Pedestrian APLI leg collision data processing method and device, medium and equipment
By dividing the pedestrian APLI leg collision data into multiple arrays and calling the calculation model calculation result data, the problem of cumbersome and error in pedestrian protection APLI leg model simulation analysis is solved, and fast and accurate data processing and evaluation is achieved.
Patent Information
- Application Number
- CN202411551166.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-01
- Publication Date
- 2025-02-18
AI Technical Summary
In the pedestrian protection APLI leg shape simulation analysis, engineers need to process a large amount of data, which leads to cumbersome, time-consuming and prone to human errors, affecting the accuracy of the evaluation.
By obtaining the data to be processed, dividing it into multiple arrays, and calling the leg calculation model to calculate the result data of each array, including the thigh bending moment, the calf bending moment and the knee ligament elongation amount, and finally calculating the legs based on these result data. Scoring results of the test area.
The rapid and accurate processing of pedestrian APLI leg collision data is achieved, which reduces the workload of engineers, improves data processing efficiency, shortens R&D time, and reduces human participation to improve the accuracy of data processing.
Smart Images
Figure CN119475580A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field, and in particular to a method, device, medium and equipment for processing pedestrian APLI leg collision data. Background Art
[0002] As people's living standards and travel needs improve, the number of cars is increasing, and collisions between cars and pedestrians also occur from time to time. In collisions, pedestrians are mainly injured in the head and legs. In order to reduce pedestrian casualties, pedestrian protection regulations have been introduced, which put forward certain requirements for the design and construction of the front structure of the car. Pedestrian protection regulations such as CNCAP and CIASI all have assessments of the injuries to pedestrians' legs in accidents.
[0003] In the leg shape simulation analysis and calculation of pedestrian protection APLI (advanced Pedestrian Legform Impactor, APLI for short), according to the evaluation scope stipulated by the regulations, the general APLI leg shape simulation analysis is usually around 10-15 points, and each point corresponds to an independent model. In the simulation process of pedestrian protection APLI leg collision, the submission of full tasks, the extraction of results and the corresponding scoring statistics are tedious and time-consuming tasks for engineers, with a large amount of repetitive work and affecting the progress of project development. In addition, errors caused by human factors will also affect the accuracy of the evaluation. Therefore, a method is needed to quickly and accurately process pedestrian APLI leg collision data. Summary of the invention
[0004] In order to solve the above technical problems, the present application is proposed. The embodiments of the present application provide a method, device, medium and equipment for processing pedestrian APLI leg collision data.
[0005] According to one aspect of the present application, a method for processing pedestrian APLI leg collision data is provided, including: obtaining data to be processed; wherein the data to be processed is stored in at least one folder; based on the number of data points to be analyzed, dividing the data to be processed in the same folder into multiple arrays; wherein all the data points to be analyzed constitute a leg test area; calling a leg calculation model to calculate the array corresponding to each data point to be analyzed respectively, and obtaining result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; and calculating a scoring result of the leg test area based on the result data.
[0006] In one embodiment, the calling of the leg calculation model to respectively calculate the array corresponding to each of the data points to be analyzed to obtain the result data includes: calling the leg calculation model to respectively calculate the array corresponding to each of the data points to be analyzed, and periodically monitoring the calculation progress until the result data is obtained.
[0007] In one embodiment, after the leg calculation model is called to calculate the array corresponding to each of the data points to be analyzed and the result data is obtained, the method for processing the pedestrian APLI leg collision data also includes: calculating a result report of the leg test area according to the result data corresponding to all the data points to be analyzed; wherein the result report includes a plurality of thigh bending moments, a plurality of calf bending moments and a knee ligament elongation for each of the data points to be analyzed; and calculating the scoring result of the leg test area based on the result data includes: calculating the scoring result of the leg test area based on the result report.
[0008] In one embodiment, the calculation of the scoring result of the leg test area based on the result data includes: calculating the actual score of the single data point to be analyzed based on multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of the single data point to be analyzed; and calculating the scoring result of the leg test area based on the actual scores of all the data points to be analyzed.
[0009] In one embodiment, the actual score of the single data point to be analyzed is calculated based on multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of the single data point to be analyzed, including: selecting the maximum value among the multiple thigh bending moments and the maximum value among the multiple calf bending moments as the thigh bending moment to be evaluated and the calf bending moment to be evaluated, respectively; evaluating the thigh bending moment to be evaluated, the calf bending moment to be evaluated and the knee ligament elongation, respectively, to obtain corresponding thigh bending moment scores, calf bending moment scores and knee ligament elongation scores; and obtaining the actual score of the single data point to be analyzed by weighted summation according to the thigh bending moment score, the calf bending moment score and the knee ligament elongation score.
[0010] In one embodiment, the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation are evaluated respectively to obtain corresponding thigh bending moment scores, calf bending moment scores, and knee ligament elongation scores, including: based on the thigh bending moment to be evaluated, the calf bending moment to be evaluated, the knee ligament elongation and the corresponding high performance limit and low performance limit, linear interpolation is used to calculate the thigh bending moment score, the calf bending moment score, and the knee ligament elongation score; wherein the high performance limit includes the lower limit values of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation, and the low performance limit includes the upper limit values of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation.
[0011] In one embodiment, calculating the scoring result of the leg test area according to the actual scores of all the data points to be analyzed includes: calculating the scoring result of the leg test area according to the average value of the actual scores of all the data points to be analyzed.
[0012] According to another aspect of the present application, a device for processing pedestrian APLI leg collision data is provided, comprising: a data acquisition module, used to acquire data to be processed; wherein the data to be processed is stored in at least one folder; an array division module, used to divide the data to be processed in the same folder into multiple arrays based on the number of data points to be analyzed; wherein all the data points to be analyzed constitute a leg test area; a data calculation module, used to call the leg calculation model to calculate the array corresponding to each data point to be analyzed respectively, and obtain result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; a scoring calculation module, used to calculate the scoring result of the leg test area based on the result data.
[0013] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute any of the above methods.
[0014] According to another aspect of the present application, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; and the processor is used to execute any of the above-described methods.
[0015] The present application provides a method, device, medium and equipment for processing pedestrian APLI leg collision data, which obtains data to be processed; wherein the data to be processed is stored in at least one folder; based on the number of data points to be analyzed, the data to be processed in the same folder is divided into multiple arrays; wherein all the data points to be analyzed constitute a leg test area; the leg calculation model is called to calculate the array corresponding to each data point to be analyzed respectively to obtain result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; the scoring result of the leg test area is calculated based on the result data; that is, the data in a single folder corresponding to the pedestrian APLI leg collision data is divided into multiple arrays, and the model is called for each array to calculate the result data to achieve multi-threaded calculation to improve data calculation efficiency, and the scoring result of the leg test area is calculated according to the result data to achieve automatic acquisition, calculation and evaluation of pedestrian APLI leg collision data, thereby reducing the workload of engineers, improving data processing efficiency, shortening research and development time, and reducing human participation to improve data processing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.
[0017] Figure 1 It is a flowchart of a method for processing pedestrian APLI leg collision data provided by an exemplary embodiment of the present application.
[0018] Figure 2 It is a flowchart of a method for calculating pedestrian APLI leg collision data provided by an exemplary embodiment of the present application.
[0019] Figure 3 It is a schematic diagram of the score report structure of pedestrian APLI leg collision data provided by an exemplary embodiment of the present application.
[0020] Figure 4 It is a schematic diagram of the structure of a device for processing pedestrian APLI leg collision data provided by an exemplary embodiment of the present application.
[0021] Figure 5 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION
[0022] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described here.
[0023] Figure 1 FIG. 1 is a flow chart of a method for processing pedestrian APLI leg collision data provided by an exemplary embodiment of the present application. Figure 1 As shown, the method for processing pedestrian APLI leg collision data includes the following steps: Step 110: Obtain data to be processed.
[0024] The data to be processed is stored in at least one folder. The pedestrian APLI leg simulation model includes two parts: the pedestrian protection simulation model extracted from the whole vehicle model (a folder named INCL) and the pedestrian APLI leg calculation model (a folder starting with L). The pedestrian APLI leg calculation model is stored in multiple folders. After the pedestrian protection simulation model is built, the relative position relationship between the APLI leg and the pedestrian protection simulation model is set by using the keywords in LS-DYNA through the pre-processing software: ANSA, Hyperwork, etc., and the pedestrian APLI leg calculation model is constructed after export. After determining the specific number of points to be analyzed (the number of data points to be analyzed), the data points to be analyzed are the contact points where the pedestrian APLI leg collides with the car. Different contact points can be obtained when the pedestrian APLI leg collides with the car at different positions. Then confirm how many models are needed according to the number of points to be calculated (the number of models to be calculated is equal to the number of points to be calculated). This application uses python and META built-in language to write relevant scripts to extract the data to be processed from multiple folders corresponding to the pedestrian APLI leg calculation model.
[0025] Step 120: Divide the data to be processed in the same folder into multiple arrays based on the number of data points to be analyzed.
[0026] Among them, all the data points to be analyzed constitute the leg test area. This application performs data processing on the data to be processed in the same folder at a time. Specifically, the data to be processed in the same folder is divided into multiple arrays, where the number of arrays corresponds to the number of processes, that is, the data to be processed in the same folder is divided into multiple processes for data processing to improve data processing efficiency, and the data to be processed in a folder is processed at a time to reduce the mutual interference between the data to be processed in different folders.
[0027] Step 130: Call the leg calculation model to calculate the array corresponding to each data point to be analyzed and obtain result data.
[0028] The result data include thigh bending moment, calf bending moment and knee ligament elongation. The leg calculation model can be LS-DYNA software. Figure 2 As shown, the present application calls the leg calculation model to calculate each array separately to obtain the result data of each array.
[0029] Step 140: Calculate the scoring result of the leg test area based on the result data.
[0030] After calculating the result data of the data to be processed in all folders, the scoring results of the leg test area are calculated based on all the result data to realize the automatic processing of pedestrian APLI leg collision data.
[0031] The present application provides a method for processing pedestrian APLI leg collision data, which comprises obtaining data to be processed; wherein the data to be processed is stored in at least one folder; dividing the data to be processed in the same folder into multiple arrays based on the number of data points to be analyzed; wherein all the data points to be analyzed constitute a leg test area; calling a leg calculation model to calculate the array corresponding to each data point to be analyzed respectively to obtain result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; calculating the scoring result of the leg test area based on the result data; that is, dividing the data in a single folder corresponding to the pedestrian APLI leg collision data to obtain multiple arrays, and calling the model to calculate the result data for each array to realize multi-threaded calculation to improve data calculation efficiency, and calculating the scoring result of the leg test area according to the result data to realize automatic acquisition, calculation and evaluation of pedestrian APLI leg collision data, thereby reducing the workload of engineers, improving data processing efficiency, shortening research and development time, and reducing human participation to improve data processing accuracy.
[0032] In one embodiment, the specific implementation method of the above step 130 may be: calling the leg calculation model to calculate the array corresponding to each data point to be analyzed respectively, and periodically monitoring the calculation progress until the result data is obtained.
[0033] like Figure 2 As shown, the present application monitors the calculation progress when calling the leg calculation model to calculate the array corresponding to the data point to be analyzed. Specifically, the present application can periodically determine whether the leg calculation model has completed the calculation (that is, whether the calculation result is obtained). If the calculation is not completed, the monitoring continues; if the calculation is completed, the result data is read.
[0034] In one embodiment, after step 130, the above-mentioned pedestrian APLI leg collision data processing method may further include: calculating a result report of the leg test area according to the result data corresponding to all the data points to be analyzed; wherein the result report includes a plurality of thigh bending moments, a plurality of calf bending moments and a knee ligament elongation for each data point to be analyzed; correspondingly, the specific implementation method of step 140 may be: calculating the scoring result of the leg test area based on the result report.
[0035] like Figure 2 As shown, after calculating the result data corresponding to each data point to be analyzed, the present application calculates the result report of the leg test area based on the result data corresponding to all the data points to be analyzed. Specifically, Figure 3 As shown, the result report includes multiple thigh bending moments (for example, 3), multiple calf bending moments (for example, 4) and a knee ligament elongation for each data point to be analyzed (corresponding to different car collision positions and leg contact points). After the result report of the leg test area is calculated, the scoring result of the leg test area is calculated based on the result report.
[0036] In one embodiment, the specific implementation method of the above step 140 can be: based on multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of a single data point to be analyzed, calculate the actual score of the single data point to be analyzed; based on the actual scores of all data points to be analyzed, calculate the scoring result of the leg test area.
[0037] After calculating multiple thigh bending moments, multiple calf bending moments and one knee ligament extension of a single data point to be analyzed, the present application calculates the actual score of the single data point to be analyzed based on the multiple thigh bending moments, multiple calf bending moments and one knee ligament extension of the single data point to be analyzed, and after calculating the actual scores of all the data points to be analyzed, based on the actual scores of all the data points to be analyzed, comprehensively calculates the scoring result of the leg test area composed of all the data points to be analyzed.
[0038] In one embodiment, the specific implementation method of the above-mentioned step 140 can be: selecting the maximum value among multiple thigh bending moments and the maximum value among multiple calf bending moments as the thigh bending moment to be evaluated and the calf bending moment to be evaluated, respectively; evaluating the thigh bending moment to be evaluated, the calf bending moment to be evaluated and the knee ligament elongation, respectively, to obtain the corresponding thigh bending moment score, calf bending moment score and knee ligament elongation score; according to the thigh bending moment score, the calf bending moment score and the knee ligament elongation score, weighted summation is performed to obtain the actual score of the single data point to be analyzed.
[0039] After calculating multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of a single data point to be analyzed, the present application selects the maximum value of multiple thigh bending moments as the thigh bending moment to be evaluated, and the maximum value of multiple calf bending moments as the calf bending moment to be evaluated, and combines the knee ligament elongation to evaluate the thigh bending moment to be evaluated, the calf bending moment to be evaluated and the knee ligament elongation, respectively, to obtain the corresponding thigh bending moment score, calf bending moment score and knee ligament elongation score, and weighted sum the thigh bending moment score, calf bending moment score and knee ligament elongation score to obtain the actual score of the corresponding single data point to be analyzed. For example, the present application can set the weights of the thigh bending moment score, the calf bending moment score and the knee ligament elongation score to 0.4, 0.4 and 0.2 respectively, that is, the actual score of the corresponding single data point to be analyzed = thigh bending moment score * 0.4 + calf bending moment score * 0.4 + knee ligament elongation score * 0.2.
[0040] In one embodiment, the specific implementation method of the above step 140 can be: based on the thigh bending moment to be evaluated, the calf bending moment to be evaluated, the knee ligament elongation and the corresponding high performance limit and low performance limit, linear interpolation is used to calculate the thigh bending moment score, the calf bending moment score and the knee ligament elongation score; wherein the high performance limit includes the lower limit value of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation, and the low performance limit includes the upper limit value of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation.
[0041] After determining the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation, this application evaluates the thigh bending moment score, calf bending moment score, and knee ligament elongation score of each data point to be analyzed according to the limit values of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation required by the regulations. Specifically, this application sets the lower limit value (high performance limit value) and upper limit value (low performance limit value) of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation, among which the high performance limit value is: thigh bending moment 390Nm, calf bending moment 275Nm, knee ligament elongation (Medial Collateral Ligament, MCL for short) 27mm, and the low performance limit value is: thigh bending moment 440Nm, calf bending moment 320Nm, knee ligament elongation 32mm. This application uses linear interpolation to calculate the scores of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation between the high performance limit and the low performance limit. Specifically, a score less than or equal to the high performance limit is 1 (for example, when the thigh bending moment to be evaluated is less than or equal to 390Nm, the thigh bending moment score is 1), and a score greater than or equal to the low performance limit is 0 (for example, when the thigh bending moment to be evaluated is greater than or equal to 440Nm, the thigh bending moment score is 0), and the score between the high performance limit and the low performance limit is calculated as follows: Thigh bending moment score = (Low performance limit of thigh bending moment to be evaluated - thigh bending moment to be evaluated) / (Low performance limit of thigh bending moment to be evaluated - High performance limit of thigh bending moment to be evaluated), calf bending moment score = (Low performance limit of calf bending moment to be evaluated - calf bending moment to be evaluated) / (Low performance limit of calf bending moment to be evaluated - High performance limit of calf bending moment to be evaluated), knee ligament extension score = (Low performance limit of knee ligament extension - knee ligament extension) / (Low performance limit of knee ligament extension - High performance limit of knee ligament extension).
[0042] In one embodiment, the specific implementation of the above step 140 may be: calculating the scoring result of the leg test area according to the average value of the actual scores of all the data points to be analyzed.
[0043] After calculating the actual scores of all the data points to be analyzed, the application calculates the average of the actual scores of all the data points to be analyzed to obtain the scoring result of the leg test area, wherein the specific calculation formula of the scoring result of the leg test area is as follows: Score = ×5.
[0044] The specific calculation results are as follows: Figure 3 As shown, this application takes four data points to be analyzed, L0, L100, L200 and L300, as an example, wherein the score of each data point to be analyzed is 1, and the score result of the leg test area formed by the four data points to be analyzed is 5 points (the highest score).
[0045] Figure 4 FIG. 1 is a schematic diagram of a device for processing pedestrian APLI leg collision data provided by an exemplary embodiment of the present application. Figure 4 As shown, the pedestrian APLI leg collision data processing device 40 includes: a data acquisition module 41, used to acquire the data to be processed; wherein the data to be processed is stored in at least one folder; an array division module 42, used to divide the data to be processed in the same folder into multiple arrays based on the number of data points to be analyzed; wherein all the data points to be analyzed constitute a leg test area; a data calculation module 43, used to call the leg calculation model to calculate the array corresponding to each data point to be analyzed respectively, and obtain result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; a score calculation module 44, used to calculate the score result of the leg test area based on the result data.
[0046] The present application provides a processing device for pedestrian APLI leg collision data, which obtains the data to be processed through a data acquisition module 41; wherein the data to be processed is stored in at least one folder; the array division module 42 divides the data to be processed in the same folder into multiple arrays based on the number of data points to be analyzed; wherein all the data points to be analyzed constitute a leg test area; the data calculation module 43 calls the leg calculation model to calculate the array corresponding to each data point to be analyzed respectively to obtain result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; the scoring calculation module 44 calculates the scoring result of the leg test area based on the result data; that is, the data in a single folder corresponding to the pedestrian APLI leg collision data is divided into multiple arrays, and the model is called for each array to calculate the result data, so as to realize multi-threaded calculation to improve data calculation efficiency, and the scoring result of the leg test area is calculated according to the result data, so as to realize the automatic acquisition, calculation and evaluation of the pedestrian APLI leg collision data, thereby reducing the workload of engineers, improving data processing efficiency, shortening research and development time, and reducing human participation to improve the accuracy of data processing.
[0047] In one embodiment, the data calculation module 43 may be further configured to: call the leg calculation model to calculate the array corresponding to each data point to be analyzed, and periodically monitor the calculation progress until the result data is obtained.
[0048] In one embodiment, the pedestrian APLI leg collision data processing device 40 can be further configured to: calculate the result report of the leg test area according to the result data corresponding to all the data points to be analyzed; wherein the result report includes multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation for each data point to be analyzed; correspondingly, the score calculation module 44 can be further configured to: calculate the score result of the leg test area based on the result report.
[0049] In one embodiment, the above-mentioned scoring calculation module 44 can be further configured as: according to multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of a single data point to be analyzed, the actual score of the single data point to be analyzed is calculated; according to the actual scores of all data points to be analyzed, the scoring result of the leg test area is calculated.
[0050] In one embodiment, the scoring calculation module 44 can be further configured as follows: selecting the maximum value among multiple thigh bending moments and the maximum value among multiple calf bending moments as the thigh bending moment to be evaluated and the calf bending moment to be evaluated, respectively; evaluating the thigh bending moment to be evaluated, the calf bending moment to be evaluated and the knee ligament elongation, respectively, to obtain the corresponding thigh bending moment score, calf bending moment score and knee ligament elongation score; and performing weighted summation according to the thigh bending moment score, the calf bending moment score and the knee ligament elongation score to obtain the actual score of the single data point to be analyzed.
[0051] In one embodiment, the scoring calculation module 44 can be further configured as follows: based on the thigh bending moment to be evaluated, the calf bending moment to be evaluated, the knee ligament elongation and the corresponding high performance limit and low performance limit, a thigh bending moment score, a calf bending moment score and a knee ligament elongation score are obtained by linear interpolation calculation; wherein the high performance limit includes the lower limit of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation, and the low performance limit includes the upper limit of the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation.
[0052] In one embodiment, the score calculation module 44 may be further configured to calculate the score result of the leg test area according to the average value of the actual scores of all the data points to be analyzed.
[0053] Below, reference Figure 5 The electronic device according to the embodiment of the present application is described. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the collected input signal from them.
[0054] Figure 5 A block diagram of an electronic device according to an embodiment of the present application is illustrated.
[0055] like Figure 5 As shown, the electronic device 10 includes one or more processors 11 and a memory 12 .
[0056] The processor 11 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.
[0057] The memory 12 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage medium.
[0058] In one example, the electronic device 10 may further include: an input device 13 and an output device 14 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).
[0059] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector, which is used to receive the collected input signals from the first device and the second device.
[0060] In addition, the input device 13 may also include, for example, a keyboard, a mouse, and the like.
[0061] The output device 14 can output various information to the outside, including the determined distance information, direction information, etc. The output device 14 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.
[0062] Of course, to simplify, Figure 5 Only some of the components related to the present application in the electronic device 10 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device 10 may also include any other appropriate components.
[0063] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present application described in the above-mentioned "Exemplary Method" section of this specification.
[0064] The computer program product may be written in any combination of one or more programming languages to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0065] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the method according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.
[0066] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.
[0067] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.
[0068] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.
[0069] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.
[0070] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
[0071] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.
Claims
1. A method for processing pedestrian APLI leg collision data, characterized in that: include: Acquire data to be processed; wherein the data to be processed is stored in at least one folder; Based on the number of data points to be analyzed, the data to be processed in the same folder are divided into multiple arrays; wherein all the data points to be analyzed constitute a leg test area; Calling the leg calculation model to calculate the array corresponding to each of the data points to be analyzed, and obtaining result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; A scoring result for the leg test area is calculated based on the result data.
2. The method for processing pedestrian APLI leg collision data according to claim 1, characterized in that: The calling of the leg calculation model to respectively calculate the array corresponding to each of the data points to be analyzed, and obtaining the result data includes: The leg calculation model is called to respectively calculate the array corresponding to each of the data points to be analyzed, and the calculation progress is periodically monitored until the result data is obtained.
3. The method for processing pedestrian APLI leg collision data according to claim 1, characterized in that: After the leg calculation model is called to calculate the array corresponding to each of the data points to be analyzed and the result data is obtained, the method for processing pedestrian APLI leg collision data further includes: Calculate the result report of the leg test area according to the result data corresponding to all the data points to be analyzed; wherein the result report includes a plurality of thigh bending moments, a plurality of calf bending moments and a knee ligament elongation for each data point to be analyzed; The step of calculating the score result of the leg test area based on the result data includes: A scoring result for the leg test area is calculated based on the result report.
4. The method for processing pedestrian APLI leg collision data according to claim 3, characterized in that: The step of calculating the score result of the leg test area based on the result data includes: Calculate the actual score of the single data point to be analyzed based on multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of the single data point to be analyzed; The scoring result of the leg test area is calculated based on the actual scores of all the data points to be analyzed.
5. The method for processing pedestrian APLI leg collision data according to claim 4, characterized in that: The actual score of the single data point to be analyzed is calculated based on multiple thigh bending moments, multiple calf bending moments and a knee ligament elongation of the single data point to be analyzed, including: Selecting a maximum value among the multiple thigh bending moments and a maximum value among the multiple calf bending moments as the thigh bending moment to be evaluated and the calf bending moment to be evaluated, respectively; The thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation are evaluated respectively to obtain corresponding thigh bending moment scores, calf bending moment scores, and knee ligament elongation scores; The actual score of the single data point to be analyzed is obtained by weighted summation according to the thigh bending moment score, the calf bending moment score and the knee ligament elongation score.
6. The method for processing pedestrian APLI leg collision data according to claim 5, characterized in that: The step of evaluating the thigh bending moment to be evaluated, the calf bending moment to be evaluated, and the knee ligament elongation respectively to obtain the corresponding thigh bending moment score, calf bending moment score, and knee ligament elongation score comprises: Based on the thigh bending moment to be evaluated, the calf bending moment to be evaluated, the knee ligament elongation and the corresponding high performance limit and low performance limit, linear interpolation is used to calculate the thigh bending moment score, the calf bending moment score and the knee ligament elongation score; wherein the high performance limit includes the lower limit values of the thigh bending moment to be evaluated, the calf bending moment to be evaluated and the knee ligament elongation, and the low performance limit includes the upper limit values of the thigh bending moment to be evaluated, the calf bending moment to be evaluated and the knee ligament elongation.
7. The method for processing pedestrian APLI leg collision data according to claim 4, characterized in that: The scoring result of the leg test area is calculated based on the actual scores of all the data points to be analyzed, including: The scoring result of the leg test area is calculated based on the average of the actual scores of all the data points to be analyzed.
8. A device for processing pedestrian APLI leg collision data, characterized in that: include: A data acquisition module, used to acquire data to be processed; wherein the data to be processed is stored in at least one folder; An array division module, used for dividing the data to be processed in the same folder into multiple arrays based on the number of data points to be analyzed; wherein all the data points to be analyzed constitute a leg test area; A data calculation module, used for calling the leg calculation model to respectively calculate the array corresponding to each of the data points to be analyzed, and obtain result data; wherein the result data includes thigh bending moment, calf bending moment and knee ligament elongation; A scoring calculation module is used to calculate the scoring result of the leg test area based on the result data.
9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.
10. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is used to execute the method described in any one of claims 1 to 7.