A method for evaluating the assembly quality of shield tunneling equipment based on digital twin

Abstract

The present invention discloses a method for evaluating the assembly quality of shield tunneling equipment based on digital twins, comprising the following steps: collecting and analyzing real-time data of the assembly site during the assembly process of the shield tunneling equipment to find out the key points of its assembly difficulties; using three-dimensional drawing software and simulation software to build a virtual assembly model for the shield tunneling equipment, and simulating the assembly production line of the shield tunneling equipment in real time; through a data mapping feedback mechanism and a unified standardized communication protocol, the data of the physical space and the virtual space are mutually integrated and fed back, and combined with historical operation and maintenance data to form a twin database; the assembly quality index of the shield tunneling equipment is identified to determine its evaluation index and evaluation grade, and the generalized comparison table method of the hesitant fuzzy set is used to calculate the assembly process score according to the membership function to determine the assembly grade, thereby establishing a shield tunneling machine assembly quality evaluation model.

Description

Technical Field

[0001] The present invention belongs to the technical field of shield tunneling equipment engineering, and relates to a shield tunneling machine assembly quality evaluation method based on digital twin. The proposed digital twin model can monitor, evaluate, predict, and optimize the mapping of physical assembly entities through virtual models, and can solve the problem that data information and physical information are difficult to integrate in the manufacturing process. The comprehensive hesitant fuzzy decision matrix fully considers the degree of hesitation of expert scoring, which is more in line with people's way of thinking and reduces the loss of decision-making information. Background Art

[0002] Shield tunneling has the advantages of high construction efficiency and little impact on the ground. In recent years, it has become the main method of tunnel construction in urban subway construction and important projects. Research on the assembly quality evaluation method of shield tunneling equipment can effectively improve the efficiency of shield assembly and find out the key assembly difficulties, which is of great engineering significance. In order to meet and achieve the goals of safe production, high quality, high efficiency, and rapid response, digital twin technology has developed rapidly in the field of complex equipment manufacturing. The digital twin model can monitor, evaluate, predict, and optimize the mapping of physical entities through virtual models, and can solve the problem of the difficulty in integrating data information and physical information in the manufacturing process.

[0003] Assembly quality evaluation is the key to ensure the assembly quality of complex equipment. When using decision-making methods such as hierarchical analysis method for evaluation, expert scoring is a key link. Due to the complexity and variability of assembly quality, even experienced experts are hesitant when making decisions. Hesitant fuzzy is suitable for multi-attribute decision-making problems. The concept of non-membership is introduced to allow abstention when experts make judgments. That is, the membership hesitant fuzzy set and non-membership hesitant fuzzy set of the assembly process that meets a certain attribute are given at the same time, and a comprehensive hesitant fuzzy matrix is ​​obtained, which fully considers the hesitation degree of expert scoring, is more in line with people's way of thinking, and reduces the loss of decision-making information. Summary of the invention

[0004] The purpose of the present invention is to provide a method for evaluating the assembly quality of shield tunneling equipment based on digital twins to solve the problems arising from the above-mentioned background technology. In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme; a method for evaluating the assembly quality of shield tunneling equipment based on digital twins. The technical scheme of the present invention is as follows, which is characterized by comprising the following steps:

[0005] Step (1): Physical space raw data collection: Through the shield tunneling equipment assembly equipment status monitoring system, collect and analyze the data of each component during its assembly process, combine hardware collection and software collection to obtain assembly information, and use MySQL database software to classify, store and transmit the data;

[0006] Step (2): Construction of a digital twin virtual assembly model of shield tunneling equipment: Use drawing software to draw two-dimensional and three-dimensional diagrams of the components of the shield tunneling equipment and import them into the Plant Simulation software. In the Plant Simulation software, the material transportation equipment, storage warehouse, assembly environment, etc. of the assembly process are reasonably arranged. Through repeated correction of the model, the shield tunneling equipment assembly production line is simulated in real time to achieve virtual assembly feedback on the on-site assembly process.

[0007] Step (3): Creation of twin data: Based on the on-site assembly system data and the real-time feedback data from the simulation software platform, the data of the physical space and the virtual space are integrated, fed back and mapped through a unified standardized communication protocol, combined with historical operation and maintenance data, and stored in a MySQL database to form a twin database;

[0008] Step (4): Establish an assembly quality evaluation system: Use twin data to identify the quality indicators of shield tunneling equipment and determine the assembly quality evaluation indicators and evaluation levels of shield tunneling equipment;

[0009] Step (5): Construct a shield tunneling equipment assembly quality evaluation model based on twin data: obtain a comprehensive hesitant fuzzy decision matrix through expert evaluation, use the generalized comparison table method of hesitant fuzzy sets to calculate the scores of each component assembly process to determine the assembly level, and establish a shield tunneling machine assembly quality evaluation model.

[0010] The hardware acquisition configuration at the shield tunneling equipment assembly and processing site in the step (1) includes using current sensors, displacement sensors, pressure sensors, and surface quality measuring instruments to collect real-time data such as the assembly environment, displacement and error at different positions, assembly surface quality, and assembly dimensions during the assembly process, thereby providing a data source and data reliability for the digital twin high-fidelity model; the virtual space configuration refers to the configuration of the three-dimensional modeling software, data simulation software, algorithm optimization software, and the interface protocol between the software, obtaining simulation optimization data of the algorithm software, simulation software, and CAD software, and realizing data storage configuration using the data interface, local area network, and database software.

[0011] The shield tunneling equipment assembly process based on Plant Simulation in step (2) is divided into three steps: model drawing, assembly work preparation and assembly execution:

[0012] (1) Model drawing: Use UG or other 3D drawing software to draw 3D drawings of the various components of the shield tunneling equipment, such as the shield cutter head, main bearing, gear, etc., and convert them into formats that can be recognized by the simulation software: *.stp, *.prt, *.x_t, and import them into Plant Simulation to prepare for the assembly stage.

[0013] (2) Assembly work preparation: Analyze the assembly requirements of shield tunneling equipment and determine the general layout of the production assembly system as a U-shaped assembly line, effectively combining shield parts handling equipment, process operation equipment, and various components to meet different assembly requirements.

[0014] (3) Assembly execution: According to the assembly line layout, set up three-dimensional models of the assembly workshop, shield tunneling equipment components, logistics and transportation equipment, and storage warehouses, simulate the assembly process of different component assembly stations, set initial conditions, and establish information interaction between the visualization platform and the on-site construction system.

[0015] The digital twin data in step (3) includes physical entities, virtual simulation models, and historical operation and maintenance data, wherein the physical space data mainly includes shield tunneling equipment assembly component errors, process equipment information, assembly environment, etc.; the virtual space data mainly includes geometric data, simulation model data, rule model data, etc.; the historical operation and maintenance data mainly includes: all assembly fault locations and their causes, and the one-time assembly success rate of each component. Through a unified standardized communication protocol, twin data for assembly quality evaluation is constructed and stored in a Mysql database, thereby constructing a twin database for shield tunneling equipment assembly quality evaluation;

[0016] The expression of the digital twin model of shield tunneling equipment oriented to assembly quality is as follows:

[0017] Ge = {Am, En, Gm, Ma}

[0018] Gm={Cm,Km,Lm}

[0019] Ma={Qa,Ta,Fa,Pa,Va}

[0020] Among them: Ge is the digital twin model of shield tunneling equipment, Am is the physical model, En is the assembly feature, Gm is the model geometry information, and Ma is other assembly related information;

[0021] Cm is the size information, Km is the accuracy information, and Lm is the feature information;

[0022] Qa is assembly tool information, Ta is process information, Fa is quality information, Pa is environment information, and Va is personnel information.

[0023] In the step (4), an assembly quality evaluation model is established: the evaluation results of the assembly quality are evaluated using an evaluation set V = {V1, V2, V3, V4}, that is, the assembly quality is divided into four levels, V1 is excellent, V2 is good, V3 is fair, and V4 is poor; the shield tunneling equipment assembly quality evaluation index and the assembly quality score comparison table are determined, as shown in Table 1 and Table 2 below:

[0024] Table 1 Shield tunneling equipment assembly quality evaluation index system

[0025]

[0026] Table 2 Score comparison table

[0027]

[0028] The score range corresponding to the assembly level (ω i ,ω j ), 1≤i,j≤4 can be adjusted according to actual working conditions.

[0029] In step (5), let X = {x1, x2, ..., x m} is the set of assembly processes to be evaluated, U = {u1,u2,…,u m} is a set of assembly quality evaluation indicators. At the same time, membership hesitant fuzzy sets and non-membership hesitant fuzzy sets that meet certain attributes are given to obtain a comprehensive hesitant fuzzy decision matrix to reduce the loss of decision information. The generalized comparison table method of hesitant fuzzy sets is used to calculate the score of the assembly process, thereby obtaining the quality of the assembly process. The specific evaluation steps used are shown below.

[0030] (1) The comprehensive hesitant fuzzy matrix R is obtained through expert evaluation. Each row of R represents an assembly process, and the number of rows is equal to the number of columns.

[0031] (2) Calculate the membership and non-membership degrees according to formula (1) and (2)

[0032]

[0033]

[0034] Where h1 and h2 represent two hesitant fuzzy elements, θ max = max{θ(h1),θ(h2)}, θ(h1),θ(h2) represent the median number of h1 and h2 respectively, 1≤i, j≤n, 0≤C ij ≤n,C ii =0.5n.

[0035] (3) Calculate the membership set C of all assembly processes ij , get the generalized comparison table of membership, and use the characteristic function to compare C ij Finally, the row sum and column sum of the generalized comparison table, as well as the difference Q between the row sum and the column sum, are calculated. i (X1), the characteristic function is: Where x,y≥0,x≥y.

[0036] (4) Calculate C of all non-membership sets ij , get the generalized comparison table of non-membership degree, calculate the difference Q between the row sum and column sum in the generalized comparison table i (X2).

[0037] (5) Use the membership function to calculate the final score Q(R). The membership function is:

[0038]

[0039] Among them, Q i (X1) and Q i (X2) represents the membership score and non-membership score of the i-th assembly process respectively, λ1 is the correlation coefficient of the membership score, λ2 is the correlation coefficient of the non-membership score, -1<λ1<1, -1<λ2<1.

[0040] (6) The score Q(R) of each assembly process is compared with the shield tunneling equipment score comparison table, and the assembly quality level of each assembly process is given based on expert experience.

[0041] The beneficial effects of the present invention are:

[0042] 1. Digital twin technology can monitor, evaluate, predict, and optimize the mapping of physical entities through virtual models, realize digital self-perception and precise synchronization of physical and digital spaces, and integrate and feedback the data of physical and virtual spaces through unified standardized communication protocols to build a twin database and provide data support for the assembly quality evaluation system.

[0043] 2. The hesitant fuzzy method is applicable to multi-attribute decision-making problems. At the same time, the membership hesitant fuzzy set and non-membership hesitant fuzzy set of the assembly process that conforms to a certain attribute are given, and a comprehensive hesitant fuzzy matrix is ​​obtained, which fully considers the hesitation degree of expert scoring, is more in line with people's way of thinking, and reduces the loss of decision-making information. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 Flowchart of the shield tunneling equipment assembly quality evaluation method based on digital twin;

[0045] Figure 2 Data collection configuration diagram;

[0046] Figure 3 Flowchart of virtual assembly simulation model of shield tunneling equipment;

[0047] Figure 4 U-shaped assembly line for shield tunneling equipment;

[0048] Figure 5 Creation of a twin database for shield tunneling equipment;

[0049] Figure 6 Flowchart of the shield tunneling equipment assembly quality evaluation method. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0051] The present invention will be described in detail below in conjunction with the accompanying drawings. Figures 1 to 3 As shown, a shield tunneling equipment assembly quality evaluation method based on digital twin is characterized by comprising the following steps:

[0052] Step (1): Physical space raw data collection: Through the shield tunneling equipment assembly equipment status monitoring system, collect and analyze the data of each component during its assembly process, combine hardware collection and software collection to obtain assembly information, and use MySQL database software to classify, store and transmit the data;

[0053] Step (2): Construction of a digital twin virtual assembly model of shield tunneling equipment: In the Plant Simulation software, the material transportation equipment, storage warehouse, and assembly environment of the assembly process are rationally arranged. By repeatedly correcting the model, the shield tunneling equipment assembly production line is simulated in real time to achieve virtual assembly feedback on the on-site assembly process.

[0054] Step (3): Creation of twin data: Based on the on-site assembly system data and the real-time feedback data from the simulation software platform, the data of the physical space and the virtual space are integrated, fed back and mapped through a unified standardized communication protocol, combined with historical operation and maintenance data, and stored in a MySQL database to form a twin database;

[0055] Step (4): Establish an assembly quality evaluation system: Use twin data to identify the quality indicators of shield tunneling equipment and determine the assembly quality evaluation indicators and evaluation levels of shield tunneling equipment;

[0056] Step (5): Construct a shield tunneling equipment assembly quality evaluation model based on twin data: obtain a comprehensive hesitant fuzzy decision matrix through expert evaluation, use the generalized comparison table method of hesitant fuzzy sets to calculate the scores of each component assembly process to determine the assembly level, and establish a shield tunneling machine assembly quality evaluation model.

[0057] The hardware collection configuration of the shield tunneling equipment assembly and processing site in step (1) is as follows: Figure 2As shown, current sensors, displacement sensors, pressure sensors, and surface quality measuring instruments are used to collect real-time data such as assembly environment, displacement and error at different positions, assembly surface quality, and assembly dimensions during the assembly process, providing a data source and data reliability for the digital twin high-fidelity model; virtual space configuration refers to the configuration of three-dimensional modeling software, data simulation software, algorithm optimization software, and interface protocols between software, obtaining simulation optimization data of algorithm software, simulation software, and CAD software, and using data interfaces, local area networks, and database software to implement data storage configuration.

[0058] The shield tunneling equipment assembly process based on Plant Simulation in step (2) is divided into three steps: model drawing, assembly work preparation and assembly execution. Figure 3 As shown:

[0059] (1) Model drawing: Use UG or other 3D drawing software to draw 3D drawings of the various components of the shield tunneling equipment, such as the shield cutter head, main bearing, gear, etc., and convert them into formats that can be recognized by the simulation software: *.stp, *.prt, *.x_t, and import them into Plant Simulation to prepare for the assembly stage.

[0060] (2) Assembly work preparation: Analyze the assembly requirements of shield tunneling equipment and determine that the general layout of the production assembly system is a U-shaped assembly line, such as Figure 4 As shown, shield parts handling equipment, process operation equipment, and various components are effectively combined together to meet different assembly requirements.

[0061] (3) Assembly execution: According to the assembly line layout, set up three-dimensional models of the assembly workshop, shield tunneling equipment components, logistics and transportation equipment, and storage warehouses, simulate the assembly process of different component assembly stations, set initial conditions, and establish information interaction between the visualization platform and the on-site construction system.

[0062] The digital twin data in step (3) includes physical entities, virtual simulation models and historical operation and maintenance data, wherein the physical space data mainly includes assembly component errors of shield tunneling equipment, process equipment information, assembly environment, etc.; the virtual space data mainly includes geometric data, simulation model data, rule model data, etc.; the historical operation and maintenance data mainly includes: all assembly fault locations and their causes, and the one-time assembly success rate of each component. Through a unified standardized communication protocol, twin data for assembly quality evaluation is constructed and stored in a Mysql database, and a twin database for shield tunneling equipment assembly quality evaluation is constructed, such as Figure 5 As shown;

[0063] The expression of the digital twin model of shield tunneling equipment oriented to assembly quality is as follows:

[0064] Ge = {Am, En, Gm, Ma}

[0065] Gm={Cm,Km,Lm}

[0066] Ma={Qa,Ta,Fa,Pa,Va}

[0067] Among them: Ge is the digital twin model of shield tunneling equipment, Am is the physical model, En is the assembly feature, Gm is the model geometry information, and Ma is other assembly related information;

[0068] Cm is the size information, Km is the accuracy information, and Lm is the feature information;

[0069] Qa is assembly tool information, Ta is process information, Fa is quality information, Pa is environment information, and Va is personnel information.

[0070] In the step (4), an assembly quality evaluation model is established: the evaluation results of the assembly quality are evaluated using an evaluation set V = {V1, V2, V3, V4}, that is, the assembly quality is divided into four levels, V1 is excellent, V2 is good, V3 is fair, and V4 is poor; the shield tunneling equipment assembly quality evaluation index and the assembly quality score comparison table are determined, as shown in Table 1 and Table 2 below:

[0071] Table 1 Shield tunneling equipment assembly quality evaluation index system

[0072]

[0073] Table 2 Score comparison table

[0074]

[0075] The score range corresponding to the assembly level (ω i ,ω j ), 1≤i,j≤4 can be adjusted according to the actual working conditions. In step (5), let X={x1,x2,…,x m} is the set of assembly processes to be evaluated, U = {u1,u2,…,u m} is the set of assembly quality evaluation indicators, and the membership hesitant fuzzy set and non-membership hesitant fuzzy set that meet certain attributes are given at the same time, and the comprehensive hesitant fuzzy decision matrix is ​​obtained to reduce the loss of decision information. The generalized comparison table method of hesitant fuzzy sets is used to calculate the score of the assembly process, so as to obtain the quality of the assembly process, such as Figure 6 The specific evaluation steps adopted are shown below.

[0076] (1) The comprehensive hesitant fuzzy matrix R is obtained through expert evaluation. Each row of R represents an assembly process, and the number of rows is equal to the number of columns.

[0077] (2) Calculate the membership and non-membership degrees according to formula (1) and (2)

[0078]

[0079]

[0080] Where h1 and h2 represent two hesitant fuzzy elements, θ max = max{θ(h1),θ(h2)}, θ(h1),θ(h2) represent the median number of h1 and h2 respectively, 1≤i, j≤n, 0≤C ij ≤n,C ii =0.5n.

[0081] (3) Calculate the membership set C of all assembly processes ij , get the generalized comparison table of membership, and use the characteristic function to compare C ij Finally, the row sum and column sum of the generalized comparison table, as well as the difference Q between the row sum and the column sum, are calculated. i (X1), the characteristic function is: Where x,y≥0,x≥y.

[0082] (4) Calculate C of all non-membership sets ij , get the generalized comparison table of non-membership degree, calculate the difference Q between the row sum and column sum in the generalized comparison table i (X2).

[0083] (5) Use the membership function to calculate the final score Q(R). The membership function is:

[0084]

[0085] Among them, Q i (X1) and Q i (X2) represents the membership score and non-membership score of the i-th assembly process respectively, λ1 is the correlation coefficient of the membership score, λ2 is the correlation coefficient of the non-membership score, -1<λ1<1, -1<λ2<1.

[0086] (6) The score Q(R) of each assembly process is compared with the shield tunneling equipment score comparison table, and the assembly quality level of each assembly process is given based on expert experience.

[0087] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above-mentioned implementation mode. Technical personnel familiar with the field can also make various equivalent deformations or substitutions without violating the spirit of the present invention. These equivalent deformations or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A shield tunneling equipment assembly quality evaluation method based on digital twin, characterized by The following steps are involved: Step (1): Physical space raw data collection: Through the shield tunneling equipment assembly equipment status monitoring system, collect and analyze the data of each component during its assembly process, combine hardware collection and software collection to obtain assembly information, and use MySQL database software to classify, store and transmit the data; Step (2): Construction of a digital twin virtual assembly model of shield tunneling equipment: Use drawing software to draw two-dimensional and three-dimensional diagrams of the components of the shield tunneling equipment and import them into the PlantSimulation software. In the PlantSimulation software, the material transportation equipment, storage warehouse, assembly environment, etc. of the assembly process are reasonably laid out. By repeatedly correcting the model, the shield tunneling equipment assembly production line is simulated in real time to achieve virtual assembly feedback on the on-site assembly process. Step (3): Creation of twin data: Based on the on-site assembly system data and the real-time feedback data from the simulation software platform, the data of the physical space and the virtual space are integrated, fed back and mapped through a unified standardized communication protocol, combined with historical operation and maintenance data, and stored in a MySQL database to form a twin database; Step (4): Establish an assembly quality evaluation system: Use twin data to identify the assembly quality indicators of shield tunneling equipment and determine the assembly quality evaluation indicators and evaluation levels of shield tunneling equipment; Step (5): Construct a shield tunneling equipment assembly quality evaluation model based on twin data: obtain a comprehensive hesitant fuzzy decision matrix through expert evaluation, use the generalized comparison table method of hesitant fuzzy sets to calculate the scores of each component assembly process to determine the assembly level, and establish a shield tunneling machine assembly quality evaluation model.

2. A shield tunneling equipment assembly quality evaluation method based on digital twin as claimed in claim 1, characterized in that: The hardware acquisition configuration at the shield tunneling equipment assembly and processing site in the step (1) includes: using current sensors, displacement sensors, pressure sensors, and surface quality measuring instruments to collect real-time data such as assembly environment, displacement and error at different positions, assembly surface quality, and assembly dimensions during the assembly process, providing a data source and data reliability for the digital twin high-fidelity model; virtual space configuration refers to the configuration of three-dimensional modeling software, data simulation software, algorithm optimization software, and interface protocols between software, obtaining simulation optimization data of algorithm software, simulation software, and CAD software, and using data interfaces, local area networks, and database software to implement data storage configuration.

3. A shield tunneling equipment assembly quality evaluation method based on digital twin as claimed in claim 1, characterized in that: The shield tunneling equipment assembly process based on PlantSimulation in step (2) is divided into three steps: model drawing, assembly work preparation and assembly execution: (1) Model drawing: Use UG or other 3D drawing software to draw 3D drawings of the various components of the shield tunneling equipment, such as the shield cutter head, main bearing, gear, etc., and convert them into formats that can be recognized by the simulation software: *.stp, *.prt, *.x_t, and import them into PlantSimulation to prepare for the assembly stage; (2) Assembly work preparation: Analyze the assembly requirements of shield tunneling equipment and determine the general layout of the production assembly system as a U-shaped assembly line, effectively combining shield parts handling equipment, process operation equipment, and various components to meet different assembly requirements; (3) Assembly execution: According to the assembly line layout, set up three-dimensional models of the assembly workshop, shield tunneling equipment components, logistics and transportation equipment, and storage warehouses, simulate the assembly process of different component assembly stations, set initial conditions, and establish information interaction between the visualization platform and the on-site construction system.

4. A shield tunneling equipment assembly quality evaluation method based on digital twin as claimed in claim 1, characterized in that: The digital twin data in step (3) includes physical entities, virtual simulation models and historical operation and maintenance data, wherein the physical space data mainly includes shield tunneling equipment assembly component errors, process equipment information, and assembly environment; the virtual space data mainly includes geometric data, simulation model data, and rule model data; the historical operation and maintenance data mainly includes: all assembly fault locations and their causes, and the one-time assembly success rate of each component. Through a unified standardized communication protocol, twin data for assembly quality evaluation is constructed and stored in a Mysql database, and a twin database for shield tunneling equipment assembly quality evaluation is constructed; The expression of the shield tunneling equipment digital twin model for assembly quality is as follows: Ge = {Am, En, Gm, Ma} Gm={Cm,Km,Lm} Ma={Qa,Ta,Fa,Pa,Va} Among them: Ge is the digital twin model of shield tunneling equipment, Am is the physical model, En is the assembly feature, Gm is the model geometry information, and Ma is other assembly related information; Cm is the size information, Km is the accuracy information, and Lm is the feature information; Qa is assembly tool information, Ta is process information, Fa is quality information, Pa is environment information, and Va is personnel information.

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