Hard point data processing method and device, equipment, medium and product

Abstract

The invention provides a hard point data processing method and device, equipment, a medium and a product, and relates to the technical field of data processing. The method comprises the steps that a first hard point data list comprising at least one piece of to-be-modeled vehicle part hard point data and a second hard point data list which is stored in a database and comprises multiple pieces of vehicle part template hard point data are obtained, and the hard point data comprise hard point names and hard point coordinate values; based on the first hard point data list and the second hard point data list, hard point coordinate values, matched with hard point names in the second hard point data list, in the first hard point data list are replaced into the second hard point data through an editing distance algorithm, and the processed second hard point data list is obtained and output. By means of the method, errors caused by manual intervention are reduced, the efficiency and accuracy of hard point data processing are improved, and then the efficiency and accuracy of vehicle part modeling are improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, equipment, medium and product for processing hard data. Background Technology

[0002] In the field of automotive engineering design, when engineers use Computer-Aided Engineering (CAE) simulation software to build complex models, they typically need to first create a large number of hard points, and then write positions or orientations based on these hard points to create modeling elements such as components, constraints, and force elements. Therefore, fine-tuning the hard points can achieve the purpose of modifying the entire model.

[0003] Because different automakers may use similar or identical names for hard points, it is necessary to verify the hard points to be modeled against the template hard points when modeling vehicle parts. Existing simulation software's hard point editing window simply displays all template hard points in a table, requiring engineers to verify each hard point against the hard point to be modeled and all template hard points.

[0004] However, manual proofreading is not only extremely labor-intensive, but also prone to errors. Summary of the Invention

[0005] This application provides a method, apparatus, device, medium, and product for processing hard point data, which aims to improve the efficiency and accuracy of hard point data processing, while reducing the user's operating threshold and enhancing the user experience.

[0006] In a first aspect, embodiments of this application provide a method for processing hard point data, including:

[0007] Obtain a first hard point data list and a second hard point data list stored in the database. The first hard point data list includes hard point data of at least one vehicle component to be modeled, and the second hard point data list includes hard point data of multiple vehicle component templates. The hard point data includes hard point name and hard point coordinate value.

[0008] Based on the first hard point data list and the second hard point data list, the hard point coordinate values ​​that match the hard point names in the first hard point data list and the second hard point data list are replaced in the second hard point data list by the edit distance algorithm, so as to obtain the processed second hard point data list.

[0009] Output the processed list of the second hard point data.

[0010] In one possible implementation, based on the first hardpoint data list and the second hardpoint data list, and using an edit distance algorithm, the hardpoint coordinate values ​​in the first hardpoint data list that match the hardpoint names in the second hardpoint data list are replaced before being added to the second hardpoint data list. The method further includes:

[0011] Each first hardpoint name in the first hardpoint data list is preprocessed, and each second hardpoint name in the second hardpoint data list is preprocessed. The preprocessing includes at least one of removing spaces, removing special characters, and standardizing the character format in the hardpoint name.

[0012] In one possible implementation, the step of replacing the hardpoint coordinate values ​​in the first hardpoint data list that match the hardpoint names in the second hardpoint data list with those in the second hardpoint data list using an edit distance algorithm, based on the first hardpoint data list and the second hardpoint data list, includes:

[0013] For each second hardpoint name, the minimum number of edits between the second hardpoint name and each first hardpoint name is calculated using an edit distance algorithm;

[0014] If the minimum number of edits is 0, modify the hard point coordinate value corresponding to the second hard point name to the hard point coordinate value corresponding to the first hard point name with the minimum number of edits being 0.

[0015] If the minimum number of edits is greater than 0, then the hard point coordinate value corresponding to the second hard point name will be modified to the hard point coordinate value corresponding to the first hard point name with the minimum number of edits, and a modification flag will be displayed.

[0016] In one possible implementation, the method further includes:

[0017] If the number of the first hardpoint names is greater than the number of the second hardpoint names, then the hardpoint data corresponding to the remaining unmatched first hardpoint names after the matching is completed will be filled into the second hardpoint data list in order.

[0018] In one possible implementation, the method further includes:

[0019] Based on the processed second hard point data list, it is cascaded with the vehicle component model to complete the modeling of the vehicle component.

[0020] In one possible implementation, the method further includes:

[0021] Based on the processed second hard point data list, in response to the user's selection and drag operations, the hard point data in the processed second hard point data list can be adjusted.

[0022] Secondly, embodiments of this application provide a hard point data processing apparatus, comprising:

[0023] The first processing module is used to obtain a first hard point data list and a second hard point data list stored in the database. The first hard point data list includes hard point data of at least one vehicle component to be modeled, and the second hard point data list includes hard point data of multiple vehicle component templates. The hard point data includes hard point name and hard point coordinate value.

[0024] The second processing module is used to replace the hard point coordinate values ​​in the first hard point data list that match the hard point names in the second hard point data list with the hard point coordinate values ​​in the second hard point data list using an edit distance algorithm, based on the first hard point data list and the second hard point data list, to obtain the processed second hard point data list.

[0025] The third processing module is used to output the processed second hard point data list.

[0026] Thirdly, embodiments of this application provide a computer device, including: a memory and a processor;

[0027] The memory stores computer-executed instructions;

[0028] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0029] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0030] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0031] This application provides a method, apparatus, device, medium, and product for processing hardpoint data. It acquires a first hardpoint data list including hardpoint data of at least one vehicle component to be modeled, and a second hardpoint data list stored in a database including hardpoint data of multiple vehicle component templates. The hardpoint data includes hardpoint names and hardpoint coordinate values. Then, based on the first and second hardpoint data lists, an edit distance algorithm is used to replace the hardpoint coordinate values ​​in the second hardpoint data list with those matching hardpoint names in the first and second hardpoint data lists, resulting in a processed second hardpoint data list, which is then output. This method automates hardpoint data processing, reduces errors caused by manual intervention, improves user experience, and further enhances the efficiency and accuracy of vehicle component modeling. Attached Figure Description

[0032] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0033] Figure 1 A flowchart illustrating a method for processing hard point data provided in this application. Figure 1 ;

[0034] Figure 2 A flowchart illustrating a method for processing hard point data provided in this application. Figure 2 ;

[0035] Figure 3 A schematic diagram of the interface editing method for processing hard point data provided in this application;

[0036] Figure 4 A schematic diagram of a hard spot data processing device provided in this application;

[0037] Figure 5 This is a schematic diagram of the structure of a computer device provided in this application.

[0038] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0039] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0040] The application background of this application is explained as follows:

[0041] In the field of CAE simulation modeling in automotive engineering, hard points are the core benchmark elements that engineers pre-set before building models of complex components such as vehicle body frames, chassis suspensions, and power systems. In essence, they are virtual anchor points with precise three-dimensional coordinates (x, y, z axis positions) and clear directional attributes, which are used as the basic reference for subsequent modeling.

[0042] In practical engineering, hard point data varies across different vehicle models, such as front and rear track width and wheelbase. Automakers typically compile this hard point data into a table format. Engineers can then adjust the hard points in the template model according to specific design requirements to model vehicle components, significantly reducing repetitive operations. However, since different automakers may use similar or identical names for hard points, it's necessary to verify the hard points to be modeled against the template hard points when modeling vehicle components. Existing CAE simulation software's hard point editing window only lists all template hard points in a table format. Engineers must manually compare the hard point names included in the design requirements with those in the template hard points, inputting data line by line.

[0043] However, manual proofreading is not only extremely labor-intensive, but also prone to errors.

[0044] Therefore, providing a method for processing hard data that can significantly reduce engineers' workload, lower operational error rates, and improve the accuracy of model adjustments and user experience is an urgent technical problem to be solved.

[0045] To address the aforementioned technical problems, the inventors, during their research on hard point data processing, discovered that by using the Levenshtein Distance algorithm, the hard point data of the vehicle component to be modeled is compared with pre-stored template hard point data of the vehicle component in the database. Hard point data in the hard point data of the vehicle component to be modeled whose names match those in the template hard point data is used to replace the corresponding template hard point data. Finally, based on the template hard point data obtained after matching, it is cascaded with the vehicle component model to complete the modeling of the vehicle component. This not only improves the processing efficiency of hard point data but also significantly reduces the workload of engineers and lowers the error rate of manual operation. Based on this, this application provides a method, apparatus, device, medium, and product for processing hard point data.

[0046] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0047] Figure 1 A flowchart illustrating a method for processing hard point data provided in this application. Figure 1 ,like Figure 1 As shown, the method includes:

[0048] S101: Obtain a first hard point data list and a second hard point data list stored in the database. The first hard point data list includes hard point data of at least one vehicle component to be modeled, and the second hard point data list includes hard point data of multiple vehicle component templates. The hard point data includes hard point names and hard point coordinate values.

[0049] In this step, the hard point data of the vehicle component to be modeled refers to the precise reference data provided by the manufacturer for a specific vehicle model to be developed or simulated, corresponding to a key component. The hard point data for each vehicle component to be modeled must include at least the specific coordinates of that hard point in the vehicle's 3D coordinate system. And the name of the hardpoint. Understandably, the structure and function of a vehicle component need to be defined by at least one key reference point / hardpoint. Therefore, the hardpoint data corresponding to at least one hardpoint constitutes the hardpoint data set of the vehicle component to be modeled, i.e., the first hardpoint data list.

[0050] Vehicle component template hard point data refers to standardized and universal hard point benchmark data for vehicle components that are pre-stored in a database. These data are typically based on mature vehicle platforms, classic component designs, or industry-standard specifications and serve as reference templates for subsequent modeling of similar components. Similarly, the hard point data corresponding to multiple template hard points form a vehicle component template hard point data set, i.e., a second hard point data list.

[0051] For example, the first hard point data list can be imported using common spreadsheet formats such as Excel. The table clearly lists all hard point information corresponding to each component of the vehicle to be modeled in a standardized format: hard point name and x, y, z coordinate values. The table supports drag-and-drop, filtering, exporting, pasting, and editing functions. Alternatively, the hard point data of the vehicle components to be modeled can be copied from external sources and then pasted into the table without using the import method. This reduces the user's operational costs and improves the user experience.

[0052] S102: Based on the first hard point data list and the second hard point data list, the hard point coordinate values ​​that match the hard point names in the first hard point data list and the second hard point data list are replaced in the second hard point data list using the edit distance algorithm, so as to obtain the processed second hard point data list.

[0053] The Levenshtein Distance algorithm, also known as the edit distance algorithm, is a classic algorithm used to calculate the difference between two strings (source characters and target characters). Its core objective is to obtain the minimum number of edits required to transform a source string into a target string. Transformations include operations such as insertion, replacement, and deletion. For example, transforming the source string "cat" into the target string "cart" requires inserting "r"; transforming the source string "apple" into the target string "aple" requires deleting "p"; and transforming the source string "book" into the target string "hook" requires replacing "b" with "h". By default, with each transformation operation having equal weight, the number of edits for all three transformation operations is 1.

[0054] Specifically, based on each hardpoint data in the second hardpoint data list, the Levenshtein Distance algorithm is used to calculate the edit distance between the hardpoint name of that hardpoint data and the hardpoint name in the first hardpoint data list, i.e., the minimum number of edits. The smaller the edit distance, the higher the similarity between the hardpoint names of the two hardpoint data. This determines the hardpoint data pair with the best matching hardpoint names. After the matching relationship is established, the coordinate values ​​of the hardpoint in the first hardpoint data list are replaced with the coordinate values ​​of the corresponding matching hardpoint in the second hardpoint data list. Finally, all the replaced and retained hardpoint data in the second hardpoint data list are integrated to obtain the processed second hardpoint data list. It can be understood that the processed second hardpoint data list is obtained by filling the vehicle template hardpoint data list with the hardpoint data of the vehicle component to be modeled. This processed second hardpoint data list retains the original standardized structure and baseline information of unmatched hardpoints in the vehicle template hardpoint data list, and also includes the actual coordinate values ​​of the hardpoints in the vehicle component to be modeled whose names match the hardpoint names in the vehicle template hardpoint data.

[0055] S103: Output the processed list of the second hard point data.

[0056] The hard point data processing method provided in this application involves obtaining a first hard point data list including hard point data of the vehicle component to be modeled and a second hard point data list containing hard point data of vehicle component templates stored in a database. An edit distance algorithm is used to automatically match the similarity of hard point names between the two hard point data lists. The matching hard point coordinate values ​​from the first and second hard point data lists are then replaced in the second hard point data list, thereby generating and outputting a processed second hard point data list. This method achieves automated integration of hard point data, reduces errors caused by manual intervention, and improves the efficiency and accuracy of vehicle component modeling. It is suitable for data optimization in vehicle development and simulation processes.

[0057] Figure 2 A flowchart illustrating a method for processing hard point data provided in this application. Figure 2 ,like Figure 2 As shown, in Figure 1 Based on the embodiment, in S102, based on the first hard point data list and the second hard point data list, the hard point coordinate values ​​that match the hard point names in the first hard point data list and the second hard point data list are replaced in the second hard point data list using an edit distance algorithm. Specifically, this includes:

[0058] In one possible implementation, prior to S102, the method for processing the hard point data further includes:

[0059] S201: Preprocess each first hardpoint name in the first hardpoint data list.

[0060] S202: Preprocess each second hardpoint name in the second hardpoint data list.

[0061] The preprocessing includes at least one of removing spaces, removing special characters, and standardizing the character format in hard point names.

[0062] Specifically, removing spaces means deleting spaces from each hard point name (first hard point name and second hard point name) in the hard point data list (first hard point data list and second hard point data list); removing special characters means deleting non-text symbols in each hard point name, such as underscores, punctuation marks, etc.; character format standardization means standardizing the case of characters in each hard point name, such as standardizing all to uppercase or standardizing all to lowercase.

[0063] By preprocessing each hardpoint name, hardpoint names that originally appeared different due to variations in format, symbols, or expression habits are transformed into a consistent format. This reduces errors during subsequent name matching using the Levenshtein Distance algorithm, ensuring that hardpoints with truly identical meanings can be accurately identified, and providing a reliable data foundation for efficient and accurate matching and replacement.

[0064] S203: For each second hard point name, calculate the minimum number of edits between the second hard point name and each first hard point name using the edit distance algorithm.

[0065] For example, for a preprocessed second hardpoint name (assuming the second hardpoint name is string a with length m), calculate the minimum number of edits between the second hardpoint name and each first hardpoint name in the first hardpoint data list (assuming a hardpoint name is string b with length n).

[0066] Specifically, based on the first hardpoint name and the second hardpoint name, a... A two-dimensional table is constructed, where the cell in the i-th row and j-th column stores the minimum number of edits required to convert the first i characters of string a into the first j characters of string b. The table is then initialized: the first row (when i=0) is filled with values ​​from 0 to n from left to right, representing the number of operations j required to insert n characters into an empty string to obtain the first j characters of string b; the first column (when j=0) is filled with values ​​from 0 to m from top to bottom, representing the number of operations i required to delete i characters from the first i characters of string a to obtain an empty string.

[0067] Then, the other cells of the two-dimensional table are filled row by row and column by column. When processing the i-th row and j-th column, if the i-th character of string a (i.e., a[i-1], since string indexing starts from 0) is the same as the j-th character of string b (i.e., b[j-1]), then the value of the cell is equal to the value of the top-left cell (i-1 row and j-1 column), that is, no additional operation is required; if the two characters are different, then the value of the cell is the minimum of the top-left cell value plus 1 (replacement operation), the value of the cell above (i-1 row and j-th column) plus 1 (deletion operation), and the value of the cell to the left (i-1 row and j-1 column) plus 1 (insertion operation).

[0068] Once the two-dimensional table is fully filled, the value in the bottom right cell (row m, column n) represents the minimum number of edits required between the current second hardpoint name and the first hardpoint name.

[0069] S204: Determine if the minimum number of edits is 0.

[0070] If yes, then execute S205; otherwise, execute S206.

[0071] S205: Modify the hardpoint coordinate value corresponding to the second hardpoint name to the hardpoint coordinate value corresponding to the first hardpoint name, which has a minimum number of edits of 0.

[0072] In other words, if the minimum number of edits is 0, then the hardpoint coordinates corresponding to the second hardpoint name will be modified to the hardpoint coordinates corresponding to the first hardpoint name, which has a minimum number of edits of 0.

[0073] Understandably, a minimum number of edits of 0 means that two hard point names can be completely identical after being calculated by the Levenshtein Distance algorithm without any insertion, deletion, or replacement operations. In other words, the two hard point names are completely identical.

[0074] Specifically, the original coordinate values ​​corresponding to the second hard point name in the second hard point data list are replaced with the coordinate values ​​corresponding to the first hard point name in the first hard point data list, which has been edited at least 0 times. This ensures that hard points in the second hard point data list (vehicle component template hard point data list) with names that are completely identical to those in the first hard point data list (the hard point data list of the vehicle component to be modeled) can be accurately updated to the actual coordinates of the hard point data of the vehicle component to be modeled. This preserves the structural framework of the template while precisely incorporating the core parameters of the hard point data of the vehicle component to be modeled, providing a more reliable benchmark for subsequent modeling.

[0075] S206: Modify the hardpoint coordinate value corresponding to the second hardpoint name to the hardpoint coordinate value corresponding to the first hardpoint name with the fewest number of edits, and display the modification mark.

[0076] In other words, if the minimum number of edits is greater than 0, the hard point coordinate value corresponding to the second hard point name will be modified to the hard point coordinate value corresponding to the first hard point name with the minimum number of edits, and a modification flag will be displayed.

[0077] Understandably, the minimum number of edits refers to the minimum number of edits required to make two hardpoint names identical after calculation by the Levenshtein Distance algorithm, through the insertion, deletion, or replacement of characters. In other words, the first hardpoint name with the minimum number of edits is the hardpoint name in the first hardpoint data list that is closest to the second hardpoint name.

[0078] The original coordinate values ​​corresponding to the second hardpoint name in the second hardpoint data list are replaced with the hardpoint coordinate values ​​corresponding to the first hardpoint name in the first hardpoint data list, which have the fewest edits. The technical principle and effect are consistent with those mentioned in S205, and will not be repeated here. Simultaneously, a modification indicator is displayed on the replaced second hardpoint name and its corresponding hardpoint coordinate values. This is achieved by highlighting the table row containing the hardpoint data (or the cell containing the coordinate values) with a blue or yellow background to alert engineers of any incomplete matches, facilitating subsequent verification and adjustments, thus balancing data processing efficiency and accuracy.

[0079] S207: Determine whether the first hard point name or the second hard point name is a complete match.

[0080] If not, return to continue executing S203; if yes, execute S208.

[0081] S208: Determine whether the number of the first hardpoint names is equal to the number of the second hardpoint names.

[0082] If yes, then execute S209; otherwise, execute S210.

[0083] S209: Obtain the processed list of second hard point data.

[0084] In other words, if either the first hardpoint name or the second hardpoint name achieves a complete match, and the number of first hardpoint names equals the number of second hardpoint names, then the list of second hardpoint data that achieves a complete match is the processed list of second hardpoint data.

[0085] S210: Determine whether the number of the first hard point names is greater than the number of the second hard point names.

[0086] If yes, then execute S211; otherwise, execute S212.

[0087] S211: After the matching is completed, fill the hard point data corresponding to the names of the unmatched first hard points into the second hard point data list in order to obtain the processed second hard point data list.

[0088] In other words, if the number of first hardpoint names is greater than the number of second hardpoint names, the hardpoint data corresponding to the remaining unmatched first hardpoint names after the matching is completed will be filled into the second hardpoint data list in order.

[0089] The remaining unmatched first hardpoint data refers to the hardpoint data in the first hardpoint data list that has not established a matching relationship with any second hardpoint name after all second hardpoint names have been matched.

[0090] Specifically, the remaining unmatched first hard point names are added to the existing content of the second hard point data list in the order they were originally arranged in the first hard point data list. This results in a processed second hard point data list, which ensures that the vehicle component template hard point data list can completely cover the hard point data of the vehicle component to be modeled, avoiding the omission of key data due to insufficient hard points in the template hard point data list.

[0091] S212: Based on the hard point data corresponding to the second hard point name that has been matched with the first hard point name, and the hard point data corresponding to the remaining unmatched second hard point names after the matching is completed, a processed list of second hard point data is obtained.

[0092] In other words, if the number of first hardpoint names is less than the number of second hardpoint names, then the processed list of second hardpoint data is obtained based on the hardpoint data corresponding to the second hardpoint names that have been matched with the first hardpoint names, and the hardpoint data corresponding to the remaining unmatched second hardpoint names after the matching is completed.

[0093] The remaining unmatched second hardpoint names correspond to hardpoint data that, after matching with all first hardpoint names, do not have a matching relationship with any first hardpoint name in the second hardpoint data list.

[0094] Specifically, after completing the hardpoint matching and coordinate replacement operations in all the first hardpoint data lists, the second hardpoint data list includes two types of hardpoint data: one type is hardpoint data that has been matched with all the first hardpoint names (whether fully matched or not fully matched), and has been updated with the coordinate values ​​of the hardpoint data of the vehicle component to be modeled (not fully matched items have a modification mark); the other type is the vehicle component template hardpoint data that retains its original state after the matching is completed. Based on these two types of hardpoint data, the processed second hardpoint data list retains both the actual hardpoint parameters of the vehicle component hardpoint data to be modeled and the standardized structure of the vehicle component template hardpoint data list, serving as the core benchmark data for subsequent CAE simulation modeling.

[0095] S213: Based on the processed second hard point data list, cascade it with the vehicle component model to complete the modeling of the vehicle component.

[0096] In this step, the vehicle component model refers to the pre-defined basic model framework in the CAE simulation software used to construct various vehicle components. For example, the precise coordinate values ​​of each hard point in the processed second hard point data list are associated and bound to the vehicle component model in the CAE software. This means that the hard point data in the processed second hard point data list serves as the positional reference and structural constraints of the component model, transforming the hard point data into a three-dimensional component model with actual spatial position and structural relationships, thus completing the modeling of the vehicle component.

[0097] The hardpoint data processing method provided in this application includes: firstly, preprocessing the hardpoint names in the two hardpoint data lists, including removing spaces, special characters, and standardizing character formats to eliminate matching errors caused by format differences. Next, for each second hardpoint name, the minimum number of edits (i.e., edit distance) between it and each first hardpoint name is calculated to evaluate name similarity. If the edit distance is 0, indicating a complete name match, the second hardpoint coordinate value is directly replaced with the corresponding first hardpoint coordinate value; if the edit distance is not 0, the first hardpoint name with the smallest edit distance is selected for coordinate replacement, and a modification flag is displayed to indicate a non-complete match. Furthermore, if the number of first hardpoint names is greater than the number of second hardpoint names, the remaining unmatched first hardpoint data is appended sequentially to the second hardpoint data list; otherwise, the matched and unmatched second hardpoint data are retained. The processed second hardpoint data list is obtained, and it is then cascaded with a vehicle component model to complete the modeling of the vehicle component.

[0098] By employing preprocessing and distance editing algorithms, similar hardpoint names can be intelligently identified and matched, reducing human error caused by differences in name format or description, and enabling automated coordinate updates. Simultaneously, for situations where hardpoint data list lengths vary, the integrity of the hardpoint data is ensured, preventing the omission of critical hardpoints. The introduced modification markers facilitate engineers' quick verification and adjustment of incomplete matches. These methods improve the accuracy and efficiency of hardpoint data processing, reduce labor costs, and enhance the consistency between the model and actual component data, laying a reliable foundation for subsequent simulation analysis.

[0099] Based on the above embodiments, the method for processing hard spot data further includes:

[0100] In one possible implementation, based on the processed second hardpoint data list, adjustments are made to the hardpoint data in the processed second hardpoint data list in response to the user's selection and drag operations.

[0101] Understandably, while the processed second hardpoint data list has achieved a one-to-one match between the hardpoint data of the vehicle component to be modeled and the hardpoint data of the vehicle component template, some rows still fail to achieve a perfect one-to-one correspondence due to differences in name descriptions, special naming rules, etc. For example, hardpoint names may not match completely (highlighted). At this point, in response to the user's selection and dragging operations, that is, the user can select one or more rows of hardpoint data in the processed second hardpoint data list (one row: click or long press to select; several rows: hold down the Ctrl key or select multiple consecutive or non-consecutive rows of hardpoint data by using a selection box, which will be highlighted or visually marked after selection), click and drag the selected row to the target row position / target row area, and release the mouse or touch. The two rows / two groups of hardpoint data (including hardpoint names, hardpoint coordinate values, modification indicators, and all other information) will be completely swapped. The hardpoint data of the originally selected row will be replaced in the target row position / target row area, and the hardpoint data of the target row / target row area will be moved to the original selected row position.

[0102] Throughout the operation, the processed second hard point data list will be refreshed in real time to display the swapped results, allowing users to intuitively confirm the adjustment effect. This flexible manual intervention method makes up for the local shortcomings of intelligent matching and provides a more accurate data foundation for subsequent modeling.

[0103] Figure 3 A schematic diagram of the interface editing method for processing hard point data provided in this application is shown. In one possible implementation, the method for processing hard point data further includes:

[0104] When replacing the hardpoint coordinates that match the hardpoint names in the first hardpoint data list with those in the second hardpoint data list using the edit distance algorithm, such as... Figure 3 As shown, for hard points with symmetrical attributes in vehicle components, the coordinate values ​​of the hard points on the opposite side of the first hard point are synchronously modified in the second hard point data list (mutually symmetrical hard points are marked with the same color). This ensures that the coordinates of symmetrical hard points always maintain a correspondence that conforms to the symmetry logic of the vehicle structure, maintaining data consistency and accuracy without manual user intervention.

[0105] In addition, such as Figure 3 As shown, the hard point data processing method provides two modes: independent editing and merged editing. In merged editing mode, the hard point coordinate values ​​are displayed in one column, and the three coordinate values ​​can be modified uniformly by directly inputting the complete coordinate combination. In independent editing mode, the hard point coordinate values ​​are displayed in three columns, and the corresponding coordinate axis values ​​can be modified separately for each column without operating on the three coordinate values ​​at the same time, thus balancing the flexibility of editing and the intuitiveness of data management.

[0106] Figure 4 This application provides a schematic diagram of the structure of a hard point data processing device, as shown below. Figure 4 As shown, the hard point data processing device 40 provided in this embodiment includes:

[0107] The first processing module 401 is used to obtain a first hard point data list and a second hard point data list stored in the database. The first hard point data list includes hard point data of at least one vehicle component to be modeled, and the second hard point data list includes hard point data of multiple vehicle component templates. The hard point data includes hard point name and hard point coordinate value.

[0108] The second processing module 402 is used to replace the hard point coordinate values ​​that match the hard point names in the first hard point data list with those in the second hard point data list with the hard point coordinate values ​​in the second hard point data list based on the first hard point data list and the second hard point data list using an edit distance algorithm, so as to obtain the processed second hard point data list.

[0109] The third processing module 403 is used to output the processed second hard point data list.

[0110] In one possible implementation, the hard point data processing device 40 further includes:

[0111] The fourth processing module 404 is used to preprocess each first hard point name in the first hard point data list and to preprocess each second hard point name in the second hard point data list. The preprocessing includes at least one of removing spaces, removing special characters, and standardizing the character format in the hard point name.

[0112] In one possible implementation, the second processing module 402 is specifically used for:

[0113] For each second hardpoint name, the minimum number of edits between the second hardpoint name and each first hardpoint name is calculated using the edit distance algorithm;

[0114] If the minimum number of edits is 0, modify the hard point coordinate value corresponding to the second hard point name to the hard point coordinate value corresponding to the first hard point name with the minimum number of edits being 0.

[0115] If the minimum number of edits is greater than 0, then the hardpoint coordinate value corresponding to the second hardpoint name will be modified to the hardpoint coordinate value corresponding to the first hardpoint name with the minimum number of edits, and a modification flag will be displayed.

[0116] In one possible implementation, the hard point data processing device 40 further includes:

[0117] The fifth processing module 405 is used to fill the hardpoint data corresponding to the remaining unmatched first hardpoint names into the second hardpoint data list in order if the number of first hardpoint names is greater than the number of second hardpoint names.

[0118] In one possible implementation, the hard point data processing device 40 further includes:

[0119] The sixth processing module 406 is used to cascade the processed second hard point data list with the vehicle component model to complete the modeling of the vehicle component.

[0120] In one possible implementation, the hard point data processing device 40 further includes:

[0121] The seventh processing module 407 is used to adjust the hard point data in the processed second hard point data list in response to the user's selection and drag operations.

[0122] The hard spot data processing device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described again in this embodiment.

[0123] Figure 5 A schematic diagram of the structure of a computer device provided in this application, such as... Figure 5 As shown, the computer device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the computer device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0124] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0125] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0126] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0127] The memory may include random access memory (RAM) in high-speed memory, and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0128] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0129] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0130] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0131] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0132] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside within an ASIC. Alternatively, the processor and the readable storage medium can exist as discrete components in a device.

[0133] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0134] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0135] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0136] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0137] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0138] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for processing hard point data, characterized in that, include: Obtain a first hard point data list and a second hard point data list stored in the database. The first hard point data list includes hard point data of at least one vehicle component to be modeled, and the second hard point data list includes hard point data of multiple vehicle component templates. The hard point data includes hard point name and hard point coordinate value. Based on the first hard point data list and the second hard point data list, the hard point coordinate values ​​that match the hard point names in the first hard point data list and the second hard point data list are replaced in the second hard point data list by the edit distance algorithm, so as to obtain the processed second hard point data list. Output the processed list of the second hard point data.

2. The method according to claim 1, characterized in that, The method, which involves replacing the hardpoint coordinates in the first hardpoint data list with those in the second hardpoint data list before adding them to the second hardpoint data list using an edit distance algorithm based on the first hardpoint data list and the second hardpoint data list, further includes: Each first hardpoint name in the first hardpoint data list is preprocessed, and each second hardpoint name in the second hardpoint data list is preprocessed. The preprocessing includes at least one of removing spaces, removing special characters, and standardizing the character format in the hardpoint name.

3. The method according to claim 1 or 2, characterized in that, The step of replacing the hardpoint coordinate values ​​in the first hardpoint data list with those in the second hardpoint data list, based on the first hardpoint data list and the second hardpoint data list, with hardpoint coordinate values ​​matching hardpoint names in the second hardpoint data list using an edit distance algorithm, includes: For each second hardpoint name, the minimum number of edits between the second hardpoint name and each first hardpoint name is calculated using an edit distance algorithm; If the minimum number of edits is 0, modify the hard point coordinate value corresponding to the second hard point name to the hard point coordinate value corresponding to the first hard point name with the minimum number of edits being 0. If the minimum number of edits is greater than 0, then the hard point coordinate value corresponding to the second hard point name will be modified to the hard point coordinate value corresponding to the first hard point name with the minimum number of edits, and a modification flag will be displayed.

4. The method according to claim 3, characterized in that, The method further includes: If the number of the first hardpoint names is greater than the number of the second hardpoint names, then the hardpoint data corresponding to the remaining unmatched first hardpoint names after the matching is completed will be filled into the second hardpoint data list in order.

5. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the processed second hard point data list, it is cascaded with the vehicle component model to complete the modeling of the vehicle component.

6. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the processed second hard point data list, in response to the user's selection and drag operations, the hard point data in the processed second hard point data list can be adjusted.

7. A hard point data processing apparatus, characterized in that, include: The first processing module is used to obtain a first hard point data list and a second hard point data list stored in the database. The first hard point data list includes hard point data of at least one vehicle component to be modeled, and the second hard point data list includes hard point data of multiple vehicle component templates. The hard point data includes hard point name and hard point coordinate value. The second processing module is used to replace the hard point coordinate values ​​in the first hard point data list that match the hard point names in the second hard point data list with the hard point coordinate values ​​in the second hard point data list using an edit distance algorithm, based on the first hard point data list and the second hard point data list, to obtain the processed second hard point data list. The third processing module is used to output the processed second hard point data list.

8. A computer device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1 to 6.

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