Evaluation method for assembly quality and efficiency of tunnel boring machines

Abstract

The present application provides a method for evaluating the assembly quality and efficiency of a tunnel boring machine. Applied to the technical field of tunnel boring machine assembly quality and efficiency evaluation, the method comprises the following steps: after the assembly of the tunnel boring machine is completed, measuring the assembly position error and assembly roughness corresponding to the cutter head, propulsion system, track, and support system of the tunnel boring machine; determining the total assembly position error based on each assembly position error; determining the total assembly roughness based on each assembly roughness; 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; calculating the tunnel boring machine assembly quality and efficiency score based on the total assembly position error, total assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; and determining the tunnel boring machine assembly quality and efficiency grade based on the tunnel boring machine assembly quality and efficiency score. In this way, the efficiency of the tunnel boring machine assembly quality and efficiency 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, reduce the failure rate, and thus improve the excavation speed and efficiency. In tunnel construction, time is cost, and any shutdown 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 plan 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 with continuous use; through the collection and analysis of data during 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, reducing operating costs. Through strict control and evaluation of assembly quality, reasonable budgets and investment expectations can be established at the beginning of the project to ensure the maximum economic benefits of the project; high-quality assembly can improve the energy efficiency of the 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 the goal of green construction. 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 of the quality and efficiency evaluation of tunnel boring machine assembly. Summary of the Invention

[0004] The present disclosure 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 TBM is assembled, the assembly position errors and assembly roughness of the cutterhead, propulsion system, track, and support system of the TBM are measured respectively; the total assembly position error is determined based on the individual assembly position errors; and the total assembly roughness is determined based on the individual assembly roughnesses;

[0007] 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;

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

[0009] Furthermore, determining the total assembly position error based on each assembly position error; and determining the total assembly roughness based on 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 Set the total assembly roughness for the second preset.

[0017] 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 includes:

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

[0019] If 0<L<L1, the eccentricity risk level of the tunnel boring machine trial run is determined to be the first eccentricity risk level;

[0020] If L1≤L<L2, the eccentricity risk level of the tunnel boring machine trial run is determined to be the second eccentricity risk level;

[0021] If L ≥ L2, the eccentricity risk level of the TBM trial run is determined to be the third eccentricity risk level; the TBM trial run is immediately stopped, and the TBM assembly quality efficiency level is determined to be poor;

[0022] Wherein, L1 is the first preset eccentricity, and L2 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 further includes:

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

[0025] If L1≤L<L2 and 0<F≤F1, then continue the TBM trial operation;

[0026] If L1≤L<L2 and 0<D≤D1, then continue the TBM trial operation;

[0027] 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;

[0028] Wherein, F1 is the preset amplitude, and D1 is the preset deflection angle.

[0029] Furthermore, the calculation of the tunnel boring machine assembly quality and efficiency score based on 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, and 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, determining the tunnel boring machine assembly quality and efficiency grade according to the tunnel boring machine assembly quality and efficiency score includes:

[0035] 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;

[0036] 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;

[0037] If R2<R zp If ≤R3, the tunnel boring machine assembly quality and efficiency level is judged to be good, and a trial run success message is generated;

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

[0039] 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.

[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 <Rjd0 、R xl <R xl0 、R wd <R wd0 , then a trial run failure message is generated, otherwise a trial run success message is generated; where R jd0 R is the preset accuracy score, xl0 R is the preset efficiency score, 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 configured to measure the assembly position errors and assembly roughness of the cutter head, propulsion system, track, and support system of the tunnel boring machine after assembly is completed; determine the total assembly position error based on the individual assembly position errors; and determine the total assembly roughness based on the individual assembly roughnesses;

[0044] an acquisition module, configured to conduct a trial run of the tunnel boring machine within a preset time, and acquire the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the trial run;

[0045] The second determination module is used to calculate the tunnel boring machine assembly quality efficiency score based on 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 efficiency grade based on the tunnel boring machine assembly quality efficiency score; the tunnel boring machine assembly quality efficiency grade includes excellent, good, fair, and poor.

[0046] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the method when executing 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 when the program is executed by a processor, the method is implemented.

[0048] According to an embodiment of the present invention, by separately measuring the assembly position error and roughness of the cutterhead, propulsion system, track, and support system, the actual assembly status of each component can be fully understood, ensuring that all components of the tunnel boring machine are in optimal condition. The concepts of total assembly position error and total assembly roughness enable the evaluation to go beyond individual components and comprehensively consider the assembly quality of the entire tunnel boring machine, providing a more comprehensive performance assessment. A post-assembly trial run dynamically monitors parameters such as advance, power consumption, amplitude, eccentricity, and deflection angle. This helps verify the correlation between assembly results and actual operational performance, promptly identify potential problems, and thereby improve the efficiency of tunnel boring machine assembly quality and efficiency evaluation. Based on the collected data, quality and efficiency scoring and grading are performed to ensure the objectivity and scientific nature of the evaluation process. After the evaluation, tunnel boring machines with excellent, good, and average assembly quality can be quickly screened, allowing for the prioritization of high-quality equipment during project implementation, reducing failures and downtime and improving overall project efficiency. High-quality assembly quality directly impacts the safety and reliability of tunnel excavation. This solution can effectively reduce safety hazards caused by improper assembly.

[0049] It should be understood that the contents described in the Summary of the Invention section 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 readily 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 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0055] To make the purpose, technical solutions, and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present disclosure.

[0056] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the related objects 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 includes:

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

[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 measurement personnel are familiar with the use of measuring tools and instruments, understand the requirements of the measurement plan, and receive 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 of the key surfaces of the cutterhead and record the relevant data; check the assembly position of each component of the propulsion system (such as the propulsion cylinder, guide rail, etc.), and use measuring tools to measure its deviation from the designed position; perform roughness measurement on the important contact surfaces and moving parts of the propulsion system; use tools such as a laser rangefinder or a ruler 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 measurement on the contact surfaces and key parts of the track; check the assembly position of each component of the support system (such as the support plate, support cylinder, etc.) and measure its deviation from the designed position; perform roughness measurement on the important contact surfaces and load-bearing parts of the support system.

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

[0061] Z pwc =1.4×Zdp ×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 assembly position error of the propulsion system, Z gd is the track assembly position error, Z zh Assembly position error for the support system.

[0063] In some embodiments, the calculation formula for 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 is the axial assembly position error of the cutter disc.

[0066] In some embodiments, the calculation formula for 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 is the cutterhead assembly roughness, C 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 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 , 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 pwc2 The second preset total assembly roughness. According to an embodiment of the present invention, by simultaneously considering assembly position error and assembly roughness and calculating the total error based on different error weights, the assembly quality of the tunnel boring machine can be evaluated more comprehensively and accurately, avoiding the limitations of single-indicator evaluation and improving the scientificity and rationality of the judgment. By setting multiple error levels and making judgments based on different error ranges and roughness combinations, the status of the tunnel boring machine can be more finely divided, facilitating the implementation of targeted maintenance and adjustment measures. Through this systematic error evaluation and level determination, potential problems can be discovered in advance, preventive and predictive maintenance can be performed, serious equipment failures during 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 for decision-making, errors in 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 the roughness of each assembly and the corresponding roughness weight, the total assembly roughness C is calculated pcc ; If 0<Zpwc <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 , 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.

[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<L1, determining that the eccentricity risk level of the tunnel boring machine trial run is a first eccentricity risk level; if L1≤L<L2, determining that the eccentricity risk level of the tunnel boring machine trial run is a second eccentricity risk level; if L≥L2, determining that the eccentricity risk level of the tunnel boring machine trial run is a third eccentricity risk level; at this time, immediately stopping the tunnel boring machine trial run, and determining that the tunnel boring machine assembly quality efficiency level is poor; wherein, L1 is the first preset eccentricity, and L2 is the second preset eccentricity. According to an embodiment of the present invention, by acquiring the eccentricity of a tunnel boring machine during 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 more carefully evaluate the operating risks of the equipment 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 thereby improves the efficiency of the tunnel boring machine assembly quality and efficiency evaluation; by setting clear eccentricity risk levels, it is possible to issue early warnings 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 risk levels and quality and efficiency levels 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 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 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 L1≤L<L2 and 0<F≤F1, continuing the trial run of the tunnel boring machine; if L1≤L<L2 and 0<D≤D1, continuing the trial run of the tunnel boring machine; if L1≤L<L2 and F>F1 and D>D1, immediately stopping the trial run of the tunnel boring machine and determining that the assembly quality efficiency level of the tunnel boring machine is poor; wherein F1 is the preset amplitude and D1 is the preset deflection angle. According to an embodiment of the present invention, by acquiring the amplitude, eccentricity, and deflection angle of a tunnel boring machine (TBM) in real time during a trial run, the equipment's operating status can be comprehensively assessed from multiple dimensions, more comprehensively reflecting the TBM's actual performance and improving the accuracy and scientific nature of the assessment. By setting clear preset conditions, the trial run is allowed to continue when the eccentricity is within a certain range and the amplitude or deflection angle is within their respective preset values. This conditional trial run strategy can further verify the TBM's performance without compromising equipment safety. By simultaneously considering the three parameters of eccentricity, amplitude, and deflection angle, flexible and specific risk assessment criteria are established, reducing the influence of subjective judgment and improving the objectivity and consistency of decision-making. Automated decision-making based on real-time data allows the trial run to be automatically terminated and the equipment's quality and efficiency level to be determined when specific conditions are met, reducing human intervention and improving the efficiency and reliability of decision-making. Quality and efficiency level determination based on specific amplitude, eccentricity, and deflection angle data makes the assessment results more accurate and objective, helping to identify potential problems and deficiencies in the equipment, thereby improving the efficiency of TBM 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 run are obtained in real time; if 0.5≤L<0.8 and 0<F≤0.5m, the tunnel boring machine trial run is continued; if 0.5≤L<0.8 and 0<D≤0.5°, the tunnel boring machine trial run is continued; if 0.5≤L<0.8 and F>0.5m and D>0.5°, the tunnel boring machine trial run is stopped immediately, and the tunnel boring machine assembly quality efficiency level is determined to be poor.

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

[0077] In some embodiments, calculating the tunnel boring machine assembly quality and efficiency score based on 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, and 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 an 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 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 key points, 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 includes: if 0 < R zp ≤R1, the tunnel boring machine 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 tunnel boring machine assembly quality and efficiency level is judged to be good, and a trial run success message is generated; if R3<R zp ≤1, the assembly quality and efficiency level of the tunnel boring machine is determined to be excellent, and a trial run success message is generated; wherein, R1 is the first preset score, R2 is the first preset score, R3 is the first preset score, and R1<R2<R3<1. According to an 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 facilitate decision-making; trial run information (success or failure) is generated according to different score ranges to ensure that the operation results receive systematic feedback. During the operation, if the score does not meet the standard, a failure message is immediately generated to facilitate rapid adjustment and improvement, thereby reducing downtime; for the determination of general levels, not only the total 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 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 efficiency level is judged to be good, and a trial run success message is generated; if 0.7<R zp If ≤1, the assembly quality and efficiency level of the tunnel boring machine 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: If R jd <R jd0 、R xl <R xl0 、R wd <R wd0 , then a trial run failure message is generated, otherwise a trial run success message is generated; where Rjd0 R is the preset accuracy score, xl0 R is the preset efficiency score, wd0 The stability score is preset. According to an embodiment of the present invention, by evaluating the trial run of a tunnel boring machine based on three key dimensions: accuracy, efficiency, and stability, the performance of the equipment can be comprehensively reflected, ensuring the accuracy and reliability of the evaluation results. By monitoring and evaluating the accuracy, efficiency, and stability scores in real time, success or failure information can be generated immediately after the trial run, helping to quickly identify problems, reduce potential downtime and maintenance time, and thereby 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 an embodiment of the present invention, by separately measuring the assembly position error and roughness of the cutterhead, propulsion system, track, and support system, the actual assembly status of each component can be fully understood, ensuring that all components of the tunnel boring machine are in optimal condition. The concepts of total assembly position error and total assembly roughness enable the evaluation to go beyond individual components and comprehensively consider the assembly quality of the entire tunnel boring machine, providing a more comprehensive performance assessment. A post-assembly trial run dynamically monitors parameters such as advance, power consumption, amplitude, eccentricity, and deflection angle. This helps verify the correlation between assembly results and actual operational performance, promptly identify potential problems, and thereby improve the efficiency of tunnel boring machine assembly quality and efficiency evaluation. Based on the collected data, quality and efficiency scoring and grading are performed to ensure the objectivity and scientific nature of the evaluation process. After the evaluation, tunnel boring machines with excellent, good, and average assembly quality can be quickly screened, allowing for the prioritization of high-quality equipment during project implementation, reducing failures and downtime and improving overall project efficiency. High-quality assembly quality directly impacts the safety and reliability of tunnel excavation. This solution can effectively reduce safety hazards caused by improper assembly.

[0087] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed 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 solution disclosed in the present disclosure through an apparatus embodiment.

[0089] 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, the device comprising:

[0090] The first determination module 201 is configured to measure the assembly position errors and assembly roughness of the cutter head, propulsion system, track, and support system of the tunnel boring machine after assembly is completed; determine the total assembly position error based on the individual assembly position errors; and determine the total assembly roughness based on the individual assembly roughnesses;

[0091] an acquisition module 202 for conducting a trial run of the tunnel boring machine within a preset time and acquiring the advance, power consumption, amplitude, eccentricity, and deflection angle during the trial run;

[0092] The second determination module 203 is configured to calculate a tunnel boring machine assembly quality efficiency score based on the overall assembly position error, overall assembly roughness, excavation amount, power consumption, amplitude, eccentricity, and deflection angle; and determine a tunnel boring machine assembly quality efficiency grade based on the tunnel boring machine assembly quality efficiency score; the tunnel boring machine assembly quality efficiency grades include 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 solutions disclosed herein, the acquisition, storage, and application of user personal information involved comply 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 assistants, cellular phones, smartphones, 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 claimed 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 ROM 302 or a computer program loaded from storage unit 308 into RAM 303. RAM 303 can also store various programs and data required for the operation of the electronic device. Computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to bus 304.

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

[0099] The computing unit 301 can be various general-purpose and / or specialized 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 that run machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, 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 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the 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 can be performed. 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 (for example, by means of firmware).

[0100] Various embodiments of the systems and techniques described 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), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system that includes 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 can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0102] In the context of the present disclosure, a readable storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. A readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of readable storage media can 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 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 can 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 having 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 can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication 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 server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0106] It should be understood that the various forms of the above-mentioned processes can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of this disclosure can be achieved. This is not limited herein.

[0107] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this 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 cutterhead, 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; 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; 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 ; According to the excavation volume and the corresponding scoring weight, power consumption and the corresponding scoring weight, trial operation time and the corresponding scoring weight, the efficiency score R is calculated. xl ; According to the amplitude and the corresponding scoring weight, eccentricity and the corresponding scoring weight, deflection angle and the corresponding scoring weight, the stability score R is calculated. wd ; According to the accuracy score and the corresponding score weight, efficiency score and the corresponding score weight, stability score and the corresponding score weight, the tunnel boring machine assembly quality and efficiency score R is calculated. zp ; Determine the tunnel boring machine assembly quality efficiency grade according to the tunnel boring machine assembly quality efficiency score; The quality and efficiency grades of tunnel boring machine assembly include excellent, good, general and poor.

2. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 1, wherein: 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, wherein: The step of performing 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 in real time during the trial run; If 0<L<L1, the eccentricity risk level of the tunnel boring machine trial run is determined to be the first eccentricity risk level; If L1≤L<L2, the eccentricity risk level of the tunnel boring machine trial run is determined to be the second eccentricity risk level; If L ≥ L2, the eccentricity risk level of the TBM trial run is determined to be the third eccentricity risk level; the TBM trial run is immediately stopped, and the TBM assembly quality efficiency level 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, wherein: The method of performing 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 further includes: Real-time acquisition of the tunnel boring machine's amplitude F, eccentricity L, and deflection angle D during the test run; If L1≤L<L2 and 0<F≤F1, then continue the TBM trial operation; If L1≤L<L2 and 0<D≤D1, then continue the TBM trial operation; 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; Wherein, 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, wherein: 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 If ≤R3, the tunnel boring machine assembly quality and efficiency level is judged to be good, and a trial run success message is generated; If R3<R zp If ≤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.

6. The method for evaluating the assembly quality and efficiency of a tunnel boring machine according to claim 5, wherein: 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 trial run failure message is generated, otherwise a trial run success message is generated; where R jd0 R is the preset accuracy score, xl0 R is the preset efficiency score, wd0 Rate the preset stability.

7. 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 of the cutter head, propulsion system, track, and support system of the tunnel boring machine 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, configured to conduct a trial run of the tunnel boring machine within a preset time, and acquire the excavation amount, power consumption, amplitude, eccentricity, and deflection angle during the trial run; The second determination module is used to calculate the accuracy score R according to the total assembly position error and the corresponding scoring weight, the total assembly roughness and the corresponding scoring weight. jd ; According to the excavation volume and the corresponding scoring weight, power consumption and the corresponding scoring weight, trial operation time and the corresponding scoring weight, the efficiency score R is calculated. xl ; According to the amplitude and the corresponding scoring weight, eccentricity and the corresponding scoring weight, deflection angle and the corresponding scoring weight, the stability score R is calculated. wd ; According to the accuracy score and the corresponding score weight, efficiency score and the corresponding score weight, stability score and the corresponding score weight, the tunnel boring machine assembly quality and efficiency score R is calculated. zp ; Determine the tunnel boring machine assembly quality efficiency grade according to the tunnel boring machine assembly quality efficiency score; The quality and efficiency grades of tunnel boring machine assembly include excellent, good, general and poor.

8. 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 to enable the at least one processor to execute the method of any one of claims 1-6.

9. 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 1-6.

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