulus greater than or equal to 20Gpa and less than or equal to 50Gpa, and a Poisson's ratio greater than 0.25 are classified as soft rocks;

[0047] Rocks with compressive strength less than 10Mpa, elastic modulus less than 20Gpa, and Poisson's ratio greater than 0.3 are classified as other rocks;

[0048] S3. Select the hob, cutter head or scraper according to different rock types, select the corresponding material to improve the wear resistance of the tool, determine the shape and size of the tool, and calculate the average compressive strength Pkqd, shear strength Jqqd, cutting force Djqx, cutting rate Qxsl and wear rate Msxl of the tool;

[0049] Hard rocks such as granite, basalt, and hard limestone have high compressive and shear strengths and usually require extremely hard tools for cutting. Hobs can effectively cut hard rocks and are suitable for situations where continuous cutting is required. The design of the hob enables it to apply pressure evenly when rotating at high speed, thereby reducing tool wear and improving rock breaking efficiency.

[0050] Soft rocks such as clay, sandstone, and soft limestone have low compressive and shear strengths. Cutters should be selected to avoid excessive damage and wear. To cope with relatively soft materials, the cutter head has good cutting and non-destructive characteristics, suitable for fast work in relatively soft formations. Its design allows deeper cutting and larger cutting width, thereby improving excavation efficiency. The scraper is suitable for excavation of muddy and loose soils, which can effectively remove formation materials and reduce soil disturbance. The effective cutting edge design of the scraper helps to provide greater flexibility when handling soft materials, especially in the presence of moisture.

[0051] In other types of rock, i.e. composite layers, it is necessary to use a combination of tools to better exert the excavation ability of the tools;

[0052] After the tool is selected, the relevant parameters of the tool are calculated, including:

[0053] The calculation formula of the average compressive strength of the tool is as follows:

[0054]

[0055] Evaluation of the compressive strength of different rock types can help select suitable tool materials to avoid damage or failure due to insufficient tool strength. In the formula, Pkqd represents the average compressive strength of the tool, n represents the number of tools, Kyqd i It represents the compressive strength of the i-th tool. The summation formula represents the summation of the tool compressive strength, calculated from the first data to the n-th data, and then divided by the number of tools n to obtain the average compressive strength of the tool. By understanding the average compressive strength of the rock, high-hardness alloys, diamonds and other materials can be selected in a targeted manner to improve the service life and work efficiency of the tool.

[0056] The calculation formula of tool shear strength is as follows:

[0057]

[0058] Understanding the shear strength of the tool can help engineers determine the cutting ability of the tool under different formation conditions and ensure that the tool can effectively cut the rock without causing excessive wear. In the formula, Jqqd represents the shear strength of the tool, Pkqd represents the average compressive strength of the tool, Txml represents the elastic modulus of the material, and Jqml represents the shear modulus of the material, which is measured by the instrument. In the formula, Jqqd represents the shear strength of the tool, Pkqd represents the average compressive strength of the tool, Txml represents the elastic modulus of the material, and Jqml represents the shear modulus of the material, which is measured by the instrument. The formula is divided by 2 to indicate that the relationship between shear strength and normal stress is nonlinear. It represents a dimensionless ratio. According to the calculation results of shear strength, the geometric shape of the tool can be optimized, its cutting characteristics can be enhanced, and the construction efficiency can be improved;

[0059] The cutting force calculation formula of the tool is as follows:

[0060] Djqx=Ka c *Qxd*

[0061] Accurate cutting force can optimize construction planning and operation sequence, improve overall construction efficiency, and prevent equipment from overloading. In the formula, Djqx represents the cutting force of the tool, Ka c It indicates the cutting resistance coefficient. This value can be obtained from the factory manual of the tool production. Qxsd indicates the cutting depth and Kd indicates the cutting width. The above values ​​are obtained through instrument measurement. By calculating the cutting force, the load of the tool under different working conditions can be clarified, thereby helping to select appropriate mechanical equipment and power configuration;

[0062] The cutting rate calculation formula is as follows:

[0063] Qxsl=Djzs*Dc*π

[0064] The calculation of cutting rate helps to determine the working efficiency of the tool under specific geological conditions, so as to formulate a more reasonable construction rhythm and shorten the construction time. In the formula, Qxsl represents the cutting rate, Djzs represents the tool speed, and Dc represents the tool diameter. The speed and diameter are obtained from the tool numerical manual. π represents 3.1415. Improving the cutting rate can reduce the time and resource consumption required to complete the operation, thereby reducing the construction cost.

[0065] The wear rate calculation formula is as follows:

[0066]

[0067] By monitoring and calculating the wear rate, the service life of the tool under various working conditions can be evaluated, providing data support for equipment maintenance and replacement. In the formula, Msxl represents the wear rate, V w represents the wear volume, t represents the use time, and reasonable control and prediction of the wear rate can not only reduce the frequency of tool replacement and production costs, but also ensure that the equipment operates in the optimal state, thereby improving the safety and economy of the overall project;

[0068] S4. Determine the number and arrangement of the cutters based on the above analysis and calculation results, and calculate the tunneling efficiency Jjxl and cost-effectiveness Cbxy of the optimal cutter configuration based on geological data and cutter performance;

[0069] According to the above analysis and calculation results, rock strength tests were conducted in the tunnel project. The results showed that the average compressive strength was 150Mpa, the shear strength was 50Mpa, the required cutting force was 5kN, and the cutting rate was set to 0.5m / mmin, and the wear rate was 0.1mm / h. According to the compressive strength and the calculated cutting force, the compressive strength of a single tool is 100Mpa, and the cutting force it can bear is 4kN. Then, under the rock of 150Mpa, in order not to make the carrying capacity of each tool close to the limit, the number of tools needs to be selected as 12 to disperse the load. Taking into account the cutting rate of 0.5m / mmin, in order to improve the construction efficiency, the tools should be designed in a staggered arrangement to ensure that the forces of the tools at different positions cooperate with each other, provide sufficient cutting capacity and be relatively uniform;

[0070] The formula for calculating the excavation efficiency of the optimal tool configuration is as follows:

[0071]

[0072] By optimizing the configuration of the cutter, the excavation speed can be increased, thereby shortening the construction period of the entire project. Excavation efficiency is directly related to the progress of the project. Optimized tool configuration can ensure that more work can be completed in the same amount of time. In the formula, Jjxl represents the excavation efficiency of the optimal tool configuration, Jjcd represents the excavation length, and Wcsj represents the excavation completion time. The above values ​​are obtained through the engineering record manual. Effective tool configuration reduces equipment failures caused by overload or uneven wear, reduces accidental risks during construction, and thus ensures the safety of workers and equipment;

[0073] The cost-effectiveness calculation formula is as follows:

[0074]

[0075] Reasonable configuration of tools can reduce the energy consumption of equipment, because the tools require less energy when cutting, which helps save oil or electricity. In the formula, Cbxy represents cost-effectiveness, Jdsy represents the benefits brought by excavation, and C represents the total cost of tool configuration and its use. The above values ​​are obtained through record keeping. By analyzing various expenses, budgets and cost control can be prepared more accurately to avoid cost waste;

[0076] S5. Analyze the tunneling efficiency and cost-effectiveness of the tunnel boring machine after tool configuration and select the optimal tool configuration solution;

[0077] When the excavation efficiency and cost-effectiveness of the optimal tool configuration are both greater than 90%, it means that the tool selection is optimal at this time, otherwise it returns to S2 for a new round of calculation and analysis.

[0078] The application of the above method eliminates the need to configure the cutter based on personal experience and data estimation. Instead, the optimal cutter configuration solution is selected based on detailed calculation and analysis of geological data and cutter parameters, which improves the working efficiency of the tunnel boring machine and reduces cost waste.

[0079] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for configuring a tunnel boring machine tool based on geological data, characterized in that: The following steps are involved: S1. Obtain core samples through geological radar and geological exploration, analyze and determine the types of soil and rocks, collect the compressive strength, shear strength, elastic modulus and Poisson's ratio of rocks, and record the thickness, distribution and interlayer relationship of strata; S2. Classify rocks into hard rock, soft rock and other types according to their physical and mechanical properties, draw strength distribution maps of different strata, and analyze the impact of rock types on tool selection; S3. Select the hob, cutter head or scraper according to different rock types, select the corresponding material to improve the wear resistance of the tool, determine the shape and size of the tool, and calculate the average compressive strength Pkqd, shear strength Jqqd, cutting force Djqx, cutting rate Qxsl and wear rate Msxl of the tool; S4. Determine the number and arrangement of the cutters based on the above analysis and calculation results, and calculate the excavation efficiency Jixl and cost-effectiveness Cbxy of the optimal cutter configuration based on geological data and cutter performance; S5. Analyze the tunneling efficiency and cost-effectiveness of the tunnel boring machine after tool configuration and select the optimal tool configuration solution.

2. A method for configuring a tunnel boring machine tool based on geological data according to claim 1, characterized in that: The formula for calculating the average compressive strength Pkqd of the tool S3 is as follows: In the formula, Pkqd represents the average compressive strength of the tool, n represents the number of tools, kyqd i It represents the compressive strength of the i-th tool. The summation formula represents the summation of the tool compressive strength, calculated from the first data to the n-th data, and then divided by the number of tools n to obtain the average compressive strength of the tool.

3. The method for configuring a tunnel boring machine tool based on geological data according to claim 2, characterized in that: The formula for calculating the tool shear strength Jqqd of S3 is as follows: In the formula, Jqqd represents the shear strength of the tool, Pkqd represents the average compressive strength of the tool, Txml represents the elastic modulus of the material, and Jqml represents the shear modulus of the material, which is measured by the instrument. The formula is divided by 2 to indicate that the relationship between shear strength and normal stress is nonlinear. Represents a dimensionless ratio.

4. The method for configuring a tunnel boring machine tool based on geological data according to claim 3, characterized in that: The formula for calculating the cutting force Djqx of the tool S3 is as follows: <h2 style=";text-align:left;direction:ltr">Djqx=Ka<h2 style=";text-align:left;direction:ltr"> c <h2 style=";text-align:left;direction:ltr"> *Qxsd*Kd In the formula, Djqx represents the cutting force of the tool, Ka c represents the cutting resistance coefficient, Qxsd represents the cutting depth, and Kd represents the cutting width.

5. The method for configuring a tunnel boring machine tool based on geological data according to claim 4, characterized in that: The formula for calculating the cutting rate Qxsl is as follows: Qxsl=Djzs*Dc*π In the formula, Qxsl represents the cutting rate, Djzs represents the tool speed, Dc represents the tool diameter, and π represents 3.1415.

6. The method for configuring a tunnel boring machine tool based on geological data according to claim 5, characterized in that: The formula for calculating the wear rate Msxl of S3 is as follows: In the formula, Msxl represents the wear rate, V w represents the wear volume, and t represents the usage time.

7. The method for configuring a tunnel boring machine tool based on geological data according to claim 6, characterized in that: The formula for calculating the tunneling efficiency Jjxl of the optimal tool configuration in S4 is as follows: In the formula, Jixl represents the excavation efficiency of the optimal tool configuration, Jjcd represents the excavation length, and Wcsj represents the time required to complete the excavation.

8. The method for configuring cutters of a tunnel boring machine based on geological data according to claim 7, characterized in that: The formula for calculating the cost-effectiveness Cbxy in S4 is as follows: In the formula, Cbxy represents cost-effectiveness, Jdsy represents the benefits brought by excavation, and C represents the total cost generated by the tool configuration and its use.

9. The method for configuring cutters of a tunnel boring machine based on geological data according to claim 8, characterized in that: The S5 analyzes the tunnel boring machine excavation efficiency and cost-effectiveness after the tool configuration and selects the optimal tool configuration scheme in the following manner: When the excavation efficiency and cost-effectiveness of the optimal tool configuration are both greater than 90%, it means that the tool selection is optimal at this time, otherwise it returns to S2 for a new round of calculation and analysis.

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