Data processing method and device, equipment and storage medium

Abstract

The invention relates to a data processing method and device, equipment and a storage medium, and the method comprises the steps: obtaining a to-be-analyzed item for mechanical structure performance analysis in an industrial product, and determining at least one to-be-analyzed working condition corresponding to the to-be-analyzed item from a preset corresponding relation between analysis items and working conditions; for each to-be-analyzed working condition, determining a corresponding post-processing demand parameter from a corresponding relationship between a preset working condition and the post-processing demand parameter, and determining corresponding post-processing demand data and a post-processing evaluation criterion based on the corresponding post-processing demand parameter; for each to-be-analyzed working condition, based on a corresponding post-processing evaluation criterion, evaluating the corresponding post-processing demand data to obtain a corresponding evaluation result; and based on the evaluation results corresponding to different to-be-analyzed working conditions in the at least one to-be-analyzed working condition, generating a performance evaluation report of the mechanical structure corresponding to the to-be-analyzed item. According to the method, the data is automatically extracted through the preset post-processing demand parameters, so that the efficiency and the quality of data processing are ensured.

Description

Technical Field

[0001] The present application relates to the field of finite element simulation technology, and in particular to a data processing method, device, equipment and storage medium. Background Art

[0002] With the continuous development of computer-aided engineering (CAE) simulation technology based on the finite element method and the continuous improvement of computer hardware performance, CAE simulation is becoming increasingly widely used in modern industrial product design. The finite element simulation analysis process generally consists of three stages: pre-processing, solution calculation, and post-processing. Post-processing involves analyzing and organizing simulation results with the help of finite element post-processing software to obtain structural performance indicators and generate simulation analysis reports. Currently, mainstream finite element post-processing software only provides basic functions such as simple result viewing and screenshots. In actual engineering, analysis engineers need to manually complete the finite element post-processing process in post-processing software based on analysis requirements. This includes importing result files, reviewing finite element calculation results for each region and component of the structure according to analysis requirements, judging whether the results meet the requirements according to evaluation criteria, and compiling the results into a simulation analysis report. Due to the cumbersome operation process, this manual post-processing method inevitably leads to a large amount of repetitive work for complex structures with many parts or when there are a large number of result files. This process is relatively inefficient and prone to errors, resulting in low accuracy and efficiency of analysis conclusions. Summary of the Invention

[0003] The present application provides a data processing method, apparatus, device and storage medium.

[0004] In a first aspect, the present application provides a data processing method, the method comprising:

[0005] Obtaining an item to be analyzed for mechanical structure performance analysis in an industrial product, and determining at least one working condition to be analyzed corresponding to the item to be analyzed from a preset correspondence between the analysis item and the working condition;

[0006] For each working condition to be analyzed, the corresponding post-processing requirement parameters are determined from the corresponding relationship between the preset working conditions and the post-processing requirement parameters, and based on the corresponding post-processing requirement parameters, the corresponding post-processing requirement data and post-processing evaluation criteria are determined;

[0007] For each working condition to be analyzed, based on the corresponding post-processing evaluation criteria, the corresponding post-processing demand data is evaluated to obtain the corresponding evaluation results;

[0008] Based on the evaluation results corresponding to different working conditions to be analyzed in at least one working condition to be analyzed, a performance evaluation report of the mechanical structure corresponding to the item to be analyzed is generated.

[0009] According to the above-mentioned technical means, the present application pre-sets the correspondence between the analysis items and the working conditions, and the correspondence between the working conditions and the post-processing requirement parameters, and then directly determines the post-processing requirement parameters after knowing the items to be analyzed, thereby determining the data processing requirement data based on the post-processing requirement parameters, so as to realize the judgment of whether the mechanical structure corresponding to the item to be analyzed is qualified based on the requirement data, and can automatically extract data, thereby ensuring the efficiency and quality of data processing.

[0010] Furthermore, the post-processing requirement parameters include result file matching information, load steps, and result requirement parameters corresponding to each working condition to be analyzed; for each working condition to be analyzed, the corresponding post-processing requirement data is determined based on the corresponding post-processing requirement parameters; for each working condition to be analyzed, the corresponding result file is determined from the finite element simulation result files of multiple mechanical structures based on the corresponding result file matching parameters; for each working condition to be analyzed, the corresponding load result data is determined from the corresponding result file based on the corresponding load step; for each working condition to be analyzed, the corresponding post-processing requirement data is determined from the corresponding load result data based on the corresponding result requirement parameters.

[0011] According to the above-mentioned technical means, the present application can directly obtain the corresponding result file from multiple result files generated by finite element simulation analysis through the result file matching information included in the post-processing requirement parameters, and then determine the load result data in the corresponding result file based on the load step, and finally determine the corresponding post-processing requirement data based on the result requirement parameters. It can be seen that each process is pre-set and can directly realize the automated post-processing process based on the pre-set parameters.

[0012] Furthermore, the result requirement parameters include at least one result grouping parameter, and each result grouping parameter includes a result reading range, a part grouping method, and a result reading parameter; for each working condition to be analyzed, based on the corresponding result requirement parameter, the corresponding post-processing requirement data is determined from the corresponding load result data, including: for each result grouping parameter, based on the corresponding result reading range, the corresponding reading part is determined from the model part database of the simulation of the corresponding working condition to be analyzed, and based on the corresponding part grouping method, the corresponding reading parts are grouped to obtain at least one corresponding part group; for the parts included in each part group, based on the corresponding result reading parameter, the corresponding part result data is determined from the corresponding load result data; the part result data of different parts in at least one part group is determined as the group result data of the corresponding result grouping parameter, and the group result data corresponding to different grouping parameters in at least one result grouping parameter is determined as the post-processing requirement data of the corresponding working condition to be analyzed.

[0013] According to the above technical means, this application sets corresponding result grouping parameters for different result groups, namely, result requirement parameters. Based on this, it is possible to read the part result data of each part in the model of the working condition simulation to be analyzed, and realize the extraction of post-processing requirement data.

[0014] Furthermore, the result reading parameters include result type and characteristic result; for the parts included in each part group, based on the corresponding result reading parameters, the corresponding part result data is determined from the corresponding load result data, including: for the parts included in each part group, based on the corresponding result type and load step, the corresponding part result cloud map is output; for the parts included in each part group, based on the corresponding characteristic result, the corresponding part result data is determined from the corresponding part result cloud map.

[0015] According to the above technical means, this application determines the corresponding part result data by outputting the part result cloud map. At this time, the cloud map can also be directly output, and the screenshot can be output after adjusting the view, which can improve the automation of data processing.

[0016] Furthermore, the post-processing requirement parameters include at least one result grouping parameter corresponding to each working condition to be analyzed, and each result grouping parameter corresponds to an evaluation parameter; the evaluation parameters include target value type, target value, target value coefficient, and evaluation method; for each working condition to be analyzed, based on the corresponding post-processing requirement parameters, the corresponding post-processing evaluation criteria are determined, including: for each result grouping parameter, according to the corresponding target value type, target value and target value coefficient, the corresponding actual target value is determined; for each result grouping parameter, the corresponding actual target value and evaluation method are determined as the corresponding post-processing evaluation criteria.

[0017] According to the above technical means, this application also sets evaluation parameters for each result grouping parameter. In this way, after obtaining the part result data, the qualification of the part is evaluated based on the evaluation criteria corresponding to the group to which the part belongs, thereby realizing the automated evaluation process.

[0018] Furthermore, for each result grouping parameter, the corresponding actual target value is determined according to the corresponding target value type, target value and target value coefficient, including: for each result grouping parameter, if the corresponding target value type is a material parameter, based on the corresponding target value type, the corresponding target value is determined from the preset material database; for each result grouping parameter, the product of the corresponding target value and the target value coefficient is determined as the corresponding actual target value.

[0019] According to the above technical means, this application sets up a preset material database so that the target value of the required parameter can be obtained based on the evaluation parameters in the post-processing requirement parameters, and then the actual comparison is determined as the target value, realizing an automated evaluation process, making the data processing more complete.

[0020] Furthermore, the post-processing requirement data includes part result data of each part in the mechanical structure to be analyzed corresponding to the item to be analyzed when simulating each working condition to be analyzed, and the post-processing evaluation criteria include an evaluation method and an actual target value set for the result group to which each part belongs; for each working condition to be analyzed, the corresponding post-processing requirement data is evaluated based on the corresponding post-processing evaluation criteria to obtain a corresponding evaluation result, including: for each working condition to be analyzed, determining the evaluation method and the actual target value set for the result group corresponding to each part in the mechanical structure to be analyzed; for each part, comparing the corresponding part result data with the actual target value according to the corresponding evaluation method to obtain the corresponding part evaluation result; for each working condition to be analyzed, the part evaluation results of different parts in the mechanical structure to be analyzed are determined as the corresponding evaluation results.

[0021] According to the above technical means, the present application can judge whether the part result data corresponding to each part is qualified, obtain the evaluation results corresponding to the working conditions to be analyzed, realize automated evaluation results, and improve the automation of data processing.

[0022] In a second aspect, the present application provides a data processing device, the data processing device comprising:

[0023] An acquisition module is used to acquire an item to be analyzed for mechanical structure performance analysis in an industrial product, and determine at least one working condition to be analyzed corresponding to the item to be analyzed from a preset correspondence between the analysis item and the working condition;

[0024] A determination module is used to determine, for each working condition to be analyzed, corresponding post-processing requirement parameters from the corresponding relationship between the preset working conditions and the post-processing requirement parameters, and to determine corresponding post-processing requirement data and post-processing evaluation criteria based on the corresponding post-processing requirement parameters;

[0025] The evaluation module is used to evaluate the corresponding post-processing demand data for each working condition to be analyzed based on the corresponding post-processing evaluation criteria and obtain the corresponding evaluation results;

[0026] The generating module is used to generate a performance evaluation report of the mechanical structure corresponding to the item to be analyzed based on the evaluation results corresponding to different working conditions to be analyzed in at least one working condition to be analyzed.

[0027] In a third aspect, the present application provides a data processing device, which includes: a processor, a memory, and a communication bus; the processor implements the above-mentioned data processing method when executing a running program stored in the memory.

[0028] In a fourth aspect, the present application provides a computer-readable storage medium, characterized in that a computer program is stored thereon, and the computer program implements the above-mentioned data processing method when executed by a processor.

[0029] Beneficial effects of this application:

[0030] (1) This application pre-sets the correspondence between analysis items and working conditions, and the correspondence between working conditions and post-processing requirement parameters, and then directly determines the post-processing requirement parameters after knowing the items to be analyzed, thereby determining the data processing requirement data based on the post-processing requirement parameters, so as to judge whether the mechanical structure corresponding to the item to be analyzed is qualified based on the requirement data, and can automatically extract data, thereby ensuring the efficiency and quality of data processing.

[0031] (2) This application can directly obtain the corresponding result file from multiple result files generated by finite element simulation analysis through the result file matching information included in the post-processing requirement parameters, and then determine the load result data in the corresponding result file based on the load step. Finally, based on the result requirement parameters, the corresponding post-processing requirement data is determined. It can be seen that each process is pre-set and can directly realize the automated post-processing process based on the pre-set parameters.

[0032] (3) In this application, evaluation parameters are also set for each result grouping parameter. In this way, after obtaining the part result data, the qualification of the part is evaluated based on the evaluation criteria corresponding to the group to which the part belongs, thereby realizing an automated evaluation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flowchart of a data processing method provided in an embodiment of the present application;

[0034] Figure 2 A schematic diagram of an exemplary process for generating an analysis report provided in an embodiment of the present application;

[0035] Figure 3 A schematic diagram of an exemplary process for determining post-processing requirement data provided in an embodiment of the present application Figure 1 ;

[0036] Figure 4 A schematic diagram of an exemplary process of reading grouping results provided in an embodiment of the present application;

[0037] Figure 5 A schematic diagram of an exemplary process for determining post-processing requirement data provided in an embodiment of the present application Figure 2 ;

[0038] Figure 6A schematic diagram of an exemplary process for reading part results provided in an embodiment of the present application;

[0039] Figure 7 A schematic diagram of an exemplary process for determining part result data provided in an embodiment of the present application;

[0040] Figure 8 A schematic diagram of an exemplary process for determining post-processing evaluation criteria provided in an embodiment of the present application;

[0041] Figure 9 A schematic diagram of an exemplary process for determining an actual target value provided in an embodiment of the present application;

[0042] Figure 10 A schematic diagram of an exemplary process for determining the evaluation result provided in the embodiment of the present application Figure 1 ;

[0043] Figure 11 A schematic diagram of an exemplary process for determining the evaluation result provided in the embodiment of the present application Figure 2 ;

[0044] Figure 12 A flowchart of an exemplary data processing method provided in an embodiment of the present application;

[0045] Figure 13 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application;

[0046] Figure 14 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The following will describe the embodiments of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand the other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for the purpose of illustrating the present application and are not intended to limit the scope of protection of the present application.

[0048] In the structural design process of mechanical products, the use of finite element simulation to analyze the mechanical properties and verify the safety of the mechanical structure is an important means to ensure and improve the performance of the mechanical structure. By replacing physical prototype testing with finite element simulation, designers can quickly obtain the mechanical response of the mechanical structure, thereby quickly judging whether the structure meets the design requirements. On this basis, thanks to the low cost and short cycle of finite element simulation, designers can quickly verify multiple schemes during the structural optimization design process and obtain design schemes with better performance through multi-scheme screening. Therefore, compared with traditional physical prototype testing, structural design and verification through finite element simulation can not only save development costs and improve development efficiency, but also greatly improve the various performance indicators of the product structure.

[0049] The finite element simulation analysis process generally includes three stages: pre-processing, solution calculation and post-processing. Among them, post-processing is the process of analyzing and organizing the simulation analysis results with the help of finite element post-processing software to obtain the performance indicators of the structure and form a simulation analysis report. At present, mainstream finite element post-processing software only provides basic functions such as simple result viewing and screenshots. In actual engineering, analysis engineers need to complete the finite element post-processing process through manual operations in the post-processing software according to analysis requirements. The large number of repetitive manual operations in the finite element simulation post-processing process makes the product development cycle longer from the perspective of the efficiency and quality of finite element analysis post-processing.

[0050] Furthermore, the specific requirements, processes, and complexity of finite element analysis post-processing can vary significantly for different analysis items. To accommodate these differences in post-processing, the traditional approach is to develop customized post-processing programs for each analysis item for automated post-processing. This approach not only requires extensive program development, but also requires independent use and maintenance for each analysis item. Changes in the post-processing requirements for an analysis item, or the need for additional analysis items, require program modifications or the development of new programs, making fully automated post-processing difficult. Therefore, there is an urgent need to develop new methods that adapt to the finite element post-processing requirements of diverse scenarios, enabling intelligent post-processing for simulation analysis and addressing the high maintenance costs of traditional automated post-processing programs. For example, in finite element simulation analysis of automotive structures under certain load conditions, the structure must exhibit no residual deformation or maintain residual deformation within a certain range. In such cases, analysis engineers only need to examine the displacement of the entire structure after loading and unloading during post-processing to determine whether the structure meets strength requirements. When simulating and analyzing other working conditions, it is required that the structure does not crack under load. In this case, different materials have different criteria for determining cracking. For example, brittle materials such as cast aluminum alloys and cast iron are generally judged by the maximum principal stress of the structure, while materials such as steel plates and aluminum profiles are generally judged by the equivalent plastic strain or MISES stress (von Mises stress). In addition, even for the same type of material, different grades of materials can have significant differences in performance parameters such as tensile strength and elongation at break, resulting in different parameters for determining cracking. In this case, during post-processing, it is necessary to group the parts of the structure according to different materials and extract results based on these material groups. As can be seen from the above examples, the specific processes of finite element analysis post-processing vary greatly depending on the analysis requirements, which brings great difficulties to the automated post-processing of finite element analysis. The traditional approach is to develop a customized post-processing program for each analysis item to achieve automated post-processing, which makes finite element analysis post-processing inefficient and prone to errors.

[0051] In view of the above technical problems, the present application provides a data processing method implemented by a data processing device. Figure 1 A flow chart of a data processing method provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the process includes the following steps S101 to S104:

[0052] Step S101: obtaining an item to be analyzed for mechanical structure performance analysis in an industrial product, and determining at least one working condition to be analyzed corresponding to the item to be analyzed from a preset correspondence between analysis items and working conditions.

[0053] In the embodiments of the present application, the data processing device is a device with data processing functions, which can be a tablet computer, a laptop computer, a handheld computer, a personal digital assistant (PDA), a desktop computer, etc. The exemplary data processing device is not limited here.

[0054] In an embodiment of the present application, the industrial product may be a mobile phone, an automobile, or other product including a mechanical structure, and the items to be analyzed are analysis items for the mechanical structure performance of the industrial product; for example, when the industrial product is an automobile, the analysis items may be the whole vehicle decoupling strength analysis, subframe strength analysis, etc.

[0055] In an embodiment of the present application, the data processing device is pre-set with a correspondence between analysis items and working conditions. When the analysis items are known, at least one working condition to be analyzed corresponding to the analysis item can be determined based on the correspondence between the analysis items and the working conditions. For example, if the analysis item is a vehicle uncoupling strength analysis, the corresponding at least one working condition to be analyzed can include a straight-pull working condition and a diagonal-pull working condition. The vehicle uncoupling strength analysis examines whether the vehicle structure will crack or produce deformation that affects normal use under the straight-pull load and diagonal-pull load defined in the vehicle tow hook strength test standard; if the analysis item is a subframe strength analysis, the corresponding at least one working condition to be analyzed can include two working conditions, L1 working condition and L2 working condition. L1 is a typical working condition, requiring that the subframe does not undergo visible permanent deformation after the L1 working condition load; L2 working condition is an extreme working condition, requiring that the subframe does not crack or produce deformation that affects the vehicle's driving under the L2 working condition load.

[0056] For example, the correspondence between the preset analysis items and the working conditions can be presented in the form of a table, as shown in Table 1:

[0057] Table 1

[0058]

[0059]

[0060] As shown in Table 1, the analysis item names are: For the vehicle decoupling strength analysis, the analysis item number is DUR200001; for the subframe strength analysis, the number can be DUR200001, or any other number. In practice, simply entering the analysis item name and number will result in at least one corresponding operating condition to be analyzed. Each analysis item contains post-processing information for multiple operating conditions, distinguished by the operating condition name. Therefore, it can be applied to the post-processing of both single- and multi-condition analysis items. For a single-condition analysis item, only the post-processing information for one operating condition needs to be listed, making it suitable for post-processing of both single- and multi-condition analysis items.

[0061] Table 1 exemplifies the characteristics of the data structure in the analysis item post-processing requirements database. The actual content and values do not constitute an undue limitation on this application. Other strings in Table 1, such as "regular matching," "group by part," "ungrouped," "maximum principal stress," "equivalent plastic strain," "displacement," "maximum value," "material parameter," "value," "tensile strength," and "elongation at break," are used to illustrate the purpose of the data item and do not constitute an undue limitation on this application.

[0062] Step S102: For each working condition to be analyzed, determine the corresponding post-processing requirement parameters from the corresponding relationship between the preset working conditions and the post-processing requirement parameters, and determine the corresponding post-processing requirement data and post-processing evaluation criteria based on the corresponding post-processing requirement parameters.

[0063] In an embodiment of the present application, corresponding post-processing requirement parameters are set for each working condition to be analyzed. For example, as shown in Table 1, all columns following the working condition name in the table are post-processing requirement parameters. The data processing device can determine the post-processing requirement data based on the result file matching method, matching parameters, load step, result group name, result reading range, part grouping method, result type, and feature results, and determine the post-processing evaluation criteria based on the target value type, target value, target value coefficient, and evaluation method.

[0064] In the embodiments of the present application, the setting of the post-processing requirement parameters can be set based on actual needs and application scenarios, which is not limited in the present application.

[0065] Thus, referring to the form shown in Table 1, the integrated management of the demand information of the analysis items (post-processing demand parameters) by a digital method refers to reorganizing the post-processing demand information of the analysis items according to a unified standard structure, and using a database to manage the post-processing demand information of each analysis item, forming an analysis item post-processing demand database (the correspondence between the preset analysis items and the working conditions and the correspondence between the preset working conditions and the post-processing demand parameters, see Table 1), so that the post-processing requirements of different analysis items can be automatically obtained in the automated post-processing process, and complete automated post-processing can be achieved. Integrating and managing the post-processing requirements of the analysis items in a machine-recognizable manner is the basis for achieving complete automated post-processing. In this way, the automated post-processing method for finite element simulation analysis provided in this application is executed according to a unified process and steps for different working conditions and analysis requirements, and the post-processing parameters are also reorganized according to a unified standard structure and uniformly managed through a database to achieve machine recognition. Therefore, the process of implementing the automated post-processing method can be conveniently implemented through the development of a program, which is convenient for use and promotion.

[0066] Step S103: For each working condition to be analyzed, based on the corresponding post-processing evaluation criteria, the corresponding post-processing requirement data is evaluated to obtain a corresponding evaluation result.

[0067] In the embodiments of the present application, for each working condition to be analyzed, the corresponding post-processing requirement data is evaluated based on the corresponding post-processing evaluation criteria to obtain the corresponding evaluation results. For example, for the strength analysis of the vehicle tow hook, the maximum principal stress of parts made of brittle materials such as cast aluminum must be less than or equal to the tensile strength of the material, and the equivalent plastic strain of parts made of plastic materials such as steel plates must be less than or equal to half of the material's fracture elongation. For the strength analysis of the subframe, the maximum residual displacement of the structure after loading in the L1 working condition must be less than 0.1mm, and in the L2 working condition, the maximum principal stress of parts made of brittle materials such as cast aluminum must be less than or equal to the tensile strength of the material, and the equivalent plastic strain of parts made of plastic materials such as steel plates must be less than or equal to half of the material's fracture elongation.

[0068] In the embodiments of the present application, the evaluation results include whether each part of various materials meets the evaluation criteria. Of course, the evaluation results may also include: if not, what is the deviation; if satisfied, what is the specific part result data, and other information. The information set in the evaluation results can be set according to actual needs and application scenarios, and this application does not limit this.

[0069] Step S104: generating a performance evaluation report of the mechanical structure corresponding to the item to be analyzed based on the evaluation results corresponding to different working conditions to be analyzed in the at least one working condition to be analyzed.

[0070] For example, if the item to be analyzed is a subframe strength analysis, and at least one of the operating conditions to be analyzed is an L1 operating condition and an L2 operating condition, an evaluation result for each component of the subframe under the L1 operating condition is obtained; an evaluation result for each component of the subframe under the L2 operating condition is obtained. Then, based on the evaluation results for each component of the subframe under different operating conditions, a subframe performance evaluation report corresponding to the subframe strength analysis is generated.

[0071] In this way, the present application pre-sets the correspondence between the analysis items and the working conditions, and the correspondence between the working conditions and the post-processing requirement parameters, and then directly determines the post-processing requirement parameters after knowing the items to be analyzed, thereby determining the data processing requirement data based on the post-processing requirement parameters, so as to realize the judgment of whether the mechanical structure corresponding to the item to be analyzed is qualified based on the requirement data, and can automatically extract data, thereby ensuring the efficiency and quality of data processing.

[0072] For example, Figure 2 As shown, a flowchart of an exemplary data processing method is provided, including the following steps S201 to S207:

[0073] Step S201: Obtain input parameters.

[0074] Here, the data processing device obtains the analysis item number, the file name of the finite element model file created during the analysis, and the file name of the result file generated by the finite element calculation from the program input parameters. In the embodiments of the present application, the analysis item type can be distinguished by the analysis item number. For analysis items of multiple working conditions, the result files may be multiple files.

[0075] Step S202: Read the finite element model file.

[0076] Here, the data processing device can read the file pointed to by the input finite element model file name through the program, parse the file and extract the names, material grades, and other information of each component of the structure (the components included in the mechanical structure corresponding to the analysis item), as well as the collection defined in the model from the file, and store them in variables.

[0077] Step S203: Obtain analysis item post-processing data.

[0078] Here, the data processing device obtains the post-processing requirement information (post-processing requirement parameters) of the analysis item according to the analysis item number through the analysis item post-processing requirement database (preset correspondence: preset analysis item and working condition correspondence and preset working condition and post-processing requirement parameters).

[0079] Step S204: Obtain a list of analysis item working conditions.

[0080] Here, the data processing device obtains the operating condition list of the analysis item (a tabular form of post-processing requirement parameters) according to the post-processing requirement information of the analysis item by the program. For example, if the input analysis item number is "DUR200002", the obtained operating condition list will be the information shown in Table 2.

[0081] Table 1

[0082]

[0083] Step S205: Read the working condition results.

[0084] Here, the data processing device reads the operating condition results based on the operating condition list to obtain post-processing results (post-processing requirement data) of all operating conditions.

[0085] Step S206: Generate an analysis report.

[0086] Here, the data processing equipment writes the read analysis results (analysis results of post-processing requirement data) and evaluation results (evaluation results of post-processing requirement data determined according to post-processing evaluation criteria) into a file according to given rules to generate a simulation analysis report (performance evaluation report).

[0087] S207, save analysis results

[0088] Here, the data processing equipment saves the post-processing results (analysis results and evaluation results) of all working conditions and the generated reports (performance evaluation reports) into the result database.

[0089] In this way, the present application provides a unified standardized post-processing process to obtain and identify the post-processing requirements of the analysis items through the above steps S201 to S207, and complete the process of result reading, result evaluation, report generation and result storage.

[0090] In some embodiments, the post-processing requirement parameters include the result file matching information, load step, and result requirement parameters corresponding to each working condition to be analyzed. When the data processing device executes the above step S102 of "determining the corresponding post-processing requirement data for each working condition to be analyzed based on the corresponding post-processing requirement parameters", as follows: Figure 3 As shown, the following steps S301 to S303 are included:

[0091] Step S301: for each working condition to be analyzed, based on the corresponding result file matching parameters, determine the corresponding result file from multiple finite element simulation result files.

[0092] In an embodiment of the present application, the result file matching parameter is used to determine the result file corresponding to the working condition when the analysis item has multiple result file inputs. For example, the result file matching parameter can be specified by specifying the naming rules of the result file of the working condition through regular expressions.

[0093] In an embodiment of the present application, multiple finite element simulation result files can also be a result file corresponding to each working condition in at least one working condition corresponding to the item to be analyzed that is currently being processed (analyzing one analysis item). Of course, it can also be a result file of multiple working conditions corresponding to multiple mechanical structures corresponding to multiple analysis items (analyzing multiple analysis items at the same time). It can be set based on actual needs and application scenarios, and this application does not limit this.

[0094] For example, for the first analysis item (whole vehicle uncoupling strength analysis), in order to identify the result files of the two working conditions during the automated processing, the naming rule of the file name of the straight-pull working condition result file is that the file name should contain the string "straight_pull", and the naming rule of the file name of the diagonal-pull working condition result file is that the file name should contain the string "diagonally_pull".

[0095] For example, for the second analysis item (subframe strength analysis), the naming rule of the file name of the L1 working condition result file is that the file name should contain the string "L1", and the naming rule of the file name of the L2 working condition result file is that the file name should contain the string "L2".

[0096] Exemplarily, the result file matching information in Table 1 is a combination of the result file matching method and the matching parameters. This allows for more matching methods to be used, making it more flexible to use. The result file matching method in the table is "regular matching", so the "matching parameters" column gives regular expressions for file naming rules, namely, the character strings ".+straight_pull.*", ".+diagonally_pull.*", ".+L1.*" and ".+L2.*", which can be used to check whether the result file name contains the character strings "straight_pull", "diagonally_pull", "L1" and "L2", respectively, which is consistent with the standardized regulations.

[0097] In this way, the corresponding result file can be determined based on the result file matching parameters.

[0098] Step S302: For each working condition to be analyzed, based on the corresponding load step, determine the corresponding load result data from the corresponding result file.

[0099] In an embodiment of the present application, a load step is a load step that specifies the result of the working condition in the result file in the case of multi-load step loading.

[0100] In the embodiments of the present application, for each working condition to be analyzed, the corresponding load step can be obtained from Table 1. For example, for the first analysis item, the straight-pull and diagonal-pull working conditions, both of which have only one load step, the result to be read is the result of the first load step. For the second analysis item, the L1 working condition, which requires loading and then unloading, specifies that the first load step of the L1 working condition is loading, and the second load step is unloading. The result to be read is the result of the second load step. The L2 working condition only requires one load step, and the result to be read is the result of the first load step.

[0101] In an embodiment of the present application, the post-processing information of each working condition includes result file matching information and load steps, which are used to determine the file and load step where the working condition results are located when there are multiple result files input and multiple load steps loaded.

[0102] In an embodiment of the present application, the data processing device can directly locate the data involved in the corresponding load step in the result file to avoid data extraction errors.

[0103] Step S303: For each working condition to be analyzed, based on the corresponding result requirement parameters, determine the corresponding post-processing requirement data from the corresponding load result data.

[0104] In an embodiment of the present application, when the data processing device obtains load result data, the post-processing requirement data can be directly extracted based on the result requirement parameters. By gradually narrowing the scope, the efficiency and accuracy of data extraction are improved.

[0105] In this way, the present application provides a method and system for automated post-processing of finite element simulation analysis, which can automatically obtain the required key results (post-processing requirement data) from the result file generated by the finite element simulation analysis according to the post-processing requirements (post-processing requirement parameters) of the analysis items, replacing the manual post-processing process and improving the efficiency and quality of finite element analysis.

[0106] like Figure 4 As shown, an exemplary flow chart of reading working condition result data (post-processing requirement data) is provided, including the following steps S401 to S406:

[0107] Step S401: Acquire operating condition data.

[0108] Here, the data processing device acquires the operating condition data.

[0109] Step S402: Matching result file.

[0110] Here, the data processing device obtains the result file matching information of the working condition from the post-processing information of the working condition, and matches the result file of the working condition from the input finite element analysis result file according to the result file matching information.

[0111] For example, for the L2 working condition in Table 2, the result file matching method is "regular matching", and the matching parameter is the regular expression '.+L2.*'. Therefore, in the program implementation, the search function of the re function package in Python is used to verify the expression '.+L2.*' with the file name of each input result file, and the file containing the 'L2' string in the file name is used as the result file of the L2 working condition. If there are multiple file names containing the 'L2' string or none, it indicates that the input parameters are incorrect, and the program reports an error and exits.

[0112] Step S403: Load the result file.

[0113] Here, the data processing device loads the operating condition result file obtained in step S402 into the post-processing software by calling the secondary development code or application programming interface of the post-processing software. For example, the data processing device operates HyperView software using the secondary development code in the Tool Command Language (Tcl) scripting language to load the result file into the HyperView software.

[0114] Step S404: Obtain a result group list.

[0115] Here, the data processing device obtains a result group list of the working condition from the working condition post-processing information. For example, for the L2 working condition in Table 2, the result group list obtained will be the information shown in Table 3. Among them, the result group named "Stress Results" needs to read the maximum principal stress of all parts with the material type of "cast"; the result group named "Strain Results" needs to read the equivalent plastic strain results of all parts with the material type of "sheet".

[0116] Table 2

[0117]

[0118] S405: Read the grouping result.

[0119] Here, the data processing device inputs the result grouping list into the grouping result processing module to read the grouping results and obtain the results of all groups.

[0120] Step S406: Check whether all working conditions have been processed.

[0121] Here, in order to adapt to the post-processing requirements of different analysis items, for multi-condition analysis items, the data processing equipment can read the results of each condition through a loop, so it is applicable to the result reading of single-condition analysis items and multi-condition analysis items, that is, the post-processing information (post-processing requirement parameters) of a condition is obtained from the condition list in turn. If all conditions are completed, the processing is terminated. If not completed, the post-processing results of the condition are read according to steps S402 to S405 until all conditions are read.

[0122] In some embodiments, the result requirement parameter includes at least one result grouping parameter, each result grouping parameter includes a result reading range, a part grouping method, and a result reading parameter; when the data processing device executes the above step S303, Figure 5 As shown, the following steps S501 to S503 may be performed:

[0123] Step S501: for each result grouping parameter, based on the corresponding result reading range, determine the corresponding read parts from the model parts database of the corresponding working condition simulation to be analyzed, and group the corresponding read parts based on the corresponding part grouping method to obtain at least one corresponding part group.

[0124] In an embodiment of the present application, as shown in Tables 1 to 3, the result requirement parameters include at least one result grouping parameter, each result grouping parameter includes a result reading range, a part grouping method, and a result reading parameter (result type and feature result).

[0125] In an embodiment of the present application, each result grouping parameter corresponds to a result grouping, and at least one result grouping is set to facilitate dividing the structure into several parts through result grouping. Different types of results can be read for each part according to actual needs, or the results can be read for each part in different ways to suit the post-processing requirements of different analysis items.

[0126] In the above step S405, the result data of the parts in the mechanical structure are set to be read in groups to meet the result reading requirements of different analysis items. For example, when the analysis item requires reading stress results for part of the parts of the structure and strain results for another part of the parts, this can be achieved by setting two different result groups.

[0127] For example, the data processing equipment can distinguish by the result group name, so that multiple results can be read for the same working condition. For example, in the straight pull working condition of the whole vehicle tow hook strength analysis, the stress results can be read for some parts while the strain results can be read for other parts.

[0128] In the embodiments of the present application, the result reading range must at least include specifying a list of parts (part groups) for which results need to be read by specifying a collection name in a finite element model, specifying the parts for which results need to be read by specifying a material type, or specifying the entire structure as the range for which results need to be read, to meet the common needs of the post-processing process. In this way, by reading results in groups, different results can be read for different areas or different result reading methods can be used to meet different analysis needs.

[0129] In an embodiment of the present application, taking the result group named "strain results" in Table 3 as an example, the result reading range is "mat=sheet", which means that the parts for which the results need to be read in this result group are all parts whose material type is "sheet". The data processing device utilizes a program to first obtain the material of each part through the read finite element model information (model part database), and then obtains the type of material through the material parameter database (preset material database). All corresponding parts whose material type is "sheet" are regarded as parts for which the results need to be read. The result reading range is "mat=cast", which means that the parts for which the results need to be read in this result group are all parts whose material type is "cast". The data processing device utilizes a program to first obtain the material of each part through the read finite element model information (model part database), and then obtains the type of material through the material parameter database (preset material database). All corresponding parts whose material type is "cast" are regarded as parts for which the results need to be read. The result reading range is "all", which means that all parts of the entire structure are regarded as the range for which the results need to be read. In some common application scenarios, a part collection is created within a finite element analysis model to specify the parts list for which results need to be read. In this case, the range of results to be read can be specified by specifying a collection name within the finite element model. For example, the result reading range can be set based on actual needs and application scenarios, and this application does not impose any restrictions on this.

[0130] The material parameter database (preset material database) is used to manage simulation performance parameters of commonly used materials, including but not limited to material grade, material type, elastic modulus, yield strength, tensile strength, elongation at break, and other information that may be required during post-processing. For example, the material parameters in the material parameter database can be displayed in the table format shown in Table 4.

[0131] Table 3

[0132] name Material Type Elastic modulus / MPa Yield strength / MPa Tensile strength / MPa Elongation at break / % A380 cast 70639 160 330 3.5 AL6082-T6 sheet 70000 252 294 10 B280-440DP sheet 203000 305 445 34.1 QSTE420TM sheet 203000 450 533.89 35.21

[0133] In Table 4, the material grade, i.e., the material name (Name), indicates the material type (Type), the elastic modulus (E) of the material, the yield strength (Yield) of the material, the tensile strength (Tensile) of the material, and the elongation at break (Elongation) of the material.

[0134] For example, according to the analysis and usage requirements of an embodiment of the present invention, there are two types of materials in Table 4: one is brittle materials such as cast aluminum, represented by "cast", and the other is ductile materials such as steel plates and aluminum profiles, represented by "sheet". During the use of the method, classification and representation should be performed based on the actual analysis and usage requirements. The classification method and classification representation method in this embodiment do not constitute an undue limitation on this application.

[0135] In an embodiment of the present application, after acquiring read parts, the data processing device groups the read parts based on a part grouping method to obtain at least one part group. Each result grouping parameter corresponds to at least one part group. The part grouping method indicates how to group the parts within the result reading range, and reads the results separately for each group. The grouping method must include at least grouping by material, grouping by component, or no grouping to meet the common needs of the post-processing process.

[0136] For example, the L1 working condition of the subframe strength analysis only needs to read the residual displacement of the entire structure after unloading, so the grouping method is set to "No grouping". In other cases, it is necessary to read the results of each part to guide the design. Set the grouping method to "Group by part" to read the results of each part.

[0137] For example, in Table 3, where the results are grouped as "Strain Results," the grouping method is "Group by Part." Therefore, each part (reading part) for which results need to be read is grouped separately. The finite element model information determines the material grade corresponding to the part, which serves as the material grade for the group. If the part grouping method is "No Grouping," there is only one part group (part group), and the group's parts list contains all parts for which results need to be read, with the material grade blank.

[0138] For example, if the grouping method is grouping by material, the material grades of all parts that need to read the results are determined according to the model parts database to obtain a material list, and the list of parts contained in each material is determined according to the finite element model information (model parts database), and the parts contained in each material are divided into a group, and the material grade of the group is the corresponding material grade.

[0139] Step S502: For each part group, read parameters based on corresponding results, and determine corresponding part result data from corresponding load result data.

[0140] In the embodiments of the present application, for each part for which results need to be read, the corresponding part result data is determined from the corresponding load result data based on the corresponding result reading parameters. For example, as shown in Table 3, for the stress result group, the result reading parameter is to read the maximum value of the maximum principal stress. Therefore, the maximum value of the maximum principal stress read is the corresponding part result data; for the strain result group, the result reading parameter is to read the maximum value of the equivalent plastic strain. Therefore, the maximum value of the equivalent plastic strain read is the corresponding part result data.

[0141] In the embodiment of the present application, in addition to reading the results in groups, more detailed simulation results can be obtained by also reading the results in groups of parts. The free combination of the two levels of grouping makes it more flexible to use and has a wider range of applications.

[0142] Step S503: determining the part result data of different parts in at least one part group as grouped result data corresponding to the result grouping parameter, and determining the grouped result data corresponding to different grouping parameters in at least one result grouping parameter as post-processing requirement data corresponding to the working condition to be analyzed.

[0143] In an embodiment of the present application, for each result grouping parameter, the part result data of different parts in each part group in its corresponding at least one part group is determined as the corresponding grouping result data, that is, the first result grouping corresponds to 3 part groups, part group 1 has part 10, part group 2 has part 20, and part group 3 has part 30. Then, in step S502, the part result data of part 10 of part group 1, the part result data of part 20 of part group 2, and the part result data of part 30 of part group 3 are the grouping result data corresponding to the first result grouping (result grouping parameter).

[0144] In an embodiment of the present application, the working condition to be analyzed includes at least one result grouping parameter, and thus corresponds to at least one grouping result data.

[0145] In this way, the acquired identical data are divided into a group, and the result reading parameters are set in units of the group, thereby avoiding the redundancy of setting information.

[0146] like Figure 6 As shown, a schematic diagram of an exemplary process of reading part result data is provided, including the following steps S601 to S606:

[0147] Step S601: Acquire group information.

[0148] Here, the data processing device sequentially obtains information of one group from the result group list (Table 3).

[0149] Step S602: Determine the result reading range.

[0150] Here, the data processing device obtains the result reading range from the result grouping information and determines the parts for which results need to be read based on the result reading range. If the result reading range is the entire mechanical structure, all parts in the mechanical structure are considered as the parts for which results need to be read. If the result reading range is a specified material type, parts of the specified material type are obtained using the finite element model information obtained in step S202 as the parts for which results need to be read. If the result reading range is a specified set of parts, the finite element model information obtained in step S202 is used to search for the corresponding set in the model, and the parts in the set are considered as the parts for which results need to be read.

[0151] Step S603: Obtain the parts grouping method.

[0152] Here, the data processing device obtains the parts grouping method from the result grouping information.

[0153] Step S604: forming a parts grouping list.

[0154] Here, the data processing device further groups the parts for which reading results are required according to the part grouping method to form a part group list (at least one part group and result reading parameters). For an exemplary example, refer to the discussion of step S501 above.

[0155] Step S605: Read the part results.

[0156] Here, the data processing device reads the results based on the parts grouping list to obtain the simulation analysis results (part result data) for each part grouping.

[0157] Step S606: Check whether all result groupings are completed.

[0158] Here, if it is not completed directly, the post-processing result of the group is read according to step S602 to step S605 until all groups are read.

[0159] In this way, the part result data of each part in different result groups under each working condition can be obtained.

[0160] In some embodiments, the result reading parameters include the result type and the characteristic result; when the data processing device executes the above step S502, Figure 7 As shown, the following steps S701 and S702 may also be performed:

[0161] Step S701: For each part group, based on the corresponding result type and load step, output the corresponding part result cloud.

[0162] In the embodiment of the present application, the result type is used to specify the type of simulation results that need to be read in the result grouping range.

[0163] In an embodiment of the present application, the data processing device outputs a corresponding part result cloud map for each part based on the corresponding result type and load step, and determines whether the view needs to be adjusted and a screenshot output according to actual needs and application scenarios.

[0164] Step S702: For each part group, determine corresponding part result data from the corresponding part result cloud map based on the corresponding feature results.

[0165] In an embodiment of the present application, the data processing device obtains the characteristic results of the result grouping through the analysis item post-processing requirement database and reads the characteristic result value; the characteristic result refers to the result value that needs to be output for the final judgment, which can be the maximum value, the minimum value, or the result value on a specified node.

[0166] For example, if the feature result is the maximum value, the maximum value in the cloud map (part result cloud map) is read and output; if the feature result is the minimum value, the minimum value in the cloud map is read and output; if it is the result on a specified node, the result on the node is read and output.

[0167] In this way, the present application determines the corresponding part result data by outputting the part result cloud map. At this time, the cloud map can also be directly output without manual screenshots and view adjustments, which can improve the automation of data processing.

[0168] In some embodiments, the post-processing requirement parameters include at least one result grouping parameter corresponding to each working condition to be analyzed, and each result grouping parameter corresponds to an evaluation parameter; the evaluation parameter includes a target value type, a target value, a target value coefficient, and an evaluation method; the data processing device performs the above step S102 "for each working condition to be analyzed, based on the corresponding post-processing requirement parameter, determining the corresponding post-processing evaluation standard", such as Figure 8 As shown, the process includes the following steps S801 and S802:

[0169] Step S801: For each result grouping parameter, determine the corresponding actual target value according to the corresponding target value type, target value and target value coefficient.

[0170] In an embodiment of the present application, the target value type is used to specify the type of target value to be compared with the feature result; the target value is used to specify the target value to be compared with the feature result to determine whether the part is qualified; the target value coefficient is used to specify the coefficient for magnifying and reducing the target value.

[0171] In the embodiment of the present application, by setting the target value coefficient, it can be used to adjust the safety factor of the analysis and judgment, thereby adapting to more analysis needs.

[0172] In an embodiment of the present application, for each result grouping parameter, a corresponding actual target value is determined based on the corresponding target value type, target value, and target value coefficient.

[0173] Exemplarily, if the target value type is a numeric value, the product of the target value and the target value coefficient is taken as the actual target value.

[0174] Step S802: For each result grouping parameter, the corresponding actual target value and evaluation method are determined as the corresponding post-processing evaluation criteria.

[0175] In the embodiment of the present application, for each result grouping parameter, the corresponding actual target value and evaluation method are determined as the corresponding post-processing evaluation criteria. The evaluation method generally includes less than or equal to, greater than, greater than or equal to, less than, or other evaluation methods.

[0176] For example, a range can be set by multiplying the actual target value by the target value coefficient. If the range is within the range, it is considered qualified, otherwise it is unqualified. For example, it is greater than or equal to the actual target value and the first target value coefficient, and less than or equal to the actual target value and the second target value coefficient.

[0177] Thus, in this application, evaluation parameters are also set for each result grouping parameter. Thus, after obtaining the part result data, the qualification of the part is evaluated based on the evaluation criteria corresponding to the group to which the part belongs, thereby realizing an automated evaluation process.

[0178] In some embodiments, when the data processing device executes the above step S801, Figure 9 As shown, the following steps S901 and S902 may be included:

[0179] Step S901: For each result grouping parameter, if the corresponding target value type is a material parameter, determine the corresponding target value from a preset material database based on the corresponding target value type.

[0180] In an embodiment of the present application, if the target value type is a material parameter, the performance parameter specified by the target value can be obtained from the material parameter database (preset material database) based on the material grade of the part group, and the value of the performance parameter is determined as the target value;

[0181] Step S902: For each result grouping parameter, the product of the corresponding target value and the target value coefficient is determined as the corresponding actual target value.

[0182] In an embodiment of the present application, if the target value type is a material parameter, the target value, that is, the product of the value of the performance parameter and the target value coefficient is used as the actual target value.

[0183] In the embodiment of the present application, if the target value type is a numerical value, the target value is directly determined as the actual target value. By combining the target value type and the target value, it is possible to describe the actual target values of different analysis items.

[0184] In an embodiment of the present application, the target value type and target value are used to describe the actual target values of different analysis items through different combinations. When the target value type is a numerical value, the target value is a specific numerical value used to specify the actual target value; when the target value type is a material parameter, the target value is tensile strength and elongation at break, which are used to indicate that the actual target value compared with the characteristic result is the tensile strength or elongation at break of the material. In the automated post-processing process, the tensile strength or elongation at break of the material is obtained through the material parameter database.

[0185] In an embodiment of the present application, by combining target value types and target values, and in conjunction with the use of a material parameter database (preset material database), the actual target values required for different analysis items can be automatically obtained, thereby being suitable for post-processing of different analysis items. In the case of manual post-processing, if the results of finite element analysis need to be compared with the performance parameters of the material, engineers generally need to manually query the material parameters and then compare them with the results of finite element analysis, which is cumbersome, inefficient, and prone to errors.

[0186] In this way, the present application sets up a preset material database so that the target value of the required parameter can be obtained based on the evaluation parameters in the post-processing requirement parameters, and then the actual comparison is determined as the target value, realizing an automated evaluation process, making the data processing more complete.

[0187] In some embodiments, the post-processing requirement data includes the part result data of each part in the mechanical structure to be analyzed corresponding to the item to be analyzed when simulating each working condition to be analyzed, and the post-processing evaluation criteria include the evaluation method and actual target value set for the result group to which each part belongs; when the data processing device executes the above step S104, if Figure 10As shown, the following steps S1001 to S1003 may be included:

[0188] Step S1001: for each working condition to be analyzed, determine the evaluation method and actual target value of the result grouping setting corresponding to each part in the mechanical structure to be analyzed.

[0189] In an embodiment of the present application, for each working condition to be analyzed, the evaluation method and actual target value of the corresponding result grouping are determined for each part in the corresponding mechanical structure to be analyzed. For example, brittle materials such as cast aluminum alloys and cast iron generally belong to the stress result grouping, and materials such as steel plates and aluminum profiles generally belong to the strain result grouping. For the stress result grouping, the maximum principal stress of the structure is considered, while the strain result grouping considers the equivalent plastic strain or MISES stress. Then, the corresponding evaluation method, as shown in Table 1, is less than or equal to for both the strain result grouping and the stress result grouping. The actual value is discussed in the above steps S901 and S902.

[0190] Step S1002: For each part, according to the corresponding evaluation method, the corresponding part result data is compared with the actual target value to obtain the corresponding part evaluation result.

[0191] In the embodiment of the present application, for each part, it is necessary to analyze the part evaluation results under different working conditions. For example, as shown in Table 1, the maximum value of the maximum principal stress of part 1 may be less than or equal to the tensile strength of the part material under the straight tension working condition, indicating that part 1 is qualified. However, under the oblique tension working condition, the maximum value of the maximum principal stress of part 1 is greater than the tensile strength of the part material, indicating that part 1 is unqualified. The qualified and unqualified here are a form of expression of the part evaluation results. Of course, the part evaluation results may include information such as the comparison result is 3, the tensile strength is 2, greater than, and unqualified.

[0192] Step S1003: for each working condition to be analyzed, determining the parts evaluation results of different parts in the mechanical structure to be analyzed as corresponding evaluation results.

[0193] In the embodiment of the present application, under each working condition to be analyzed, the part evaluation result of each part in the mechanical result to be analyzed is the corresponding evaluation result.

[0194] In this way, the present application can determine whether the part result data corresponding to each part is qualified, obtain the evaluation results corresponding to the working conditions to be analyzed, realize automated evaluation results, and improve the automation of data processing.

[0195] like Figure 11 As shown, a flowchart of an exemplary part evaluation method is provided, including the following steps S1101 to S1107:

[0196] Step S1101: Obtain part groups.

[0197] Here, the data processing device sequentially obtains a group (part group), a parts list of the group and a material brand from the part group list (at least one part group).

[0198] Step S1102: Set the displayed parts.

[0199] Here, the data processing device operates the post-processing software through the secondary development code or application program interface of the post-processing software, so that the post-processing software only displays the parts in the parts list. For example, the data processing device operates HyperView software through the Tcl secondary development code, so that the post-processing software only displays the parts in the parts list.

[0200] Step S1103: Set the result type.

[0201] Here, the data processing device obtains the result type of the result group from the analysis item post-processing requirement database, operates the post-processing software through the secondary development code or application program interface of the post-processing software, and sets the displayed result type to the result type of the result group; exemplarily, the data processing device operates the HyperView software through the Tcl secondary development code, and sets the displayed result type to the result type of the result group.

[0202] For example, for the results grouped as “strain results” in Table 3, the explicit result is the equivalent plastic strain of the part.

[0203] Step S1104: Set the result reading load step.

[0204] Here, the data processing device obtains the load step of the working condition from the analysis item post-processing requirements database, operates the post-processing software through its secondary development code or application program interface, sets the load step for displaying the results to the load step of the working condition, obtains a cloud map of the desired results, adjusts the view based on actual needs, and takes a screenshot for output. For example, the data processing device operates HyperView software through Tcl secondary development code, sets the load step for displaying the results to the load step of the working condition, obtains a cloud map of the desired results, adjusts the view, and takes a screenshot for output.

[0205] For example, for the results grouped as "strain results" in Table 3, the cloud diagram of the equivalent plastic strain of the part in the first load step is displayed and output.

[0206] Step SS1105: Read the feature results.

[0207] Here, the data processing device obtains the characteristic results of the result grouping by analyzing the item post-processing requirement database, and operates the HyperView software through the Tcl secondary development code to read the characteristic result values.

[0208] For example, for the results grouped as "strain results" in Table 3, the maximum equivalent plastic strain value of the part is read and output.

[0209] Step S1106: Determine the actual target value.

[0210] Here, the data processing device determines the actual target value based on the target value type, the target value, and the target value coefficient.

[0211] For example, for the result grouping of "strain results" in Table 3, the target value type is "material parameter", the target value is "elongation at fracture", and the target value coefficient is 0.5. Therefore, the actual target value is: 0.5*elongation at fracture of the part material.

[0212] Step S1107: Result evaluation.

[0213] Here, the data processing equipment obtains the evaluation method from the analysis item post-processing requirement database, compares the read feature results with the actual target value according to the evaluation method, determines whether the part or part group meets the design requirements, and outputs the evaluation result.

[0214] For example, for the grouping of results in Table 3 as "strain results", the evaluation method is "less than or equal to", so whether the part meets the design requirements is judged by judging whether the maximum equivalent plastic strain of the part is less than or equal to 0.5*the elongation at fracture of the part material. If the maximum equivalent plastic strain of the part is less than or equal to 0.5*the elongation at fracture of the part material, then it is judged that the part meets the design requirements.

[0215] Step S1108: All parts grouping processing is completed.

[0216] Here, if the processing is not completed, the results of the part grouping are read according to steps S1102 to S1107 until all part groups are read.

[0217] As shown in Table 1, different combinations of characteristic results, target value types, target values, target value coefficients, and evaluation methods are given. For example, there are three such combinations: the maximum value is less than or equal to the tensile strength of the material, the maximum value is less than or equal to 0.5 times the elongation at break of the material, and the maximum value is less than 0.1. Furthermore, by combining the result evaluation method with the corresponding result reading type, three finite element analysis evaluation criteria can be combined: the maximum value of the maximum principal stress is less than or equal to the tensile strength of the material, the maximum value of the equivalent plastic strain is less than or equal to 0.5 times the elongation at break of the material, and the maximum value of the displacement is less than 0.1. By combining the result evaluation method with the combined result reading type, the commonly used evaluation criteria in finite element analysis can basically be covered.

[0218] In an embodiment of the present application, through different combinations of feature results, target value types, target values, target value coefficients and evaluation methods, it is possible to describe the result evaluation methods of different analysis items, thereby achieving machine recognition of the result evaluation methods in the post-processing process of the analysis items.

[0219] In the embodiments of the present application, through the combination of technical features such as Table 1, the post-processing requirements of different analysis items can be integrated and managed, and the post-processing requirements of different analysis items can be machine-recognizable, which is the basis for achieving fully automated post-processing.

[0220] In an embodiment of the present application, a database (table) is used to store post-processing requirement parameters for different analysis items. When the analysis items or the working conditions of each analysis item increase or decrease, or the analysis requirements change, it is only necessary to make corresponding increases, decreases or modifications to the data in the analysis item post-processing requirement database. There is no need to modify the method flow and the used programs and software tools. Therefore, it can flexibly adapt to changes in analysis requirements.

[0221] In the embodiments of the present application, Figure 2 、 Figure 4 、 Figure 6 ,as well as Figure 11 Of course, the above combination is not limited to the above combination, and other combination methods that can realize the data processing method of this application are also possible.

[0222] In this way, the present application can replace the manual post-processing process, solve the problem of low efficiency and easy errors in finite element analysis post-processing, and can be applied to the post-processing of different analysis items to realize intelligent post-processing of finite element analysis.

[0223] like Figure 12 As shown, a flowchart of an exemplary standardization post-processing method is provided, including the following steps S1201 to S1203:

[0224] Step S1201: Standardize the loading process of analysis items, read the results, and evaluate the results.

[0225] Here, the loading process, result reading, and evaluation methods of standardized analysis items include: specifying the simulation order for each working condition corresponding to the analysis item, or specifying the naming rules for the file name of each working condition result file; specifying the loading order of the loads in each working condition; specifying the rules for reading the results of each working condition, as well as the evaluation criteria and standards for the simulation results. In actual engineering, each company generally formulates corresponding finite element analysis specifications for each analysis item, making provisions for finite element modeling, working condition loading, result reading, and evaluation methods. However, when analysis and post-processing are performed manually, the regulations made are relatively rough, and some regulations still require human judgment, which is not conducive to automated processing. Therefore, it is necessary to use the above-mentioned standardized means to make the post-processing process of the analysis items automated.

[0226] Step S1202: Integrate and manage post-processing requirement information of analysis items through digital methods.

[0227] Here, digitally integrating and managing analysis item requirement information refers to reorganizing the analysis item's post-processing requirement information according to a unified standard structure and managing each analysis item's post-processing requirement information using a database, forming an analysis item post-processing requirement database. This allows the automated post-processing process to automatically capture the post-processing requirements of different analysis items, achieving fully automated post-processing. Typically, analysis specifications within an enterprise are stored and managed in the form of files, with each analysis item corresponding to an analysis specification file. However, these decentralized file-based storage and management of analysis specifications cannot be read and identified by a computer, making fully automated post-processing impossible. Therefore, integrating and managing the analysis item's post-processing requirements in a machine-readable manner is fundamental to achieving fully automated post-processing.

[0228] For example, the post-processing requirement information of the analysis items is integrated and managed through a digital method. According to the requirements of the two analysis items for result reading, the post-processing requirement information of the two analysis items is reorganized. In the analysis item post-processing requirement database, the post-processing requirement information of the two analysis items can be displayed in a tabular form, as shown in Table 1.

[0229] Step S1203: Post-process the analysis items using a unified standardized post-processing process.

[0230] Here, in the embodiments of the present application, post-processing an analysis item through a unified standardized post-processing process means automatically obtaining the analysis item's post-processing requirement information from the analysis item post-processing requirement database according to a unified standard process during the post-processing process, and completing the finite element result reading, result analysis, report generation, and result storage process based on the post-processing requirement information, thereby achieving fully automated post-processing. Because different analysis items all follow the same process to complete the post-processing process, the post-processing program does not need to be individually customized based on a specific analysis item and can be applied to different analysis items. There is no need to maintain and update the post-processing program for each analysis item.

[0231] For example, analysis items are post-processed using a unified, standardized post-processing process. A program is written in Python to automate the post-processing process. The finite element analysis result file is loaded and the results are read by calling Tcl secondary development code in HyperView software. Although Python is used in the embodiments to automate the post-processing process, any available programming language may be used to automate the post-processing process when implementing the method provided herein.

[0232] The present application provides a data processing method for obtaining an item to be analyzed for the performance analysis of a mechanical structure in an industrial product, and determining at least one working condition to be analyzed corresponding to the item to be analyzed from the correspondence between preset analysis items and working conditions; for each working condition to be analyzed, determining the corresponding post-processing requirement parameters from the correspondence between the preset working conditions and post-processing requirement parameters, and determining corresponding post-processing requirement data and post-processing evaluation criteria based on the corresponding post-processing requirement parameters; for each working condition to be analyzed, evaluating the corresponding post-processing requirement data based on the corresponding post-processing evaluation criteria to obtain a corresponding evaluation result; and generating a performance evaluation report for the mechanical structure corresponding to the item to be analyzed based on the evaluation results corresponding to different working conditions to be analyzed in the at least one working condition to be analyzed. The present application automatically extracts data through pre-set post-processing requirement parameters, thereby ensuring the efficiency and quality of data processing.

[0233] The embodiment of the present application provides a data processing device 13, such as Figure 13 As shown, including:

[0234] An acquisition module 131 is configured to acquire an item to be analyzed for mechanical structure performance analysis in an industrial product, and determine at least one working condition to be analyzed corresponding to the item to be analyzed from a preset correspondence between the analysis item and the working condition;

[0235] A determination module 132 is configured to determine, for each working condition to be analyzed, corresponding post-processing requirement parameters from a correspondence between preset working conditions and post-processing requirement parameters, and determine corresponding post-processing requirement data and post-processing evaluation criteria based on the corresponding post-processing requirement parameters;

[0236] The evaluation module 133 is used to evaluate the corresponding post-processing requirement data for each working condition to be analyzed based on the corresponding post-processing evaluation criteria to obtain a corresponding evaluation result;

[0237] The generating module 134 is configured to generate a performance evaluation report of the mechanical structure corresponding to the item to be analyzed based on the evaluation results corresponding to different working conditions to be analyzed in at least one working condition to be analyzed.

[0238] In one embodiment of the present application, the post-processing requirement parameters include the result file matching information, load step, and result requirement parameters corresponding to each working condition to be analyzed; the determination module 132 is also used to determine the corresponding result file from multiple finite element simulation result files based on the corresponding result file matching parameters for each working condition to be analyzed; for each working condition to be analyzed, based on the corresponding load step, determine the corresponding load result data from the corresponding result file; for each working condition to be analyzed, based on the corresponding result requirement parameters, determine the corresponding post-processing requirement data from the corresponding load result data.

[0239] In one embodiment of the present application, the result requirement parameters include at least one result grouping parameter, and each result grouping parameter includes a result reading range, a part grouping method, and a result reading parameter; the determination module 132 is also used to determine, for each result grouping parameter, based on the corresponding result reading range, the corresponding reading part from the model part database of the corresponding working condition simulation to be analyzed, and group the corresponding reading parts based on the corresponding part grouping method to obtain at least one corresponding part group; for the parts included in each part group, based on the corresponding result reading parameter, determine the corresponding part result data from the corresponding load result data; determine the part result data of different parts in at least one part group as the group result data of the corresponding result grouping parameter, and determine the group result data corresponding to different grouping parameters in at least one result grouping parameter as the post-processing requirement data of the corresponding working condition to be analyzed.

[0240] In one embodiment of the present application, the result reading parameters include result type and characteristic result; the determination module 132 is also used to output the corresponding part result cloud map for the parts included in each part group based on the corresponding result type and load step; for the parts included in each part group, based on the corresponding characteristic result, the corresponding part result data is determined from the corresponding part result cloud map.

[0241] In one embodiment of the present application, the post-processing requirement parameters include at least one result grouping parameter corresponding to each working condition to be analyzed, and each result grouping parameter corresponds to an evaluation parameter; the evaluation parameters include target value type, target value, target value coefficient, and evaluation method; the determination module 132 is also used to determine the corresponding actual target value for each result grouping parameter according to the corresponding target value type, target value and target value coefficient; for each result grouping parameter, the corresponding actual target value and evaluation method are determined as the corresponding post-processing evaluation criteria.

[0242] In one embodiment of the present application, the determination module 132 is also used to determine, for each result grouping parameter, if the corresponding target value type is a material parameter, the corresponding target value from the preset material database based on the corresponding target value type; for each result grouping parameter, the product of the corresponding target value and the target value coefficient is determined as the corresponding actual target value.

[0243] In one embodiment of the present application, the post-processing requirement data includes the part result data of each part in the mechanical structure to be analyzed corresponding to the item to be analyzed when simulating each working condition to be analyzed, and the post-processing evaluation criteria include the evaluation method and actual target value set for the result group to which each part belongs; the evaluation module 133 is also used to determine the evaluation method and actual target value set for the result group corresponding to each part in the mechanical structure to be analyzed for each working condition to be analyzed; for each part, the corresponding part result data is compared with the actual target value according to the corresponding evaluation method to obtain the corresponding part evaluation result; for each working condition to be analyzed, the part evaluation results of different parts in the mechanical structure to be analyzed are determined as the corresponding evaluation results.

[0244] Figure 14 This is a structural diagram of a data processing device 14 provided in an embodiment of the present application. In practical applications, based on the same disclosed concept of the above embodiments, as Figure 14 As shown, the device 14 of this embodiment includes: a processor 141 , a memory 142 and a communication bus 143 .

[0245] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. The computer-readable storage medium stores one or more programs, which can be executed by one or more processors and applied to a parking space positioning device for a parking scenario. The computer program implements the data processing method described above.

[0246] An embodiment of the present application provides a computer program product, including a computer program or instructions. When the computer program or instructions are executed by the processor 141, the data processing method as described above is implemented.

[0247] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage and optical storage, etc.) containing computer-usable program code.

[0248] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0249] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0250] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0251] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A data processing method, characterized in that: The method comprises: Obtaining an item to be analyzed for mechanical structure performance analysis in an industrial product, and determining at least one working condition to be analyzed corresponding to the item to be analyzed from a preset correspondence between analysis items and working conditions; For each of the working conditions to be analyzed, determining corresponding post-processing requirement parameters from the corresponding relationship between the preset working conditions and the post-processing requirement parameters, and determining corresponding post-processing requirement data and post-processing evaluation criteria based on the corresponding post-processing requirement parameters; For each of the working conditions to be analyzed, based on the corresponding post-processing evaluation criteria, the corresponding post-processing demand data is evaluated to obtain a corresponding evaluation result; Based on the evaluation results corresponding to different working conditions to be analyzed in the at least one working condition to be analyzed, a performance evaluation report of the mechanical structure corresponding to the item to be analyzed is generated.

2. The data processing method according to claim 1, wherein: The post-processing requirement parameters include result file matching information, load steps, and result requirement parameters corresponding to each working condition to be analyzed; For each of the working conditions to be analyzed, determining corresponding post-processing requirement data based on the corresponding post-processing requirement parameters includes: For each of the working conditions to be analyzed, determining a corresponding result file from a plurality of finite element simulation result files based on the corresponding result file matching parameters; For each of the working conditions to be analyzed, based on the corresponding load step, determining corresponding load result data from the corresponding result file; For each of the working conditions to be analyzed, the corresponding post-processing requirement data is determined from the corresponding load result data based on the corresponding result requirement parameter.

3. The data processing method according to claim 2, characterized in that: The result requirement parameters include at least one result grouping parameter, each of which includes a result reading range, a part grouping method, and a result reading parameter; For each of the working conditions to be analyzed, determining the corresponding post-processing requirement data from the corresponding load result data based on the corresponding result requirement parameter includes: For each of the result grouping parameters, based on the corresponding result reading range, a corresponding read part is determined from the corresponding model part database of the working condition simulation to be analyzed, and the corresponding read parts are grouped based on the corresponding part grouping method to obtain at least one corresponding part group; For each part included in the part group, based on the corresponding result reading parameters, determine corresponding part result data from the corresponding load result data; The part result data of different parts in the at least one part group are determined as group result data corresponding to the result grouping parameter, and the group result data corresponding to different grouping parameters in the at least one result grouping parameter are determined as the post-processing requirement data corresponding to the working condition to be analyzed.

4. The data processing method according to claim 3, wherein: The result reading parameters include a result type and a characteristic result; for each part included in the part group, determining corresponding part result data from the corresponding load result data based on the corresponding result reading parameters includes: For each part included in the part group, output a corresponding part result cloud diagram based on the corresponding result type and the load step; For each part included in the part group, the corresponding part result data is determined from the corresponding part result cloud map based on the corresponding feature result.

5. The data processing method according to claim 4, characterized in that: The post-processing requirement parameters include at least one result grouping parameter corresponding to each of the working conditions to be analyzed, and each of the result grouping parameters corresponds to an evaluation parameter; the evaluation parameters include a target value type, a target value, a target value coefficient, and an evaluation method; For each of the working conditions to be analyzed, determining a corresponding post-processing evaluation criterion based on the corresponding post-processing requirement parameter includes: For each of the result grouping parameters, determining a corresponding actual target value according to the corresponding target value type, the target value, and the target value coefficient; For each of the result grouping parameters, the corresponding actual target value and the evaluation method are determined as the corresponding post-processing evaluation criteria.

6. The data processing method according to claim 5, characterized in that: The step of determining, for each result grouping parameter, a corresponding actual target value according to the corresponding target value type, the target value, and the target value coefficient, includes: For each of the result grouping parameters, if the corresponding target value type is a material parameter, determining the corresponding target value from a preset material database based on the corresponding target value type; For each of the result grouping parameters, the product of the corresponding target value and the target value coefficient is determined as the corresponding actual target value.

7. The data processing method according to any one of claims 1 to 6, characterized in that: The post-processing requirement data includes part result data of each part in the mechanical structure to be analyzed corresponding to the item to be analyzed when simulating each working condition to be analyzed, and the post-processing evaluation criteria include an evaluation method and an actual target value set for the result group to which each part belongs; For each of the working conditions to be analyzed, based on the corresponding post-processing evaluation criteria, the corresponding post-processing requirement data is evaluated to obtain a corresponding evaluation result, including: For each of the working conditions to be analyzed, determining an evaluation method and an actual target value for the result grouping setting corresponding to each of the parts in the mechanical structure to be analyzed; For each of the parts, according to the corresponding evaluation method, the corresponding part result data is compared with the actual target value to obtain a corresponding part evaluation result; For each of the working conditions to be analyzed, the parts evaluation results of different parts in the mechanical structure to be analyzed are determined as the corresponding evaluation results.

8. A data processing device, characterized in that: The data processing device includes: an acquisition module, configured to acquire an item to be analyzed for mechanical structure performance analysis in an industrial product, and determine at least one working condition to be analyzed corresponding to the item to be analyzed from a preset correspondence between analysis items and working conditions; a determination module, configured to determine, for each of the working conditions to be analyzed, corresponding post-processing requirement parameters from a correspondence between preset working conditions and post-processing requirement parameters, and determine corresponding post-processing requirement data and post-processing evaluation criteria based on the corresponding post-processing requirement parameters; An evaluation module, configured to evaluate the corresponding post-processing requirement data based on the corresponding post-processing evaluation criteria for each working condition to be analyzed, and obtain a corresponding evaluation result; A generating module is used to generate a performance evaluation report of the mechanical structure corresponding to the item to be analyzed based on the evaluation results corresponding to different working conditions to be analyzed in the at least one working condition to be analyzed.

9. A data processing device, characterized in that: The data processing device includes: a processor, a memory and a communication bus; when the processor executes the running program stored in the memory, the data processing method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the data processing method according to any one of claims 1 to 7 is implemented.

Images