Tunnel boring machine assembly quality-effect evaluation method

Abstract

The invention provides a tunnel boring machine assembly quality and efficiency evaluation method. The method is applied to the technical field of tunnel boring machine assembly quality and efficiency evaluation and comprises the steps that after tunnel boring machine assembly is completed, assembly position errors and assembly roughness corresponding to a cutterhead, a propelling system, a track and a supporting system of a tunnel boring machine are measured respectively; determining a total assembly position error according to each assembly position error; determining the total assembly roughness according to each assembly roughness; carrying out pilot run on the tunnel boring machine within a preset time, and obtaining the tunneling amount, power consumption, amplitude, eccentricity ratio and deflection angle during the pilot run; according to the total assembly position error, the total assembly roughness, the tunneling amount, the power consumption, the amplitude, the eccentricity rate and the deflection angle, the assembly quality-effect score of the tunnel boring machine is calculated; and determining the assembly quality-effect grade of the tunnel boring machine according to the assembly quality-effect score of the tunnel boring machine. In this way, the efficiency of tunnel boring machine assembly quality-effect evaluation can be improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of tunnel boring machine assembly quality and efficiency evaluation, and in particular to a tunnel boring machine assembly quality and efficiency evaluation method. Background Art

[0002] As an important equipment in modern tunnel engineering, the assembly quality and efficiency of tunnel boring machines directly affect the progress and safety of the project. High-quality assembly can ensure that the machine is more stable during operation and reduce the failure rate, thereby improving the excavation speed and efficiency. In tunnel construction, time is cost, and any downtime caused by equipment failure will cause economic losses. Therefore, ensuring the assembly quality of the tunnel boring machine can effectively shorten the project cycle and reduce construction costs; detail management and quality control in the assembly process can reduce potential safety hazards. Through strict assembly quality assessment, safety risks can be reduced at the source and the lives of construction workers can be protected; through detailed analysis of assembly quality, the design scheme can be optimized, the assembly process can be improved, and the overall performance of the equipment can be improved. Continuous quality feedback and improvement can It can make the tunnel boring machine more reliable and efficient in continuous use; through the collection and analysis of data in the assembly process, technical bottlenecks and room for improvement can be identified, thereby stimulating the research and development and innovation of related technologies to improve the performance and service life of the tunnel boring machine; high-quality equipment can reduce the frequency of maintenance and replacement, reduce operating costs, and through strict control and evaluation of assembly quality, a reasonable budget and investment expectations can be established at the beginning of the project to ensure the maximization of the economic benefits of the project; high-quality assembly can improve the energy efficiency of equipment and reduce unnecessary waste of resources. At the same time, reducing the failure rate also means reducing resource consumption during maintenance, which helps to achieve green construction goals. Therefore, the quality and efficiency evaluation of tunnel boring machine assembly is of great significance.

[0003] At present, in the process of evaluating the quality and efficiency of tunnel boring machine assembly, judgments are usually made based on manual evaluation or expert experience, which is time-consuming and labor-intensive, resulting in low efficiency in the evaluation of the quality and efficiency of tunnel boring machine assembly. Summary of the invention

[0004] The present invention provides a method for evaluating the assembly quality and efficiency of a tunnel boring machine.

[0005] According to a first aspect of the present disclosure, a method for evaluating the assembly quality and efficiency of a tunnel boring machine is provided. The method comprises:

[0006] After the tunnel boring machine is assembled, the assembly position errors and assembly roughness of the cutter head, propulsion system, track, and support system of the tunnel boring machine are measured respectively; the total assembly position error is determined based on each assembly position error; the total assembly roughness is determined based on each assembly roughness;

[0007] The tunnel boring machine is tested within a preset time, and the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run are obtained;

[0008] The tunnel boring machine assembly quality and efficiency score is calculated based on the overall assembly position error, overall assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; the tunnel boring machine assembly quality and efficiency grade is determined based on the tunnel boring machine assembly quality and efficiency score; the tunnel boring machine assembly quality and efficiency grades include excellent, good, fair, and poor.

[0009] Further, determining the total assembly position error according to each assembly position error; and determining the total assembly roughness according to each assembly roughness include:

[0010] According to each assembly position error and the corresponding error weight, the total assembly position error Z is calculated. pwc ;

[0011] According to the roughness of each assembly and the corresponding roughness weight, the total assembly roughness C is calculated. pcc ;

[0012] If 0<Z pwc <Z pwc1 , then the error level of the tunnel boring machine is determined to be the first error level;

[0013] If Z pwc1 ≤Z pwc <Z pwc2 And 0<C pcc <C pcc1 , then the error level of the tunnel boring machine is determined to be the first error level; if Z pwc1 ≤Z pwc <Z pwc2 And C pcc1 ≤C pcc <C pcc2 , then the error level of the tunnel boring machine is determined to be the second error level; if Z pwc1 ≤Z pwc <Z pwc2 And C pcc ≥C pcc2 , then the error level of the tunnel boring machine is determined to be the third error level;

[0014] If Z pwc ≥Z pwc2 , then the error level of the tunnel boring machine is determined to be the third error level;

[0015] When the error level of the tunnel boring machine is the first error level or the second error level, performing a trial run of the tunnel boring machine within a preset time;

[0016] Among them, Z pwc1is the first preset total assembly position error, Z pwc2 is the second preset total assembly position error, C pcc1 is the first preset total assembly roughness, Z pwc2 The total assembly roughness is preset for the second.

[0017] Furthermore, the tunnel boring machine is tested within a preset time and the excavation amount, power consumption, amplitude, eccentricity and deflection angle during the test run are obtained, including:

[0018] Obtain the eccentricity L of the tunnel boring machine during the trial operation in real time;

[0019] If 0<L<L 1 , then the eccentricity risk level of the tunnel boring machine trial operation is determined to be the first eccentricity risk level;

[0020] If L 1 ≤L<L 2 , then the eccentricity risk level of the tunnel boring machine trial operation is determined to be the second eccentricity risk level;

[0021] If L ≥ L 2 , the eccentricity risk level of the trial run of the tunnel boring machine is determined to be the third eccentricity risk level; at this time, the trial run of the tunnel boring machine is immediately stopped, and the assembly quality efficiency level of the tunnel boring machine is determined to be poor;

[0022] Among them, L 1 is the first preset eccentricity, L 2 is the second preset eccentricity.

[0023] Furthermore, the step of conducting a trial run of the tunnel boring machine within a preset time and obtaining the tunneling amount, power consumption, amplitude, eccentricity, and deflection angle during the trial run also includes:

[0024] Real-time acquisition of the amplitude F, eccentricity L, and deflection angle D of the tunnel boring machine during the trial run;

[0025] If L 1 ≤L<L 2 And 0<F≤F 1 , then continue with the trial operation of the tunnel boring machine;

[0026] If L 1 ≤L<L 2 And 0<D≤D 1 , then continue with the trial operation of the tunnel boring machine;

[0027] If L 1 ≤L<L 2 And F>F 1 And D>D 1, the trial operation of the tunnel boring machine is immediately stopped, and the assembly quality and efficiency level of the tunnel boring machine is judged to be poor;

[0028] Among them, F 1 is the preset amplitude, D 1 is the preset deflection angle.

[0029] Furthermore, the calculation of the tunnel boring machine assembly quality and efficiency score according to the overall assembly position error, overall assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle includes:

[0030] The accuracy score R is calculated based on the total assembly position error and the corresponding scoring weight, the total assembly roughness and the corresponding scoring weight. jd ;

[0031] The efficiency score R is calculated based on the excavation volume and the corresponding scoring weight, power consumption and the corresponding scoring weight, trial operation time and the corresponding scoring weight. xl ;

[0032] The stability score R is calculated based on the amplitude and the corresponding score weight, the eccentricity and the corresponding score weight, the deflection angle and the corresponding score weight. wd ;

[0033] The tunnel boring machine assembly quality and efficiency score R is calculated based on the accuracy score and the corresponding score weight, efficiency score and the corresponding score weight, stability score and the corresponding score weight. zp .

[0034] Furthermore, the step of determining the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score comprises:

[0035] If 0<R zp ≤R 1 , the tunnel boring machine assembly quality efficiency level is judged to be poor, and a trial run failure message is generated;

[0036] If R 1 <R zp ≤R 2 , the tunnel boring machine assembly quality and efficiency level is judged to be general, and according to the accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information;

[0037] If R 2 <R zp ≤R 3 , the tunnel boring machine assembly quality and efficiency level is determined to be good, and a trial run success message is generated;

[0038] If R3 <R zp ≤1, the TBM assembly quality and efficiency level is judged to be excellent, and a trial run success message is generated;

[0039] Among them, R 1 Rating for the first preset, R 2 Rating for the first preset, R 3 Rating for the first preset, R 1 <R 2 <R 3 <1.

[0040] Furthermore, the accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information, including:

[0041] If R jd <R jd0 , R xl <R xl0 , R wd <R wd0 , then a test run failure message is generated, otherwise a test run success message is generated; where R jd0 R is the preset accuracy score. xl0 R is the preset efficiency score, R wd0 Rate the preset stability.

[0042] According to a second aspect of the present disclosure, a device for evaluating the assembly quality and efficiency of a tunnel boring machine is provided. The device comprises:

[0043] The first determination module is used to measure the assembly position errors and assembly roughnesses of the cutter head, propulsion system, track, and support system of the tunnel boring machine respectively after the tunnel boring machine is assembled; determine the total assembly position error according to each assembly position error; and determine the total assembly roughness according to each assembly roughness;

[0044] An acquisition module, used to test run the tunnel boring machine within a preset time and obtain the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run;

[0045] The second determination module is used to calculate the tunnel boring machine assembly quality and efficiency score according to the total assembly position error, total assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; and determine the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score; the tunnel boring machine assembly quality and efficiency grade includes excellent, good, general and poor.

[0046] According to a third aspect of the present disclosure, an electronic device is provided. The electronic device includes: a memory and a processor, wherein a computer program is stored in the memory, and the method is implemented when the processor executes the program.

[0047] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and the program implements the method when executed by a processor.

[0048] According to the embodiment of the present invention, by measuring the assembly position error and roughness of the cutterhead, propulsion system, track and support system respectively, the actual assembly status of each component can be fully understood to ensure that each component of the tunnel boring machine is in the best state; the concept of total assembly position error and total assembly roughness is adopted, so that the evaluation is not limited to a single component, but the assembly quality of the entire tunnel boring machine is comprehensively considered to provide a more comprehensive performance performance; after assembly, a trial run is carried out to dynamically monitor parameters such as excavation volume, power consumption, amplitude, eccentricity and deflection angle, which is helpful to verify the correlation between the assembly effect and the actual operating performance, timely discover potential problems, and thus improve the efficiency of the tunnel boring machine assembly quality and efficiency evaluation; based on the collected data, quality and efficiency scoring and grade assessment are carried out to ensure the objectivity and scientificity of the evaluation process; after the evaluation, tunnel boring machines with excellent, good and general assembly quality can be quickly screened out, so that high-quality equipment can be used preferentially in the project promotion, failures and downtime can be reduced, and the overall efficiency of the project can be improved; high-quality assembly quality directly affects the safety and reliability of tunnel excavation, and this solution can effectively reduce the safety hazards caused by improper assembly.

[0049] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0051] In the accompanying drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0052] Figure 1 A flow chart of a method for evaluating the assembly quality and efficiency of a tunnel boring machine according to an embodiment of the present disclosure is shown;

[0053] Figure 2 A block diagram of a device for evaluating the assembly quality and efficiency of a tunnel boring machine according to an embodiment of the present disclosure is shown;

[0054] Figure 3A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0056] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0057] Figure 1 A flow chart of a method for evaluating the assembly quality and efficiency of a tunnel boring machine according to an embodiment of the present disclosure is shown, the method comprising:

[0058] S101, after the tunnel boring machine is assembled, respectively measure the assembly position errors and assembly roughnesses corresponding to the cutter head, propulsion system, track, and support system of the tunnel boring machine; determine the total assembly position error based on each assembly position error; and determine the total assembly roughness based on each assembly roughness.

[0059] In some embodiments, according to the characteristics and requirements of the tunnel boring machine, appropriate measuring tools and instruments are prepared, such as micrometers, micrometers, laser rangefinders, roughness meters, etc.; ensure that the measuring personnel are familiar with the use of measuring tools and instruments, understand the requirements of the measurement plan, and conduct necessary operation training; use a laser rangefinder or other applicable measuring tools to measure the deviation between the actual installation position and the designed position of the cutterhead, including errors in the horizontal, vertical and axial directions; use a roughness meter to measure the roughness on the key surface of the cutterhead and record relevant data; check the assembly position of each component of the propulsion system (such as propulsion cylinders, guide rails, etc.), and use measuring tools to measure their deviation from the designed position; perform roughness measurements on important contact surfaces and moving parts of the propulsion system; use tools such as laser rangefinders or rulers to measure the difference between the actual installation position and the designed position of the track to ensure the straightness and horizontality of the track; perform roughness measurements on the contact surfaces and key parts of the track; check the assembly position of each component of the support system (such as support plates, support cylinders, etc.), and measure their deviation from the designed position; perform roughness measurements on important contact surfaces and force-bearing parts of the support system.

[0060] In some embodiments, the calculation formula of the total assembly position error can be:

[0061] Z pwc =1.4×Z dp ×2.1×Z tj ×1.3×Z gd ×3.2×Z zh

[0062] Among them, Z pwc is the total assembly position error, Z dp is the cutter head assembly position error, Z tj is the propulsion system assembly position error, Z gd is the track assembly position error, Z zh Assembly position error for the support system.

[0063] In some embodiments, the calculation formula of the cutter head assembly position error can be:

[0064] Z dp =1.45×Z sp ×2.26×Z cz 2 ×3.25×Z zx 3

[0065] Among them, Z dp is the cutter head assembly position error, Z sp is the horizontal assembly position error of the cutter head, Z cz is the vertical assembly position error of the cutter head, Z zx It is the axial assembly position error of the cutter disc.

[0066] In some embodiments, the calculation formula of the overall assembly roughness may be:

[0067] C pcc =2.3×C dp ×1.5×C tj ×1.6×C gd ×3.1×C zh

[0068] Among them, C pcc is the total assembly roughness, C dp C is the cutter head assembly roughness, tj is the assembly roughness of the propulsion system, C gd is the track assembly roughness, C zh Assemble roughness for support system.

[0069] In some embodiments, determining the total assembly position error according to each assembly position error; determining the total assembly roughness according to each assembly roughness includes: calculating the total assembly position error Z according to each assembly position error and the corresponding error weight pwc ; According to each assembly roughness and the corresponding roughness weight, the total assembly roughness C is calculated pcc ; If 0<Z pwc <Z pwc1 , then the error level of the tunnel boring machine is determined to be the first error level; if Z pwc1 ≤Z pwc <Z pwc2 And 0<C pcc <C pcc1 , then the error level of the tunnel boring machine is determined to be the first error level; if Z pwc1 ≤Z pwc <Z pwc2 And C pcc1 ≤C pcc <C pcc2 , then the error level of the tunnel boring machine is determined to be the second error level; if Z pwc1 ≤Z pwc <Z pwc2 And C pcc ≥C pcc2 , then the error level of the tunnel boring machine is determined to be the third error level; if Z pwc ≥Z pwc2 , it is determined that the error level of the tunnel boring machine is the third error level; when the error level of the tunnel boring machine is the first error level or the second error level, the tunnel boring machine is tested within a preset time; wherein Z pwc1 is the first preset total assembly position error, Z pwc2 is the second preset total assembly position error, C pcc1 is the first preset total assembly roughness, Z pwc2is the second preset total assembly roughness. According to the embodiment of the present invention, by simultaneously considering the assembly position error and the assembly roughness, and calculating the total error according to different error weights, the assembly quality of the tunnel boring machine can be evaluated more comprehensively and accurately, avoiding the limitations of single indicator judgment, and improving the scientificity and rationality of the judgment; by setting multiple error levels, and judging by different error ranges and roughness combinations, the state of the tunnel boring machine can be divided more finely, which is helpful to take targeted maintenance and adjustment measures; through this systematic error evaluation and level judgment, potential problems can be discovered in advance, preventive and predictive maintenance can be carried out, serious failures of the equipment in actual operation can be avoided, and the reliability and service life of the equipment can be improved; by relying on specific error data and roughness data to make decisions, the errors of human judgment can be reduced, the accuracy and consistency of decisions can be improved, and the efficiency of the tunnel boring machine assembly quality and efficiency evaluation can be improved.

[0070] For example, according to each assembly position error and the corresponding error weight, the total assembly position error Z is calculated. pwc ; According to each assembly roughness and the corresponding roughness weight, the total assembly roughness C is calculated pcc ; If 0<Z pwc <1mm, the error level of the tunnel boring machine is determined to be the first error level; if 1mm≤Z pwc <2mm and 0<C pcc <1μm, the error level of the tunnel boring machine is determined to be the first error level; if 1mm≤Z pwc <2mm and 1μm≤C pcc <2μm, the error level of the tunnel boring machine is determined to be the second error level; if 1mm≤Z pwc <2mm and C pcc ≥2μm, the error level of the tunnel boring machine is determined to be the third error level; if Z pwc ≥2mm, the error level of the tunnel boring machine is determined to be the third error level; when the error level of the tunnel boring machine is the first error level or the second error level, the tunnel boring machine is tested within a preset time.

[0071] S102, test-running the tunnel boring machine within a preset time, and obtaining the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run.

[0072] In some embodiments, the step of conducting a trial run of the tunnel boring machine within a preset time and obtaining the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the trial run includes: obtaining the eccentricity L of the tunnel boring machine during the trial run in real time; if 0<L<L 1 , then the eccentricity risk level of the tunnel boring machine trial operation is determined to be the first eccentricity risk level; if L1 ≤L<L 2 , then the eccentricity risk level of the tunnel boring machine trial operation is determined to be the second eccentricity risk level; if L ≥ L 2 , then the eccentricity risk level of the TBM trial run is determined to be the third eccentricity risk level; at this time, the TBM trial run is immediately stopped, and the TBM assembly quality efficiency level is determined to be poor; where L 1 is the first preset eccentricity, L 2 is the second preset eccentricity. According to an embodiment of the present invention, by acquiring the eccentricity of the tunnel boring machine during the trial operation in real time, the operating status of the equipment can be quickly and accurately grasped, so that when the eccentricity risk level is high, the trial operation can be stopped immediately to avoid potential safety hazards or equipment damage; by setting three eccentricity risk levels, it is helpful to evaluate the operating risks of the equipment more carefully and provide corresponding response strategies for different risk levels; the automated decision-making process reduces human intervention, improves the consistency and reliability of decisions, and thus improves the efficiency of the tunnel boring machine assembly quality and efficiency evaluation; by setting a clear eccentricity risk level, it is possible to issue a warning in time when potential risks occur, and take corresponding preventive measures, which helps to prevent equipment failures in advance and ensure the efficient and safe operation of the tunnel boring machine; relying on specific eccentricity data to determine the risk level and quality and efficiency level reduces the influence of subjective judgment and improves the objectivity and accuracy of the evaluation.

[0073] For example, the eccentricity L of the tunnel boring machine during the trial operation is obtained in real time; if 0<L<0.5, the eccentricity risk level of the tunnel boring machine trial operation is determined to be the first eccentricity risk level; if 0.5≤L<0.8, the eccentricity risk level of the tunnel boring machine trial operation is determined to be the second eccentricity risk level; if L≥0.8, the eccentricity risk level of the tunnel boring machine trial operation is determined to be the third eccentricity risk level; at this time, the tunnel boring machine trial operation is immediately stopped, and the tunnel boring machine assembly quality and efficiency level is determined to be poor.

[0074] In some embodiments, the step of performing a trial run of the tunnel boring machine within a preset time and obtaining the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the trial run further includes: obtaining the amplitude F, eccentricity L, and deflection angle D of the tunnel boring machine during the trial run in real time; if L 1 ≤L<L 2 And 0<F≤F 1 , then continue the TBM trial operation; if L 1 ≤L<L 2 And 0<D≤D 1 , then continue the TBM trial operation; if L 1 ≤L<L 2 And F>F 1 And D>D1 , the trial operation of the tunnel boring machine is stopped immediately, and the assembly quality and efficiency level of the tunnel boring machine is judged to be poor; where F 1 is the preset amplitude, D 1 is a preset deflection angle. According to an embodiment of the present invention, by acquiring the amplitude, eccentricity and deflection angle of the tunnel boring machine during the trial operation in real time, the equipment operation status can be comprehensively evaluated from multiple dimensions, which can more comprehensively reflect the actual performance of the tunnel boring machine and improve the accuracy and scientificity of the judgment; by setting clear preset conditions, when the eccentricity is within a certain range and the amplitude or deflection angle is within the respective preset values, the trial operation is allowed to continue. This conditional trial operation strategy can further verify the performance of the tunnel boring machine without affecting the safety of the equipment; by considering the three parameters of eccentricity, amplitude and deflection angle at the same time, a flexible and specific risk assessment standard is set, which reduces the influence of subjective judgment and improves the objectivity and consistency of decision-making; relying on the data obtained in real time to make automated decisions, the trial operation is automatically stopped and the equipment quality and efficiency level is determined when specific conditions are met, which reduces human intervention and improves the efficiency and reliability of decision-making; the quality and efficiency level is determined based on the specific amplitude, eccentricity and deflection angle data, so that the evaluation result is more accurate and objective, which helps to discover potential problems and deficiencies of the equipment, thereby improving the efficiency of the tunnel boring machine assembly quality and efficiency evaluation.

[0075] For example, the amplitude F, eccentricity L, and deflection angle D of the tunnel boring machine during the trial operation are obtained in real time; if 0.5≤L<0.8 and 0<F≤0.5m, the trial operation of the tunnel boring machine continues; if 0.5≤L<0.8 and 0<D≤0.5°, the trial operation of the tunnel boring machine continues; if 0.5≤L<0.8 and F>0.5m and D>0.5°, the trial operation of the tunnel boring machine is stopped immediately, and the assembly quality and efficiency level of the tunnel boring machine is determined to be poor.

[0076] S103, calculating the tunnel boring machine assembly quality and efficiency score according to the total assembly position error, total assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; determining the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score; the tunnel boring machine assembly quality and efficiency grade includes excellent, good, fair, and poor.

[0077] In some embodiments, the calculating the tunnel boring machine assembly quality and efficiency score according to the overall assembly position error, overall assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle includes:

[0078] The accuracy score R is calculated based on the total assembly position error and the corresponding scoring weight, the total assembly roughness and the corresponding scoring weight. jd ;

[0079] The efficiency score R is calculated based on the excavation volume and the corresponding scoring weight, power consumption and the corresponding scoring weight, trial operation time and the corresponding scoring weight. xl ;

[0080] The stability score R is calculated based on the amplitude and the corresponding score weight, the eccentricity and the corresponding score weight, the deflection angle and the corresponding score weight. wd ;

[0081] The tunnel boring machine assembly quality and efficiency score R is calculated based on the accuracy score and the corresponding score weight, efficiency score and the corresponding score weight, stability score and the corresponding score weight. zp . According to the embodiment of the present invention, by respectively calculating the accuracy score, efficiency score and stability score, the assembly quality and efficiency of the tunnel boring machine can be comprehensively evaluated from multiple dimensions, which helps to fully understand the comprehensive performance of the equipment instead of relying solely on a single indicator; by quantifying factors such as the total assembly position error, total assembly roughness, excavation volume, power consumption, trial operation time, etc., and combining them with the corresponding scoring weights for calculation, the evaluation process is made more objective and operational, and the performance and gap of the equipment in various indicators can be clearly pointed out; the scoring weight of each score can be adjusted according to actual needs and priorities, so as to highlight specific performance indicators in different application scenarios. This flexibility makes the evaluation results more in line with actual application needs, can better guide operation and maintenance, and thus improve the efficiency of the tunnel boring machine assembly quality and efficiency evaluation.

[0082] In some embodiments, the step of determining the tunnel boring machine assembly quality efficiency grade according to the tunnel boring machine assembly quality efficiency score comprises: if 0 < R zp ≤R 1 , then the TBM assembly quality and efficiency level is judged to be poor, and a trial run failure message is generated; if R 1 <R zp ≤R 2 , the tunnel boring machine assembly quality and efficiency level is judged to be general, and according to the accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information; if R 2 <R zp ≤R 3 , then the tunnel boring machine assembly quality and efficiency level is judged to be good, and the trial run success information is generated; if R 3 <R zp ≤1, the tunnel boring machine assembly quality and efficiency level is judged to be excellent, and the trial run success information is generated; where R 1 Rating for the first preset, R 2 Rating for the first preset, R 3 Rating for the first preset, R1 <R 2 <R 3 <1. According to the embodiment of the present invention, by setting a plurality of clear quality and efficiency levels, the assembly quality and efficiency score of the tunnel boring machine is clearly divided into different standards, which helps users to quickly understand the performance status of the equipment and facilitates decision-making; the trial operation information (success or failure) is generated according to different scoring ranges to ensure that the operation results are systematically fed back. During the operation, if the score does not meet the standard, the failure information is immediately generated to facilitate rapid adjustment and improvement and reduce downtime; for the determination of the general level, not only the overall quality and efficiency score is considered, but also the accuracy score, efficiency score, and stability score are combined to provide a more comprehensive analysis, thereby improving the efficiency of the tunnel boring machine assembly quality and efficiency evaluation.

[0083] For example, if 0<R zp ≤0.2, the tunnel boring machine assembly quality efficiency level is judged to be poor, and a trial run failure message is generated; if 0.2<R zp ≤0.5, the tunnel boring machine assembly quality and efficiency level is judged to be general, and the accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information; if 0.5<R zp ≤0.7, the tunnel boring machine assembly quality and efficiency level is judged to be good, and the trial run success information is generated; if 0.7<R zp ≤1, the TBM assembly quality and efficiency level is judged to be excellent, and a trial run success message is generated.

[0084] In some embodiments, the accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information, including: jd <R jd0 , R xl <R xl0 , R wd <R wd0 , then a test run failure message is generated, otherwise a test run success message is generated; where R jd0 R is the preset accuracy score. xl0 R is the preset efficiency score, R wd0The preset stability score. According to the embodiment of the present invention, by evaluating the trial operation of the tunnel boring machine from the three key dimensions of accuracy, efficiency and stability, the performance of the equipment can be fully reflected, and the accuracy and reliability of the evaluation results can be ensured; by real-time monitoring and evaluation of the accuracy, efficiency and stability scores, success or failure information can be generated immediately after the trial operation is completed, which helps to quickly identify problems, reduce potential downtime and maintenance time, and thus improve the efficiency of the tunnel boring machine assembly quality and efficiency evaluation.

[0085] For example, if R jd <0.26, R xl <0.32, R wd <0.18, a trial run failure message is generated, otherwise a trial run success message is generated.

[0086] According to the embodiment of the present invention, by measuring the assembly position error and roughness of the cutterhead, propulsion system, track and support system respectively, the actual assembly status of each component can be fully understood to ensure that each component of the tunnel boring machine is in the best state; the concept of total assembly position error and total assembly roughness is adopted, so that the evaluation is not limited to a single component, but the assembly quality of the entire tunnel boring machine is comprehensively considered to provide a more comprehensive performance performance; after assembly, a trial run is carried out to dynamically monitor parameters such as excavation volume, power consumption, amplitude, eccentricity and deflection angle, which is helpful to verify the correlation between the assembly effect and the actual operating performance, timely discover potential problems, and thus improve the efficiency of the tunnel boring machine assembly quality and efficiency evaluation; based on the collected data, quality and efficiency scoring and grade assessment are carried out to ensure the objectivity and scientificity of the evaluation process; after the evaluation, tunnel boring machines with excellent, good and general assembly quality can be quickly screened out, so that high-quality equipment can be used preferentially in the project promotion, failures and downtime can be reduced, and the overall efficiency of the project can be improved; high-quality assembly quality directly affects the safety and reliability of tunnel excavation, and this solution can effectively reduce the safety hazards caused by improper assembly.

[0087] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0088] The above is an introduction to the method embodiment. The following is a further explanation of the scheme disclosed in the present invention through an apparatus embodiment.

[0089] Figure 2A block diagram of a tunnel boring machine assembly quality and efficiency evaluation device according to an embodiment of the present disclosure is shown, and the device includes:

[0090] The first determination module 201 is used to measure the assembly position errors and assembly roughnesses of the cutter head, propulsion system, track, and support system of the tunnel boring machine respectively after the tunnel boring machine is assembled; determine the total assembly position error according to each assembly position error; and determine the total assembly roughness according to each assembly roughness;

[0091] The acquisition module 202 is used to test run the tunnel boring machine within a preset time and obtain the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run;

[0092] The second determination module 203 is used to calculate the tunnel boring machine assembly quality and efficiency score according to the overall assembly position error, overall assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; and determine the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score; the tunnel boring machine assembly quality and efficiency grade includes excellent, good, fair, and poor.

[0093] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0094] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0095] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0096] Figure 3 A schematic block diagram of an electronic device that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0097] The electronic device includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM 302 or a computer program loaded from a storage unit 308 into a RAM 303. In the RAM 303, various programs and data required for the operation of the electronic device can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0098] A number of components in the electronic device are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0099] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the tunnel boring machine assembly quality and efficiency evaluation method. For example, in some embodiments, the tunnel boring machine assembly quality and efficiency evaluation method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via ROM 302 and / or a communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the tunnel boring machine assembly quality and efficiency evaluation method described above may be executed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the tunnel boring machine assembly quality and efficiency evaluation method in any other appropriate manner (eg, by means of firmware).

[0100] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0101] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0102] In the context of the present disclosure, a readable storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A readable storage medium may be a machine-readable signal medium or a machine-readable storage medium. A readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0103] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0104] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communications network). Examples of communications networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0105] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0106] It should be understood that the above-mentioned various forms of processes can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document does not limit this.

[0107] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for evaluating the assembly quality and efficiency of a tunnel boring machine, characterized in that: include: After the TBM is assembled, the assembly position error and assembly roughness of the cutter head, propulsion system, track and support system of the TBM are measured respectively; According to each assembly position error, the total assembly position error is determined; according to each assembly roughness, the total assembly roughness is determined; The tunnel boring machine is tested within a preset time, and the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run are obtained; Calculate the tunnel boring machine assembly quality and efficiency score based on the total assembly position error, total assembly roughness, excavation volume, power consumption, amplitude, eccentricity, and deflection angle; Determining the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score; The quality and efficiency grades of tunnel boring machine assembly include excellent, good, fair and poor.

2. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 1, characterized in that: Determining the total assembly position error based on the individual assembly position errors; According to the roughness of each assembly, the total assembly roughness is determined, including: According to each assembly position error and the corresponding error weight, the total assembly position error Z is calculated. pwc ; According to the roughness of each assembly and the corresponding roughness weight, the total assembly roughness C is calculated. pcc ; If 0<Z pwc <Z pwc1 , then the error level of the tunnel boring machine is determined to be the first error level; If Z pwc1 ≤Z pwc <Z pwc2 And 0<C pcc <C pcc1 , then the error level of the tunnel boring machine is determined to be the first error level; if Z pwc1 ≤Z pwc <Z pwc2 And C pcc1 ≤C pcc <C pcc2 , then the error level of the tunnel boring machine is determined to be the second error level; if Z pwc1 ≤Z pwc <Z pwc2 And C pcc ≥C pcc2 , then the error level of the tunnel boring machine is determined to be the third error level; If Z pwc ≥Z pwc2 , then the error level of the tunnel boring machine is determined to be the third error level; When the error level of the tunnel boring machine is the first error level or the second error level, performing a trial run of the tunnel boring machine within a preset time; Among them, Z pwc1 is the first preset total assembly position error, Z pwc2 is the second preset total assembly position error, C pcc1 is the first preset total assembly roughness, Z pwc2 Set the total assembly roughness for the second preset.

3. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 2, characterized in that: The step of conducting a trial run of the tunnel boring machine within a preset time and obtaining the tunneling amount, power consumption, amplitude, eccentricity, and deflection angle during the trial run includes: Obtain the eccentricity L of the tunnel boring machine during the trial operation in real time; If 0<L<L1, the eccentricity risk level of the trial operation of the tunnel boring machine is determined to be the first eccentricity risk level; If L1≤L<L2, the eccentricity risk level of the trial operation of the tunnel boring machine is determined to be the second eccentricity risk level; If L≥L2, the eccentricity risk level of the trial run of the tunnel boring machine is determined to be the third eccentricity risk level; at this time, the trial run of the tunnel boring machine is immediately stopped, and the assembly quality efficiency level of the tunnel boring machine is determined to be poor; Wherein, L1 is the first preset eccentricity, and L2 is the second preset eccentricity.

4. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 3, characterized in that: The method of testing the tunnel boring machine within a preset time and obtaining the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run also includes: Real-time acquisition of the amplitude F, eccentricity L, and deflection angle D of the tunnel boring machine during the trial run; If L1≤L<L2 and 0<F≤F1, the TBM trial operation will continue; If L1≤L<L2 and 0<D≤D1, the TBM trial operation will continue; If L1≤L<L2 and F>F1 and D>D1, the trial operation of the tunnel boring machine is stopped immediately and the assembly quality efficiency grade of the tunnel boring machine is judged to be poor; Among them, F1 is the preset amplitude, and D1 is the preset deflection angle.

5. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 4, characterized in that: The calculating of the tunnel boring machine assembly quality and efficiency score according to the total assembly position error, the total assembly roughness, the excavation amount, the power consumption, the amplitude, the eccentricity, and the deflection angle includes: The accuracy score R is calculated based on the total assembly position error and the corresponding scoring weight, the total assembly roughness and the corresponding scoring weight. jd ; The efficiency score R is calculated based on the excavation volume and the corresponding scoring weight, power consumption and the corresponding scoring weight, trial operation time and the corresponding scoring weight. xl ; The stability score R is calculated based on the amplitude and the corresponding score weight, the eccentricity and the corresponding score weight, the deflection angle and the corresponding score weight. wd ; The tunnel boring machine assembly quality and efficiency score R is calculated based on the accuracy score and the corresponding score weight, efficiency score and the corresponding score weight, stability score and the corresponding score weight. zp .

6. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 5, characterized in that: Determining the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score includes: If 0<R zp ≤R1, the TBM assembly quality and efficiency level is judged to be poor, and a trial run failure message is generated; If R1<R zp ≤R2, the tunnel boring machine assembly quality and efficiency level is judged to be general, and the accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information; If R2<R zp ≤R3, the TBM assembly quality and efficiency level is judged to be good, and the trial run success information is generated; If R3<R zp ≤1, the TBM assembly quality and efficiency level is judged to be excellent, and a trial run success message is generated; Among them, R1 is the first preset score, R2 is the first preset score, R3 is the first preset score, and R1<R2<R3<1.

7. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 6, characterized in that: The accuracy score R jd , efficiency score R xl , stability score R wd Generate trial run success information or trial run failure information, including: If R jd <R jd0 , R xl <R xl0 , R wd <R wd0 , then a test run failure message is generated, otherwise a test run success message is generated; where R jd0 R is the preset accuracy score. xl0 R is the preset efficiency score, R wd0 Rate the preset stability.

8. A tunnel boring machine assembly quality and efficiency evaluation device, characterized in that: include: The first determination module is used to measure the assembly position error and assembly roughness corresponding to the cutter head, propulsion system, track and support system of the tunnel boring machine respectively after the tunnel boring machine is assembled; According to each assembly position error, the total assembly position error is determined; according to each assembly roughness, the total assembly roughness is determined; An acquisition module, used to test run the tunnel boring machine within a preset time and obtain the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the test run; A second determination module is used to calculate the assembly quality and efficiency score of the tunnel boring machine according to the overall assembly position error, overall assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; Determining the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score; The quality and efficiency grades of tunnel boring machine assembly include excellent, good, fair and poor.

9. An electronic device, characterized in that: include: at least one processor; A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor so that the at least one processor can execute the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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