A method, device and equipment for evaluating the credibility of a digital equipment model

Abstract

The present application relates to a method, device and apparatus for evaluating the credibility of a digital model of equipment. The method comprises: for any one of the multiple output indicators related to the credibility evaluation of the digital model of equipment, under the same working condition, the digital model is simulated multiple times, and the actual installation is tested multiple times to obtain a set of experimental data of the output indicators respectively; the overlap of the two sets of experimental data is calculated, and the credibility distance is designed based on the overlap; the vector of distance values ​​in each dimension is constructed according to the credibility distance corresponding to each working condition; the average value of the distance is calculated according to the vector of the distance values ​​in each dimension, and the initial credibility of the digital model of the equipment is calculated using the average value; the comprehensive distance is calculated according to the initial credibility of the digital model of the equipment under multiple indicators, and the credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance. The credibility evaluation of the digital model of equipment can be realized by adopting this method.

Description

Technical Field

[0001] The present application relates to the field of simulation technology, and in particular to a credibility assessment method, device and apparatus for a digital model of equipment. Background Art

[0002] With the maturity and popular application of computer, information, network and other technologies, people can use digital technology to break through the limitations of time and space, establish digital models of physical objects, and accurately describe the geometry, physics, behavior, rules and other multi-dimensional attributes of physical entities through digital models. The actual behavior and operating status of physical entities can be truly portrayed, and the simulation operation data of physical entities can be output based on established laws and related rules. In this way, the operating status and behavioral characteristic trends of physical entities can be simulated and deduced through the iterative operation of models and data, thereby realizing the prediction, evaluation, and optimization of physical entities.

[0003] The digital model of equipment refers to the digital model of the physical entity of the equipment mapped in the virtual space. It is mainly responsible for describing the spatiotemporal geometric relationship, real-time operating status, behavior and process of the physical equipment, describing the multi-dimensional attributes and operating mechanism of the physical equipment, and characterizing the equipment capabilities and related laws and rules. The digital model of equipment is mainly used to carry out equipment simulation experiments and evaluate and analyze the combat performance and combat effectiveness of the equipment. In order to ensure the rationality and correctness of the construction of the digital model of equipment, it is necessary to evaluate the credibility of the model. As the digital model of equipment becomes more and more complex, credibility assessment faces many new challenges, involving the measurement and evaluation of a large number of qualitative and quantitative indicators, and usually requires the comprehensive use of multiple methods and techniques according to the characteristics of each output characteristic.

[0004] At present, many achievements have been made in theoretical research on the credibility assessment of equipment digital models. However, in practical applications, it is often difficult to comprehensively and objectively assess the credibility of equipment digital models. Based on this, it is necessary to provide a credibility assessment method for equipment digital models based on a combination of actual installation test and simulation experiment data under large sample conditions to address the above technical issues. Summary of the invention

[0005] Based on this, it is necessary to provide a credibility assessment method, device and equipment for a digital equipment model that can realize credibility assessment of the digital equipment model in response to the above technical problems.

[0006] A method for evaluating the credibility of a digital model of equipment, the method comprising:

[0007] Obtain the digital model of the equipment to be evaluated; select multiple output indicators related to the credibility evaluation of the digital model of the equipment; select relevant experimental factors of the working conditions involved in the actual installation test to design the simulation experiment, and obtain multiple simulation experiment samples corresponding to the working conditions;

[0008] For any one of the above-mentioned multiple output indicators, under the same working condition, the digital model is simulated multiple times, and the actual installation is tested multiple times to obtain a set of experimental data of the output indicator respectively;

[0009] Calculate the overlap of the two sets of experimental data, and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of distance values ​​in each dimension, and use the average value to calculate the initial credibility of the equipment digital model;

[0010] The comprehensive distance is calculated according to the initial credibility of the digital model of the equipment under multiple indicators, and the credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance.

[0011] In one embodiment, calculating the overlap between two sets of experimental data includes:

[0012] The overlap between the two sets of experimental data is calculated as

[0013] ;

[0014] in, is the number of simulation runs, is the number of actual installation tests, It is the first equipment digital model simulation experiment i The output value of the relevant indicators of the run, This is the first equipment installation test i The output value of the relevant indicators of the test, is the mean value of the output values ​​of relevant indicators of the equipment digital model simulation experiment, It is the mean output value of relevant indicators in the equipment actual installation test.

[0015] In one embodiment, the credibility distance is designed based on the overlap, including:

[0016] The reliability distance designed based on the coincidence degree is

[0017] ;

[0018] in, Indicates the degree of overlap.

[0019] In one embodiment, a vector of distance values ​​in each dimension is constructed according to the credibility distance corresponding to each working condition, including:

[0020] According to the credibility distance corresponding to each working condition, the vector of distance values ​​in each dimension is constructed as follows: ;

[0021] in, It represents the credibility distance under the first sample, and L is the number of working conditions.

[0022] In one embodiment, the initial credibility of the equipment digital model is calculated by using the average value, including:

[0023] The initial credibility of the equipment digital model is calculated using the average value as 1- ,in, Indicates the average value.

[0024] In one embodiment, the comprehensive distance is calculated based on the initial credibility of the digital model of the equipment under multiple indicators, including:

[0025] The comprehensive distance calculated based on the initial credibility of the equipment digital model under multiple indicators is:

[0026] ;

[0027] in, is the number of indicators, It is The importance weight of each indicator for credibility, It is The credibility distance of the digital model on the indicators.

[0028] In one embodiment, calculating the credibility of the digital model of the equipment to be evaluated by using the comprehensive distance includes:

[0029] The credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance:

[0030] ;

[0031] in, is the comprehensive distance.

[0032] A device for evaluating the credibility of a digital model of equipment, the device comprising:

[0033] The data acquisition module is used to obtain the digital model of the equipment to be evaluated; select multiple output indicators related to the credibility evaluation of the digital model of the equipment; select relevant experimental factors of the working conditions involved in the actual installation test to design simulation experiments, and obtain multiple simulation experiment samples corresponding to the working conditions;

[0034] A simulation operation module is used to perform multiple simulations on the digital model and multiple tests on the actual installation for any one of the above-mentioned multiple output indicators under the same working conditions, so as to obtain a set of experimental data of the output indicators respectively;

[0035] The initial credibility module is used to calculate the overlap of two sets of experimental data and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of distance values ​​in each dimension, and use the average value to calculate the initial credibility of the equipment digital model;

[0036] The credibility evaluation module is used to calculate the comprehensive distance according to the initial credibility of the equipment digital model under multiple indicators, and use the comprehensive distance to calculate the credibility of the equipment digital model to be evaluated.

[0037] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0038] Obtain the digital model of the equipment to be evaluated; select multiple output indicators related to the credibility evaluation of the digital model of the equipment; select relevant experimental factors of the working conditions involved in the actual installation test to design the simulation experiment, and obtain multiple simulation experiment samples corresponding to the working conditions;

[0039] For any one of the above-mentioned multiple output indicators, under the same working condition, the digital model is simulated multiple times, and the actual installation is tested multiple times to obtain a set of experimental data of the output indicator respectively;

[0040] Calculate the overlap of the two sets of experimental data, and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of distance values ​​in each dimension, and use the average value to calculate the initial credibility of the equipment digital model;

[0041] The comprehensive distance is calculated according to the initial credibility of the digital model of the equipment under multiple indicators, and the credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance.

[0042] The above-mentioned method, device and equipment for credibility assessment of a digital model of equipment, in this application, covers the multi-dimensional attributes of the equipment by selecting multiple output indicators related to the credibility assessment of the digital model of equipment, and avoids the one-sidedness of single indicator assessment. At the same time, the simulation experiment design is combined with various working conditions involved in the actual installation test, so that the evaluation can cover various conditions of the equipment in actual use, and comprehensively collect data from multiple dimensions to lay the foundation for high-precision evaluation. Under the same working condition, multiple digital model simulation runs and actual installation tests are carried out for each output indicator to obtain the corresponding two sets of experimental data. This comparative experiment can intuitively show the performance difference between the model and the actual installation under the same conditions, and the analysis is based on the real data of the actual installation test to ensure the reliability of the data source and provide strong data support for the credibility evaluation. From calculating the overlap of the two sets of experimental data to designing the credibility distance, and then constructing the distance value vector of each dimension and calculating the average value to obtain the initial credibility, finally, the comprehensive distance is calculated based on the initial credibility under multiple indicators to determine the final credibility. The whole process adopts a scientific and reasonable quantitative calculation process, comprehensively considers different working conditions and multi-indicator information, effectively integrates various types of data, and avoids the influence of one-sided factors, so as to accurately, comprehensively and objectively measure the credibility of the equipment digital model and realize the credibility evaluation of the high-precision equipment digital model. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic flow chart of a method for evaluating the credibility of a digital model of equipment in one embodiment;

[0044] Figure 2 A structural block diagram of a credibility assessment device for a digital model of equipment in one embodiment;

[0045] Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] In one embodiment, Figure 1 As shown, a method for evaluating the credibility of a digital model of equipment is provided, comprising the following steps:

[0048] Step 102, obtaining a digital model of the equipment to be evaluated; selecting multiple output indicators related to the credibility evaluation of the digital model of the equipment; selecting relevant experimental factors of the working conditions involved in the actual installation test to design a simulation experiment, and obtaining multiple simulation experiment samples corresponding to the working conditions.

[0049] First, obtain the digital model of the equipment to be evaluated, which is the core object of the evaluation. Then select multiple output indicators related to the credibility evaluation of the equipment digital model. These indicators cover the reflection of multi-dimensional attributes of the equipment such as geometry, physics, behavior, rules, etc., such as the equipment's operating speed, accuracy, energy consumption and other indicators. By selecting multiple indicators, the one-sidedness of single indicator evaluation is avoided, and the credibility of the model can be comprehensively measured from different angles. Select the relevant experimental factors of the working conditions involved in the actual installation test for simulation experiment design, and obtain multiple simulation experiment samples corresponding to the working conditions. The actual installation test conditions reflect the various conditions of the equipment in actual use, such as different ambient temperatures, loads, operating time, etc. By designing these working condition-related factors in the simulation experiment, the simulation experiment can be made as close to the actual equipment operation as possible.

[0050] Step 104 , for any one of the above-mentioned multiple output indicators, under the same working condition, the digital model is simulated multiple times, and the actual installation is tested multiple times to obtain a set of experimental data of the output indicator.

[0051] For multiple output indicators, multiple simulation runs are performed on the digital model and multiple tests are performed on the actual installation under the same working conditions to obtain a set of experimental data for the output indicators. This comparative experimental data acquisition under the same working conditions can directly compare the performance differences between the model and the actual installation under the same conditions, providing a rich and targeted data basis for subsequent credibility evaluation.

[0052] Step 106, calculate the overlap of the two sets of experimental data, and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of distance values ​​in each dimension, and use the average value to calculate the initial credibility of the digital model of the equipment.

[0053] The overlap between the two sets of experimental data (simulation experimental data and actual installation test data) is calculated. The overlap directly reflects the closeness between the model output and the actual installation situation. The credibility distance is designed based on the overlap. The overlap is quantified into the credibility distance through reasonable mathematical conversion. This distance value can measure the deviation between the model and the actual installation under specific working conditions and output indicators.

[0054] According to the credibility distance corresponding to each working condition, a vector of distance values ​​in each dimension is constructed. The dimension here can be understood as different working conditions or different output indicator dimensions. The data is integrated in the form of a vector, and then the average value of the distance is calculated. This average value combines the credibility distance information under different working conditions and indicators, preliminarily reflects the overall credibility level of the model, and obtains the initial credibility of the equipment digital model. This multi-dimensional comprehensive calculation of the average value avoids the excessive influence of a single working condition or indicator on the result, making the initial credibility more representative.

[0055] Step 108 , calculating a comprehensive distance according to the initial credibility of the digital model of the equipment under multiple indicators, and using the comprehensive distance to calculate the credibility of the digital model of the equipment to be evaluated.

[0056] The comprehensive distance is calculated based on the initial credibility of the equipment digital model under multiple indicators, and the credibility information under different indicators is further integrated. The credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance. This final credibility evaluation result comprehensively considers all working conditions and multi-indicator information under the actual installation test, and is based on the comparative analysis of the real data of the actual installation test. Therefore, it can more comprehensively and objectively reflect the degree of fit between the equipment digital model and the actual equipment, thereby realizing a high-precision credibility evaluation of the equipment digital model. It overcomes the problem that previous evaluation methods may only focus on some working conditions or indicators, or lack of actual installation data comparison, resulting in inaccurate and incomplete evaluation.

[0057] In the above-mentioned credibility assessment method of a digital model of equipment, the present application covers the multi-dimensional attributes of the equipment by selecting multiple output indicators related to the credibility assessment of the digital model of equipment, thereby avoiding the one-sidedness of single indicator assessment. At the same time, the simulation experiment design is combined with various working conditions involved in the actual installation test, so that the evaluation can cover various conditions of the equipment in actual use, and comprehensively collect data from multiple dimensions to lay the foundation for high-precision evaluation. Under the same working condition, multiple digital model simulation runs and actual installation tests are carried out for each output indicator to obtain the corresponding two sets of experimental data. This comparative experiment can intuitively show the performance difference between the model and the actual installation under the same conditions, and the analysis is based on the real data of the actual installation test to ensure the reliability of the data source and provide strong data support for the credibility evaluation. From calculating the overlap of the two sets of experimental data to designing the credibility distance, and then constructing the distance value vector of each dimension and calculating the average value to obtain the initial credibility, finally, the comprehensive distance is calculated based on the initial credibility under multiple indicators to determine the final credibility. The whole process adopts a scientific and reasonable quantitative calculation process, comprehensively considers different working conditions and multi-indicator information, effectively integrates various types of data, and avoids the influence of one-sided factors, so as to accurately, comprehensively and objectively measure the credibility of the equipment digital model and realize the credibility evaluation of the high-precision equipment digital model.

[0058] In one embodiment, calculating the overlap between two sets of experimental data includes:

[0059] The overlap between the two sets of experimental data is calculated as

[0060] ;

[0061] in, is the number of simulation runs, is the number of actual installation tests, It is the first equipment digital model simulation experiment i The output value of the relevant indicators of the run, This is the first equipment installation test i The output value of the relevant indicators of the test, is the mean value of the output values ​​of relevant indicators of the equipment digital model simulation experiment, It is the mean output value of relevant indicators in the equipment actual installation test.

[0062] In one embodiment, the credibility distance is designed based on the overlap, including:

[0063] The reliability distance designed based on the coincidence degree is

[0064] ;

[0065] in, Indicates the degree of overlap.

[0066] In one embodiment, a vector of distance values ​​in each dimension is constructed according to the credibility distance corresponding to each working condition, including:

[0067] According to the credibility distance corresponding to each working condition, the vector of distance values ​​in each dimension is constructed as follows: ;

[0068] in, It represents the credibility distance under the first sample, and L is the number of working conditions.

[0069] In one embodiment, the initial credibility of the equipment digital model is calculated by using the average value, including:

[0070] The initial credibility of the equipment digital model is calculated using the average value as 1- ,in, Indicates the average value.

[0071] In one embodiment, the comprehensive distance is calculated based on the initial credibility of the digital model of the equipment under multiple indicators, including:

[0072] The comprehensive distance calculated based on the initial credibility of the equipment digital model under multiple indicators is:

[0073] ;

[0074] in, is the number of indicators, It is The importance weight of each indicator for credibility, It is The credibility distance of the digital model on the indicators.

[0075] In one embodiment, calculating the credibility of the digital model of the equipment to be evaluated by using the comprehensive distance includes:

[0076] The credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance:

[0077] ;

[0078] in, is the comprehensive distance.

[0079] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0080] In one embodiment, Figure 2 As shown, a credibility assessment device for a digital model of equipment is provided, comprising:

[0081] The data acquisition module 202 is used to acquire the digital model of the equipment to be evaluated; select multiple output indicators related to the credibility evaluation of the digital model of the equipment; select relevant experimental factors of the working conditions involved in the actual installation test to perform simulation experiment design, and obtain multiple simulation experiment samples corresponding to the working conditions;

[0082] The simulation operation module 204 is used to perform multiple simulation operations on the digital model and multiple tests on the actual installation for any one of the multiple output indicators under the same working conditions, so as to obtain a set of experimental data of the output indicator respectively;

[0083] The initial credibility module 206 is used to calculate the overlap of two sets of experimental data, and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of the distance values ​​in each dimension, and use the average value to calculate the initial credibility of the equipment digital model;

[0084] The credibility evaluation module 208 is used to calculate the comprehensive distance according to the initial credibility of the digital model of the equipment under multiple indicators, and use the comprehensive distance to calculate the credibility of the digital model of the equipment to be evaluated.

[0085] For the specific definition of a credibility assessment device for a digital model of equipment, please refer to the definition of a credibility assessment method for a digital model of equipment mentioned above, which will not be repeated here. Each module in the above-mentioned credibility assessment device for a digital model of equipment can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0086] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for evaluating the credibility of a digital model of equipment is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a key, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0087] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0088] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0089] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for evaluating the credibility of a digital equipment model, characterized in that: The method comprises: Acquire a digital model of the equipment to be evaluated; select multiple output indicators related to the credibility evaluation of the digital model of the equipment; select relevant experimental factors of the working conditions involved in the actual installation test to design a simulation experiment, and obtain multiple simulation experiment samples corresponding to the working conditions; For any one of the above-mentioned multiple output indicators, under the same working condition, the digital model is simulated multiple times, and the actual installation is tested multiple times to obtain a set of experimental data of the output indicator respectively; Calculate the overlap of two sets of experimental data, and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of the distance values ​​in each dimension, and use the average value to calculate the initial credibility of the digital model of the equipment; Calculating a comprehensive distance according to the initial credibility of the digital model of the equipment under multiple indicators, and calculating the credibility of the digital model of the equipment to be evaluated using the comprehensive distance; Calculate the overlap between two sets of experimental data, including: The overlap between the two sets of experimental data is calculated as in, is the number of simulation runs, is the number of actual installation tests, It is the first equipment digital model simulation experiment The output value of the relevant indicators of the run, This is the first equipment installation test The output value of the relevant indicators of the test, is the mean value of the output values ​​of relevant indicators of the equipment digital model simulation experiment, It is the mean value of the output values ​​of relevant indicators in the equipment installation test; The comprehensive distance is calculated based on the initial credibility of the equipment digital model under multiple indicators, including: The comprehensive distance calculated based on the initial credibility of the equipment digital model under multiple indicators is: in, is the number of indicators, It is The importance weight of each indicator for credibility, It is The credibility distance of the digital model on each indicator; Calculating the credibility of the digital model of the equipment to be evaluated by using the comprehensive distance includes: The credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance: in, is the comprehensive distance.

2. The method according to claim 1, characterized in that A credibility distance is designed based on the overlap, including: The designed credibility distance based on the overlap is: in, Indicates the degree of overlap.

3. The method according to claim 2, characterized in that According to the credibility distance corresponding to each working condition, a vector of distance values ​​in each dimension is constructed, including: According to the credibility distance corresponding to each working condition, the vector of distance values ​​in each dimension is constructed as follows: in, It represents the credibility distance under the first sample, and L is the number of working conditions.

4. The method according to claim 1, characterized in that: The initial credibility of the equipment digital model is calculated using the average value, including: The initial credibility of the equipment digital model is calculated using the average value: ,in, Indicates the average value.

5. A credibility assessment device for a digital model of equipment, characterized in that: The device comprises: A data acquisition module is used to acquire a digital model of the equipment to be evaluated; select multiple output indicators related to the credibility evaluation of the digital model of the equipment; select relevant experimental factors of the working conditions involved in the actual installation test to design a simulation experiment, and obtain multiple simulation experiment samples corresponding to the working conditions; A simulation operation module is used to perform multiple simulations on the digital model and multiple tests on the actual installation for any one of the above-mentioned multiple output indicators under the same working conditions, so as to obtain a set of experimental data of the output indicators respectively; The initial credibility module is used to calculate the overlap of two sets of experimental data, and design the credibility distance based on the overlap; construct the vector of distance values ​​in each dimension according to the credibility distance corresponding to each working condition; calculate the average value of the distance according to the vector of the distance values ​​in each dimension, and use the average value to calculate the initial credibility of the equipment digital model; calculate the overlap of two sets of experimental data, including: The overlap between the two sets of experimental data is calculated as in, is the number of simulation runs, is the number of actual installation tests, It is the first equipment digital model simulation experiment i The output value of the relevant indicators of the run, This is the first equipment installation test i The output value of the relevant indicators of the test, is the mean value of the output values ​​of relevant indicators of the equipment digital model simulation experiment, It is the mean value of the output values ​​of relevant indicators in the equipment installation test; The credibility evaluation module is used to calculate the comprehensive distance according to the initial credibility of the digital model of the equipment under multiple indicators, and calculate the credibility of the digital model of the equipment to be evaluated by using the comprehensive distance; the comprehensive distance is calculated according to the initial credibility of the digital model of the equipment under multiple indicators, including: The comprehensive distance calculated based on the initial credibility of the equipment digital model under multiple indicators is: in, is the number of indicators, It is The importance weight of each indicator for credibility, It is The credibility distance of the digital model on each indicator; Calculating the credibility of the digital model of the equipment to be evaluated by using the comprehensive distance includes: The credibility of the digital model of the equipment to be evaluated is calculated using the comprehensive distance: in, is the comprehensive distance.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

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