A bumper deformation test data analysis method and system

Abstract

The application provides a bumper deformation test data analysis method and system, and relates to the automobile manufacturing detection technical field. First, a plurality of scene bumper deformation test data sets are acquired, including static and dynamic test data and corresponding environment and external force parameters. Then, a bumper deformation propagation path model is constructed to determine the deformation starting position, propagation direction and rate. Then, bumper deformation influence factor coupling analysis under multiple scenes is performed to screen core influence factors and analyze their interaction. Based on the analysis results, the bumper dynamic deformation threshold is calibrated. Finally, the above results are integrated to generate a comprehensive analysis report containing deformation propagation law, influence factor action mechanism and dynamic threshold standard. The application can comprehensively and deeply analyze the bumper deformation and improve the safety evaluation accuracy.

Description

Technical Field

[0001] This invention relates to the field of automotive manufacturing testing technology, and more specifically, to a method and system for analyzing bumper deformation test data. Background Technology

[0002] In the automotive manufacturing industry, bumpers are crucial safety components, and their deformation characteristics directly affect a vehicle's safety performance in collisions and other accidents. To ensure the quality and performance of bumpers, deformation testing is necessary, and the test data must be analyzed.

[0003] Currently, traditional methods for analyzing bumper deformation test data have several limitations. Firstly, the test scenarios are relatively limited, typically focusing only on static or simple dynamic scenarios. This makes it difficult to comprehensively simulate the various complex situations a bumper might encounter in actual use, such as collisions at different speeds and angles, and stress under different environmental conditions. Consequently, the test results cannot accurately reflect the true deformation characteristics of the bumper. Secondly, existing methods often view individual test data in isolation during data analysis, lacking in-depth research on the deformation propagation path and failing to clearly understand key information such as the starting position, propagation direction, and rate of deformation on the bumper surface. Furthermore, there is a lack of effective coupling analysis for the various factors affecting bumper deformation, making it difficult to accurately determine which factors are the core influencing factors and their interactions. Consequently, it is impossible to reasonably calibrate the dynamic deformation threshold of the bumper, resulting in an inaccurate and incomplete safety assessment of bumper deformation. Summary of the Invention

[0004] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, an embodiment of the present invention provides a method for analyzing bumper deformation test data, the method comprising: A multi-scenario bumper deformation test data set is obtained, which includes bumper deformation data under static test scenarios and bumper deformation data under dynamic test scenarios, as well as environmental parameter data and external force parameter data corresponding to the test scenarios. Based on the multi-scenario bumper deformation test data set, a bumper deformation propagation path model is constructed. The deformation time sequence features in the static and dynamic test data of the multi-scenario bumper deformation test data set are extracted to determine the starting position, propagation direction and propagation rate of the deformation on the bumper surface, thus forming the bumper deformation propagation path model. Based on the bumper deformation propagation path model, a coupling analysis of the influencing factors of bumper deformation under multiple scenarios is conducted. The core influencing factors affecting the deformation propagation rate are screened, and the interaction between different core influencing factors is analyzed to obtain the coupling analysis results of the influencing factors of bumper deformation under multiple scenarios. Based on the coupling analysis results of the multi-scenario bumper deformation influencing factors, the dynamic deformation threshold of the bumper is calibrated. Combined with the rate change characteristics of the deformation propagation path in the bumper deformation propagation path model, the range of the safe threshold for bumper deformation under different scenarios is adjusted to generate the calibrated dynamic deformation threshold of the bumper. By integrating the aforementioned bumper deformation propagation path model, the results of multi-scenario bumper deformation influencing factor coupling analysis, and the calibrated bumper dynamic deformation threshold, a comprehensive analysis report on bumper deformation testing is generated, which includes the deformation propagation law, the mechanism of action of influencing factors, and the dynamic threshold standard.

[0005] In another aspect, embodiments of the present invention also provide a bumper deformation test data analysis system, including a processor and a machine-readable storage medium connected to the processor. The machine-readable storage medium is used to store programs, instructions, or code, and the processor is used to execute the programs, instructions, or code in the machine-readable storage medium to implement the above-described method.

[0006] Based on the above, by acquiring a multi-scenario bumper deformation test dataset, covering deformation data and corresponding environmental and external force parameters under both static and dynamic test scenarios, it is possible to more realistically simulate the complex working conditions of bumpers in actual use. Then, based on this multi-scenario bumper deformation test dataset, a bumper deformation propagation path model is constructed. This model accurately extracts deformation timing characteristics, determines the starting position, propagation direction, and propagation rate of deformation on the bumper surface, and presents the deformation propagation path. Next, a coupling analysis of bumper deformation influencing factors under multiple scenarios is performed. This allows for the identification of core influencing factors affecting the deformation propagation rate and analysis of their interactions. Based on the coupling analysis results, the dynamic deformation threshold of the bumper is calibrated, and the safety threshold range under different scenarios is adjusted in conjunction with the rate change characteristics of the deformation propagation path. The final comprehensive analysis report of bumper deformation testing integrates deformation propagation laws, influencing factor mechanisms, and dynamic threshold standards, contributing to improved vehicle safety performance and reliability. Attached Figure Description

[0007] Figure 1 This is a schematic diagram of the execution flow of the bumper deformation test data analysis method provided in an embodiment of the present invention.

[0008] Figure 2 This is a schematic diagram of exemplary hardware and software components of the bumper deformation test data analysis system provided in an embodiment of the present invention. Detailed Implementation

[0009] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1This is a flowchart illustrating a method for analyzing bumper deformation test data according to an embodiment of the present invention. The following is a detailed description of this method for analyzing bumper deformation test data.

[0010] Step S110: Obtain a multi-scenario bumper deformation test data set, which includes bumper deformation data under static test scenarios and bumper deformation data under dynamic test scenarios, as well as environmental parameter data and external force parameter data corresponding to the test scenarios.

[0011] In this embodiment, the front bumper of a family sedan is used as the test object to acquire deformation test data in multiple scenarios. The front bumper is made of polypropylene composite material, and its surface is divided into multiple test areas. During the test, a laser displacement sensor is used to collect deformation data, a force sensor is used to collect external force parameters, and a thermometer, hygrometer, and barometer are used to collect environmental parameters. All data is stored in the test system database in real time, and each data entry contains a unique identifier to trace the original test record.

[0012] Step S111: Divide the bumper deformation test scenario types into static test scenarios and dynamic test scenarios. Static test scenarios are test scenarios in which a constant external force is continuously applied, while dynamic test scenarios are test scenarios in which an instantaneous impact external force is applied.

[0013] In this embodiment, the criteria for classifying test scenarios are first clarified. A static test scenario is defined as follows: a servo motor drives a loading device to continuously apply constant pressure to a specific area on the bumper surface, with the external force acting for a duration not less than a preset time (e.g., a specific number of minutes), simulating a vehicle's low-speed continuous collision or prolonged compression. A dynamic test scenario is defined as follows: using a drop hammer impact testing machine, by adjusting the mass and drop height of the drop hammer, an instantaneous impact force is applied to a specific area on the bumper surface, with the impact duration not exceeding a preset time (e.g., a specific number of milliseconds), simulating a sudden collision while the vehicle is traveling at high speed. The testing system automatically switches control modes according to the scenario type: a constant force control module is activated for static scenarios, and an impact control module is activated for dynamic scenarios.

[0014] Step S112: Extract bumper deformation data from the static test scenario. Collect bumper deformation degree data corresponding to different external force application positions and deformation accumulation data corresponding to the duration of external force holding in the static test scenario. Organize the bumper deformation degree data corresponding to different external force application positions and deformation accumulation data corresponding to the duration of external force holding in the static test scenario into a static test data subset. The static test data subset includes data corresponding to the external force application position and deformation degree and data corresponding to the external force holding time and deformation accumulation.

[0015] In this embodiment, the deformation data extraction for the static test scenario needs to be combined with preset parameters for the location and duration of the applied external force. Before the test, technicians marked six areas for the application of external force on the 3D model of the bumper: the left corner area, the left center area, the center area, the right center area, the right corner area, and the lower edge area. Each area corresponds to a specific coordinate range. When a constant external force is applied to each area, the laser displacement sensor array collects the deformation of the center point and five surrounding feature points of that area at preset time intervals (such as a specific number of seconds), forming deformation degree data. At the same time, a timer records the duration of the continuous application of the external force, accumulating the total deformation at each time point to form cumulative deformation data.

[0016] Step S1121: Determine the type of external force application location in the static test scenario, divide the bumper surface into multiple preset areas, each preset area is a type of external force application location, and record the coordinate range data of each type of external force application location.

[0017] In this embodiment, the classification of external force application location types is based on the structural characteristics of the bumper. Taking the front bumper as an example, it is divided into 5 equal-width longitudinal regions from left to right along the horizontal direction, and 3 equal-width transverse regions from top to bottom along the vertical direction, intersecting to form 15 rectangular sub-regions. Each sub-region represents an external force application location type. The coordinate range of each location type is described by a three-dimensional coordinate system. For example, the coordinate range of the left corner region is a specific interval on the X-axis, a specific interval on the Y-axis, and a specific interval on the Z-axis (the Z-axis is the direction of the bumper thickness). This coordinate range data is stored in the position parameter library of the test system for use during data acquisition.

[0018] Step S1122: For each type of external force application, apply a constant magnitude external force. During the application of the constant magnitude external force, collect the bumper deformation data corresponding to the type of external force application at preset time intervals. The deformation data is the deformation value of the bumper at the position corresponding to the type of external force application, forming the original data of external force application position-deformation degree for each type of external force application.

[0019] In this embodiment, a constant external force is applied to the left-middle region (coordinate range X1 to X2, Y1 to Y2, Z0). The testing system adjusts the loading device in real time through force sensor feedback to ensure that the magnitude of the external force is stable within a preset value (such as a specific force range). During the application process, the laser displacement sensor collects the deformation of the center point (coordinates X0, Y0, Z0) of the left-middle region at a frequency of 10Hz. Each collection moment corresponds to a deformation degree data. After continuous collection for a specific number of minutes, a raw data sequence containing timestamps, position coordinates, and deformation is formed, for example, "timestamp T1, position (X0, Y0, Z0), deformation D1; timestamp T2, position (X0, Y0, Z0), deformation D2...", which is stored as a CSV file named "static-left-middle-raw data.csv".

[0020] Step S1123: Organize the original data of the external force application location and deformation degree, remove abnormal values ​​that appear during the collection process. Abnormal values ​​are values ​​whose differences from the values ​​collected in adjacent time intervals exceed a preset difference threshold. Classify the organized values ​​according to the type of external force application location to form data corresponding to the external force application location and deformation degree.

[0021] In this embodiment, the data in "Static-Left Middle-Original Data.csv" is organized. A sliding window method is used to identify outliers. The window size is set to 5 consecutive data points. The mean and standard deviation of the data within the window are calculated. If the difference between a data point and the mean exceeds 3 times the standard deviation (a preset difference threshold), it is determined to be an outlier. For example, if the deformation D5 corresponding to timestamp T5 differs from the preceding and following data points D4 and D6 beyond the threshold, D5 is marked as an outlier and removed. The organized valid data is rearranged in the format of "Location Type-Timestamp-Deformation" to form data corresponding to the location of external force application and the degree of deformation, stored as "Static-Left Middle-Deformation Degree.csv", where the data corresponding to the left middle region contains a specific number of valid deformation records.

[0022] Step S1124: For each type of external force application location, maintain a constant external force and continuously apply it. During the process of maintaining a constant external force, collect the bumper deformation accumulation data corresponding to the external force application location type at preset time intervals. The deformation accumulation data is the total deformation value from the start of the external force application to the current time point, forming the original data of external force holding time - deformation accumulation corresponding to each type of external force application location.

[0023] In this embodiment, during the continuous application of a constant external force to the left-middle region, in addition to collecting real-time deformation data, cumulative deformation data is calculated simultaneously. Starting from the initial moment of the application of the external force (timestamp T0), the cumulative deformation at each collection moment is the sum of the real-time deformation at that moment and the cumulative deformation at the previous moment (if plastic deformation exists, the irreversible deformation component needs to be superimposed). For example, the cumulative deformation at timestamp T1 is D1, the cumulative deformation at T2 is D1 + (D2 - D1) = D2 (when elastic deformation is dominant), and if plastic deformation occurs at T3, D3 = D2 + ΔD (ΔD is the newly added plastic deformation), forming an original data sequence containing timestamps, cumulative duration (current timestamp - T0), and cumulative deformation, which is stored as "static-left-middle-cumulative original data.csv".

[0024] Step S1125: Organize the original data of external force holding time - deformation accumulation, remove abnormal values. Abnormal values ​​are values ​​that do not conform to the preset deformation accumulation law. Classify the organized values ​​according to the type of external force application location to form corresponding data of external force holding time - deformation accumulation.

[0025] In this embodiment, the preset deformation accumulation rule is that "the cumulative deformation increases monotonically with time, and the rate of increase gradually slows down." The data in "static-left-middle-cumulative raw data.csv" is checked. If the cumulative deformation at a certain timestamp is less than the previous time (in non-recovery deformation scenarios), or if the rate of increase suddenly exceeds a preset range (e.g., the rate of increase increases by a specific percentage compared to the previous stage), it is determined to be an outlier. For example, if the cumulative deformation at timestamp T10 is less than T9, and the system does not detect any external force unloading operation, it is determined to be an outlier and removed. The processed cumulative data is stored in the format "location type-cumulative duration-cumulative deformation" as "static-left-middle-cumulative data.csv", which, together with the deformation degree data, constitutes the basic data of the static test data subset.

[0026] Step S113: Extract bumper deformation data from the dynamic test scenario. Collect instantaneous change data of bumper deformation corresponding to different impact forces and deformation recovery data corresponding to impact frequencies under the dynamic test scenario. Organize the instantaneous change data of bumper deformation corresponding to different impact forces and deformation recovery data corresponding to impact frequencies under the dynamic test scenario into a dynamic test data subset. The dynamic test data subset includes data corresponding to impact force-instantaneous change of deformation and data corresponding to impact frequency-deformation recovery.

[0027] In this embodiment, the deformation data extraction for the dynamic test scenario focuses on the changes at the moment of impact and the subsequent recovery process. The test object remains the left-center area of ​​the front bumper. A drop hammer impact tester is used to apply different impact forces (achieved by adjusting the drop hammer height). A high-speed camera (with a specific frame rate) records the deformation process at the moment of impact, and a laser displacement sensor collects deformation data at higher time intervals (such as a specific number of milliseconds) to form instantaneous change data. At the same time, the impact frequency (the number of impacts per unit time) is controlled, and the amount of deformation recovery of the bumper after each impact is monitored to form recovery data.

[0028] Step S114: Collect environmental parameter data for the corresponding test scenario. Collect air temperature data, air humidity data, and ambient air pressure data during the test process in both static and dynamic test scenarios. Associate the environmental parameter data of the static test scenario with the static test data subset, and associate the environmental parameter data of the dynamic test scenario with the dynamic test data subset to form a static test data subset with environmental parameters and a dynamic test data subset with environmental parameters.

[0029] In this embodiment, environmental parameters are collected using a thermometer / hygrometer and a barometer deployed within the test chamber, with the sampling interval consistent with the deformation data. During static testing, the thermometer / hygrometer records the temperature (in degrees Celsius) and humidity (in percentage) at each deformation data collection moment, while the barometer records the ambient air pressure (in kilopascals). During dynamic testing, because the impact duration is short, the environmental parameters are considered constant during a single impact, and the environmental parameters at the start of the impact are recorded. The testing system associates the environmental parameters with the deformation data using timestamps. For example, in static testing, temperature, humidity, and air pressure fields are added to each record in the file "static-left-middle-deformation degree.csv", forming a subset of static test data with environmental parameters, and the file is named "static-left-middle-deformation degree-environment.csv".

[0030] Step S115: Collect external force parameter data for the corresponding test scenario. In the static test scenario, collect the magnitude data of the constant external force and the area of ​​the external force. In the dynamic test scenario, collect the peak value data of the instantaneous impact force and the impact time data. Associate the external force parameter data of the static test scenario with the subset of static test data with environmental parameters, and associate the external force parameter data of the dynamic test scenario with the subset of dynamic test data with environmental parameters.

[0031] In this embodiment, the external force parameters for static testing are acquired using a force sensor and a pressure distribution testing membrane. The force sensor monitors and records the magnitude of the constant external force (in Newtons) in real time, while the pressure distribution testing membrane covers the left-middle region and measures the area of ​​the external force application (in square meters). During dynamic testing, the force sensor acquires the force value change curve during the impact process, extracts the peak value of the curve (impact peak data, in Newtons), and determines the impact time (in milliseconds) by the time difference between the rising and falling edges of the curve. The testing system adds these parameters as metadata to the corresponding data subset. For example, the static test data subset with environmental parameters adds "external force magnitude" and "application area" fields, forming "static-left-middle-deformation-environment-external force.csv".

[0032] Step S116: Integrate the static test data subset with environmental parameters and external force parameters and the dynamic test data subset with environmental parameters and external force parameters to form a multi-scenario bumper deformation test data set. Each data entry in the multi-scenario bumper deformation test data set includes a test scenario type identifier, deformation data, environmental parameter data, and external force parameter data.

[0033] In this embodiment, the integration of multi-scenario data sets is achieved through database association. A "Multi-Scenario Test Data" table is created in the test system database. Fields include scenario type identifier (static / dynamic), location type, timestamp, deformation degree, cumulative deformation, temperature, humidity, air pressure, external force magnitude, impact area (static) / peak impact, and impact time (dynamic). Static data subsets with environmental and external force parameters (e.g., data from the left-middle region) and dynamic data subsets (e.g., impact data from the left-middle region) are written into this table one by one. Each record is uniquely identified using a unique identifier (scenario type + location type + timestamp). The final multi-scenario data set contains test data for six location types of static scenarios and six location types of dynamic scenarios, with a total number of records reaching a certain order of magnitude.

[0034] Step S120: Construct a bumper deformation propagation path model based on the multi-scenario bumper deformation test data set, extract the deformation timing features from the static and dynamic test data in the multi-scenario bumper deformation test data set, determine the starting position, propagation direction and propagation rate of the deformation on the bumper surface, and form a bumper deformation propagation path model.

[0035] In this embodiment, the construction of the deformation propagation path model requires integrating the temporal characteristics of static and dynamic test data. By extracting the starting position, propagation direction, and rate parameters, the entire process of deformation from occurrence to diffusion is simulated on the 3D model of the bumper. The test object remains the front bumper, and the model construction process relies on deformation data of various location types and associated environmental and external force parameters from a multi-scene dataset.

[0036] Step S121: Extract deformation start position data from the static test data subset of the multi-scenario bumper deformation test data set. The deformation start position data is the position coordinate data of the bumper when the external force is first applied in the static test scenario. Mark the position coordinate data of the bumper when the external force is first applied in the static test scenario on the three-dimensional structure model of the bumper to obtain the static deformation start position annotation set.

[0037] In this embodiment, the deformation initiation position extraction of the static test data subset requires locating the first position where significant deformation occurs after the application of external force. Taking the static test data of the left-middle region as an example, the first 5 data points after the starting time of the external force application (timestamp T0) are selected from "static-left-middle-deformation degree-environment-external force.csv". The deformation of each feature point is calculated, and the coordinates of the feature point where the deformation first exceeds the preset minimum deformation threshold (such as the material elastic deformation threshold) are determined as the starting position. For example, if the deformation of the center point (X0, Y0, Z0) of the left-middle region reaches the threshold at T0 + a specific number of seconds, this coordinate is taken as the static deformation initiation position. The starting position coordinates of all static test scenarios (such as one starting coordinate for each of the 6 position types) are imported into the 3D structure model of the bumper (using STL format). Red markers are added to the corresponding coordinate points using the model annotation tool to form a static deformation initiation position annotation set, which is stored as "static initiation position annotation.json" and contains the marker ID, coordinates and corresponding scene information.

[0038] Step S122: Extract deformation start position data from the dynamic test data subset of the multi-scenario bumper deformation test data set. The deformation start position data is the position coordinate data of the earliest deformation of the bumper when subjected to impact force in the dynamic test scenario. Mark the position coordinate data of the earliest deformation of the bumper when subjected to impact force in the dynamic test scenario on the three-dimensional structural model of the bumper to obtain the dynamic deformation start position annotation set.

[0039] In this embodiment, the extraction of the deformation initiation position in dynamic testing relies on the synchronous recording of high-speed camera data and displacement sensors. During the impact test in the left-middle region, the image sequence captured by the high-speed camera shows that within a specific number of milliseconds after the impact, the feature point (X0, Y0, Z0 + a specific offset) directly below the impact point first exhibits pixel displacement. Simultaneously, the laser displacement sensor data shows that the deformation at this point exceeds the dynamic deformation threshold (higher than the static threshold) at the same moment. The coordinates of this feature point are determined as the dynamic deformation initiation position. Similarly, the starting coordinates of the six dynamic test positions are marked on the 3D model, and blue marker points are added to form a dynamic deformation initiation position annotation set, stored as "dynamic initiation position annotation.json", which, together with the static annotation set, constitutes the starting point data of the model.

[0040] Step S123: Integrate the static deformation start position annotation set and the dynamic deformation start position annotation set, analyze the distribution characteristics of deformation start positions under different test scenarios, extract the common features of deformation start positions, and form a bumper deformation propagation start point feature set.

[0041] In this embodiment, the marker points in "Static Starting Position Labels.json" and "Dynamic Starting Position Labels.json" are imported into the 3D model analysis software. A clustering algorithm is used to classify all starting position coordinates, revealing that the starting positions in static scenes are concentrated in the center and edge transition zones of each applied area, while the starting positions in dynamic scenes are concentrated directly below the impact point and along the extension line of the impact direction. Common characteristics include: the starting positions are all located in areas directly affected by external forces or in areas with low structural stiffness (e.g., the proportion of starting positions in corner areas is higher than in the central area). These distribution characteristics and common patterns are extracted to form a feature set of the starting point of bumper deformation propagation, containing parameters such as cluster center coordinates, regional stiffness correlation, and scene type distribution ratio, stored as "Starting Point Feature Set.xlsx" as the basic features for model input.

[0042] Step S124: Extract deformation time series data from the static test data subset. The deformation time series data is the deformation degree data of each position of the bumper corresponding to different time nodes in the static test scenario. Based on the deformation degree data of each position of the bumper corresponding to different time nodes in the static test scenario, calculate the change in deformation degree between adjacent time nodes, determine the direction of deformation diffusion from the starting position to other positions, and obtain the set of static deformation propagation directions.

[0043] In this embodiment, determining the direction of static deformation propagation requires analyzing the spatial diffusion of deformation over time. Taking the static test in the left-middle region as an example, deformation degree data for all location types within a specific time period (a specific number of minutes after the application of external force) are extracted from the static test data subset to form a three-dimensional data matrix of time node-location-deformation. Based on this, the deformation change at adjacent time nodes is calculated, thereby determining the propagation direction.

[0044] Step S1241: Extract the corresponding data of external force application location and deformation degree for each type of external force application location from the static test data subset. The data of external force application location and deformation degree includes multiple time nodes and the deformation degree data of each position of the bumper corresponding to each time node.

[0045] In this embodiment, the data corresponding to the location of external force application and the degree of deformation in the left-middle region are extracted from "static-left-middle-deformation-environment-external force.csv". At the same time, the corresponding data of adjacent locations (left corner region, middle region) are retrieved. The above data includes timestamps (such as T0 to T100) and the deformation of feature points in each region under each timestamp. For example, at time T5, the deformation of the left-middle region is D5-left-middle, the left corner region is D5-left-turn, and the middle region is D5-middle, forming a multi-location temporal deformation data matrix.

[0046] Step S1242: Associate the deformation data of each position of the bumper corresponding to each time node with the coordinate data of the three-dimensional structural model of the bumper, and mark the deformation value of each position of each time node on the three-dimensional structural model of the bumper to form a time node-deformation annotation model sequence.

[0047] In this embodiment, the 3D structural model of the bumper has been loaded into the software, and the coordinates of feature points for each location type are preset. Multi-position deformation data for each time node from T0 to T100 are mapped to the model. For example, at time T5, the feature point in the left middle (X0, Y0, Z0) is labeled D5-left-middle, the feature point at the left corner (X left turn, Y left turn, Z0) is labeled D5-left turn, and the feature point in the middle (X middle, Y middle, Z0) is labeled D5-middle. The labeling method uses a color gradient to represent the degree of deformation (e.g., blue to red corresponds to deformation from small to large), forming a time node-deformation labeling model sequence. Each model corresponds to a timestamp, and the sequence as a whole presents the spatial change process of deformation over time.

[0048] Step S1243: Select the models corresponding to two adjacent time nodes in the time node-deformation annotation model sequence, and denot them as the preceding time node model and the following time node model, respectively.

[0049] In this embodiment, models corresponding to T5 (preceding) and T6 (following) are selected from the sequence. The preceding time node model (T5) contains deformation annotations at each position at time T5, and the following time node model (T6) contains annotations at time T6. The two models are overlaid using a model comparison tool to facilitate observation of changes in the deformation region.

[0050] Step S1244: Compare the deformation degree values ​​at each position in the preceding time node model and the following time node model, and calculate the change in the deformation degree value at each position. The change is the value in the following time node model minus the value in the preceding time node model.

[0051] In this embodiment, the deformation values ​​of models T5 and T6 are compared, and the change ΔD is calculated as ΔD = D6 - position - D5 - position. For example, in the left-center region, ΔD_left_center = D6 - left_center - D5 - left_center; in the left corner region, ΔD_left_turn = D6 - left_turn - D5 - left_turn; and in the center region, ΔD_center = D6 - center - D5 - center. A positive change indicates increased deformation (diffusion), a negative change indicates decreased deformation (recovery, rare in static scenes), and zero indicates no change.

[0052] Step S1245: Identify the positions where the change is greater than zero. The positions where the change is greater than zero are the new positions to which the deformation has spread. Record the coordinate data of the positions where the change is greater than zero and the corresponding change values.

[0053] In this embodiment, during the time period from T5 to T6, the left-middle region ΔD is positive (continuous deformation), the left corner region ΔD changes from zero to positive (new diffusion position), and the middle region ΔD remains zero. Therefore, the positions with changes greater than zero are the left-middle region (continuous deformation) and the left corner region (new diffusion). The coordinates of the feature points in the left corner region (X left turn, Y left turn, Z0) and the left turn ΔD value are recorded.

[0054] Step S1246: Using the starting position coordinates in the set of static deformation starting positions as a reference, calculate the direction vector of the coordinates of each position with a change greater than zero relative to the starting position coordinates. The direction of the direction vector is the direction in which the deformation spreads from the starting position to the position with a change greater than zero.

[0055] In this embodiment, the static starting position coordinates of the left central region are (X_start, Y_start, Z0), and the new diffusion position coordinates of the left corner region are (X_left turn, Y_left turn, Z0). The direction vector is calculated by subtracting the starting coordinate from the ending coordinate, i.e., (X_left turn - X_start, Y_left turn - Y_start, 0). Since the deformation is mainly on the surface of the bumper (the deformation in the Z-axis direction is relatively small, so it is considered as planar diffusion), the direction vector points to the left corner region, indicating that the deformation diffuses from the starting position in the left central region to the left corner region.

[0056] Step S1247: Perform the above comparison, calculation, identification and direction vector determination steps on all adjacent time node models in the time node-deformation annotation model sequence, collect all obtained direction vectors, remove duplicate direction vectors, and form a set of static deformation propagation directions.

[0057] In this embodiment, the above steps are performed on all adjacent time node models (99 pairs in total) from T0 to T100 to obtain multiple direction vectors, such as vectors from the starting position in the left middle to the left corner and the middle region, and vectors from the starting position in the left corner to the middle and the lower edge region. By comparing the similarity of vector magnitude and direction angle, duplicate vectors are removed (e.g., those with a direction angle difference of less than a certain angle are considered duplicates), and finally a set of static deformation propagation directions is formed, containing a specific number of unique direction vectors. Each vector is associated with a corresponding time node, position type, and change amount information.

[0058] Step S1248: Add corresponding time node information, external force application location type information, and deformation degree change information to each direction vector in the set of static deformation propagation directions, so that each direction vector in the set of static deformation propagation directions can be associated with the original data in the subset of static test data, for subsequent construction of bumper deformation propagation direction model.

[0059] In this embodiment, each direction vector in the set of static deformation propagation directions is associated with the original data through metadata. For example, the direction vector pointing to the left corner region is supplemented with information such as the time node T5-T6, the type of external force application location "left-middle region", and the change in deformation degree ΔD to the left. The above metadata corresponds to a specific record in the subset of static test data (such as the deformation data of the left corner region in the time period T5-T6), ensuring that the direction vector can be traced back to the original test data.

[0060] Step S125: Extract deformation time series data from the dynamic test data subset. The deformation time series data is the deformation degree data of each position of the bumper corresponding to different time nodes in the dynamic test scenario. Based on the deformation degree data of each position of the bumper corresponding to different time nodes in the dynamic test scenario, calculate the change in deformation degree between adjacent time nodes, determine the direction of deformation diffusion from the starting position to other positions, and obtain the set of dynamic deformation propagation directions.

[0061] In this embodiment, the extraction logic for the dynamic deformation propagation direction is similar to that for the static scenario. However, due to the short impact time and rapid deformation changes, higher temporal resolution data is required. Taking the dynamic test in the left-middle region as an example, deformation data from multiple locations within a specific number of milliseconds after the impact is extracted from the dynamic test data subset to form a time node-deformation annotation model sequence (with a time interval of a specific number of milliseconds). By comparing the changes in adjacent models, direction vectors are calculated, ultimately forming a set of dynamic deformation propagation directions. The number of vectors is greater than in the static scenario, and the directions are more dispersed (the impact causes multi-directional diffusion).

[0062] Step S126: Integrate the set of static deformation propagation directions and the set of dynamic deformation propagation directions, and combine them with the surface curvature data of the three-dimensional structure model of the bumper to correct the abnormal direction data in the deformation propagation direction, and form a bumper deformation propagation direction model.

[0063] In this embodiment, vectors representing the sets of static and dynamic deformation propagation directions are imported into a 3D model and overlaid to display the bumper surface curvature data (high curvature areas such as corners, and low curvature areas such as the center). Analysis reveals that some direction vectors point to areas with extremely high curvature (such as bolt hole locations). Such directions are physically impossible (the material cannot penetrate them) and are therefore identified as abnormal direction data and discarded. Simultaneously, the propagation direction is corrected based on the curvature data: high curvature areas cause the propagation direction to deflect towards low curvature areas (e.g., the propagation direction in the left corner area deflects at a specific angle towards the center area due to high curvature). The corrected direction vectors are categorized according to scene type to form a bumper deformation propagation direction model, including static and dynamic direction sub-models, stored as "propagation direction model.obj", which can dynamically demonstrate the propagation process in 3D software.

[0064] Step S127: Calculate the deformation propagation rate from the deformation time series data in the static test data subset, select the time difference from the start position to the preset distance position, divide the preset distance by the time difference to obtain the static deformation propagation rate data, and form a static deformation propagation rate set.

[0065] In this embodiment, the static deformation propagation rate is calculated based on distance and time difference. The preset distance is the straight-line distance from the starting position to a target position (e.g., the distance from the starting position in the left middle to the edge of the left corner area, obtained through a 3D model measurement tool). The time point from the static time series data to the target position where the deformation propagates is found: the starting time Tstart (the moment when deformation begins at the starting position), the target time Ttarget (the moment when deformation at the target position first exceeds the threshold), and the time difference ΔT = Ttarget - Tstart. The static deformation propagation rate Vstatic = preset distance / ΔT, in millimeters per second. The rate is calculated for all static propagation directions to form a set of static deformation propagation rates, including the rate value, the corresponding direction vector, the preset distance, and the time difference information.

[0066] Step S128: Calculate the deformation propagation rate from the deformation time series data in the dynamic test data subset, select the time difference from the deformation propagation from the starting position to the preset distance position, divide the preset distance by the time difference to obtain the dynamic deformation propagation rate data, and form a dynamic deformation propagation rate set.

[0067] In this embodiment, the calculation logic for the dynamic deformation propagation rate is similar to that for the static scenario, but the time difference ΔT is smaller (the dynamic scenario propagates faster). For example, the preset distance from the left-center impact initiation position to the left corner area is the same as in the static scenario, but the time difference T_eye - T_start in the dynamic scenario is only a specific proportion of that in the static scenario. Therefore, the dynamic deformation propagation rate V_dynamic = preset distance / ΔT (dynamic), which is significantly greater than V_static. The rates in all dynamic propagation directions are calculated to form a dynamic deformation propagation rate set, which, together with the static set, constitutes a rate database.

[0068] Step S129: Integrate the static deformation propagation rate set and the dynamic deformation propagation rate set, and combine the environmental parameter data and external force parameter data of the corresponding test scenario to establish the correlation between deformation propagation rate and scenario parameters, forming a bumper deformation propagation rate model.

[0069] In this embodiment, the correlation between deformation propagation rate and scene parameters is achieved through multiple regression analysis. Static and dynamic propagation rate data are used as dependent variables, while environmental parameters (temperature, humidity) and external force parameters (static force magnitude, area of ​​action; dynamic impact peak value, impact time) are used as independent variables to construct a regression model. Analysis reveals that increased temperature increases the rate (material softening), while humidity has a relatively small impact on the rate; increased static external force and decreased area of ​​action increase the rate; increased dynamic impact peak value and shortened impact time increase the rate. Based on these correlations, the rate values ​​are corrected to form a bumper deformation propagation rate model, which includes a rate calculation formula (a textually described functional relationship), parameter weight coefficients, and scene type correction terms. This model is stored as "propagation rate model.pkl" and can predict the propagation rate based on the input environmental and external force parameters.

[0070] Step S1210: Based on the feature set of the starting point of the bumper deformation propagation, the model of the direction of the bumper deformation propagation, and the model of the rate of the bumper deformation propagation, construct a model of the path of the bumper deformation propagation. The model of the path of the bumper deformation propagation includes the identifier of the starting position of the deformation, the vector of the propagation direction, and the value of the propagation rate. Each propagation path data is associated with the corresponding test scenario parameter data.

[0071] In this embodiment, the final construction of the bumper deformation propagation path model integrates the starting point feature set, the direction model, and the rate model. In the 3D modeling software, the propagation starting point is determined based on the starting point feature set, the vector of the propagation direction model is loaded, and the propagation process of deformation from the starting point along the direction vector is dynamically demonstrated according to the rate calculated by the rate model. Each propagation path (starting point-direction-rate) is associated with corresponding scene parameters (such as a temperature of 25 degrees Celsius and a specific value of the external force in a static scene; and a specific value of the impact peak and a specific number of milliseconds in a dynamic scene). Path changes can be observed by adjusting these parameters. The model output is an interactive 3D animation and a path data report, including information such as path length, propagation time, and deformation distribution along the path.

[0072] Step S130: Based on the bumper deformation propagation path model, perform a coupling analysis of bumper deformation influencing factors under multiple scenarios, screen the core influencing factors affecting the deformation propagation rate, analyze the interaction relationship between different core influencing factors, and obtain the coupling analysis results of bumper deformation influencing factors under multiple scenarios.

[0073] In this embodiment, the influence factor coupling analysis aims to identify key parameters that significantly affect the deformation propagation rate and reveal their interaction mechanisms. The analysis focuses on the deformation propagation rate data of the front bumper and related environmental and external force parameters, conducting quantitative and qualitative analyses based on the constructed propagation path model.

[0074] Step S131: Extract all possible parameter data that may affect the deformation from the multi-scenario bumper deformation test data set. The parameter data includes air temperature data, air humidity data, and ambient air pressure data from the environmental parameter data, and external force magnitude data, external force area data, impact peak data, and impact time data from the external force action parameter data.

[0075] In this embodiment, parameter data extraction is achieved through database queries. Environmental parameter fields (temperature, humidity, air pressure) and external force parameter fields (static external force magnitude, area of ​​effect; dynamic impact peak value, impact time) are filtered from the "Multi-Scenario Test Data" table, excluding non-influencing parameters such as scenario type and timestamps. The extracted data is categorized by scenario type: static scenarios include temperature, humidity, air pressure, external force magnitude, and area of ​​effect; dynamic scenarios include temperature, humidity, air pressure, impact peak value, and impact time, forming a parameter data matrix. The number of rows corresponds to the number of records in the dataset, and the number of columns represents 7 parameters (5 for static scenarios, 5 for dynamic scenarios, with some overlapping parameters).

[0076] Step S132: Associate the parameter data with the deformation propagation rate data in the bumper deformation propagation path model, calculate the degree of association between each parameter data and the deformation propagation rate data, and retain the parameter data whose degree of association meets the preset requirements as candidate influencing factors to form a set of candidate influencing factors.

[0077] In this embodiment, the degree of correlation is calculated using correlation analysis. Each column of the parameter data matrix (e.g., temperature) is compared pairwise with the rate data output by the propagation path model, and a correlation coefficient (e.g., Pearson correlation coefficient) is calculated. The preset requirement is that the absolute value of the correlation coefficient is greater than a specific threshold (e.g., 0.3) and passes a significance test (P-value less than 0.05). The analysis results show that the correlation coefficients of temperature, humidity, external force magnitude, area of ​​impact, peak impact, and impact time meet the requirements. The absolute value of the correlation coefficient of air pressure is less than the threshold (insignificant impact). Therefore, the first six parameters are retained as candidate influencing factors, forming a set of candidate influencing factors, including environmental factors (temperature, humidity) and external force factors (static: external force magnitude, area of ​​impact; dynamic: peak impact, impact time).

[0078] Step S133: Perform a single-factor impact test on each candidate impact factor in the candidate impact factor set. While keeping other candidate impact factors unchanged, change the value of the target candidate impact factor, record the deformation propagation rate change data corresponding to the change of the target candidate impact factor value, and screen out the candidate impact factors that can cause the deformation propagation rate to change in accordance with the preset change standard as core impact factors, thus forming a core impact factor set.

[0079] In this embodiment, the single-factor impact test adopts the controlled variable method to simulate deformation propagation under different parameter values ​​in the test chamber. Taking temperature (an environmental candidate factor) as an example, other factors such as humidity and external force magnitude are kept constant, and the temperature is adjusted from a preset lower limit to a preset upper limit. The test is conducted in 5 gradients, and the rate change data is calculated through the propagation path model under each gradient.

[0080] Step S1331: Select a candidate impact factor from the set of candidate impact factors as the target candidate impact factor, and record the current value of the target candidate impact factor and the current values ​​of other candidate impact factors.

[0081] In this embodiment, temperature is selected as the target candidate influencing factor, and the current value is set as the standard temperature of the test chamber (such as a specific degree Celsius). Other candidate factors (humidity, external force magnitude, area of ​​action, etc.) are all set as values ​​under standard test conditions (such as a specific percentage of humidity, a specific value of external force magnitude).

[0082] Step S1332: Set multiple value gradients for the target candidate impact factor. The value gradient consists of multiple consecutive values ​​ranging from below the current value to above the current value, with the interval between each value remaining consistent.

[0083] In this embodiment, the temperature gradient is set to 5 levels: T1 (current value - specific temperature difference), T2 (current value - specific temperature difference / 2), T3 (current value), T4 (current value + specific temperature difference / 2), and T5 (current value + specific temperature difference), with an interval of specific temperature difference / 2, covering the temperature range of the vehicle's operating environment.

[0084] Step S1333: While keeping the current values ​​of other candidate impact factors unchanged, adjust the values ​​of the target candidate impact factor to the values ​​corresponding to each value gradient in turn, and conduct bumper deformation tests in static or dynamic test scenarios under each value.

[0085] In this embodiment, the test chamber is sequentially adjusted to T1 to T5. After each temperature stabilizes for a specific period of time, a static test is conducted on the left-middle region (since temperature is an environmental parameter, it affects both static and dynamic scenarios; static is used as an example here). During the test, other parameters (humidity, magnitude of external force, etc.) remain constant through closed-loop control of the test system, ensuring that only temperature is a variable.

[0086] Step S1334: For each target candidate influence factor value, collect the corresponding bumper deformation propagation rate data. This bumper deformation propagation rate data is calculated through the bumper deformation propagation path model, and record the bumper deformation propagation rate value corresponding to each value.

[0087] In this embodiment, after the test is completed at each temperature gradient, the deformation data is input into the propagation path model to calculate the propagation rate from the left middle region to the left corner region, and V1(T1), V2(T2), V3(T3), V4(T4), and V5(T5) are obtained and recorded as "Temperature-Rate Test.csv".

[0088] Step S1335: Calculate the difference between the value of the bumper deformation propagation rate under each gradient and the value of the bumper deformation propagation rate under the current value. This difference is used as the deformation propagation rate change data.

[0089] In this embodiment, the rate change data ΔV = Vn - V3 (n = 1, 2, 4, 5), for example ΔV1 = V1 - V3, ΔV4 = V4 - V3, is used to obtain the rate change caused by temperature change.

[0090] Step S1336: Set a preset change standard, which is a preset ratio of the absolute value of the deformation propagation rate change data to the current value of the bumper deformation propagation rate value.

[0091] In this embodiment, the preset change standard is set to the absolute value of ΔV being greater than a certain percentage (such as 10%) of V3, that is, when |ΔV|>0.1×V3, the factor is considered to have a significant impact on the rate.

[0092] Step S1337: Determine whether the deformation propagation rate change data of each target candidate impact factor meets the preset change standard. If there is deformation propagation rate change data under at least one value gradient that meets the preset change standard, then the target candidate impact factor is determined to be a core impact factor.

[0093] In this embodiment, the absolute value of ΔV4 (the change at T4) of the temperature test is 15% (>10%) of V3, which meets the preset standard. Therefore, temperature is determined to be the core influencing factor.

[0094] Step S1338: Add the candidate impact factors that are determined to be core impact factors to the temporary set of core impact factors, and perform the above selection, setting, testing, collection, calculation and judgment steps for each candidate impact factor in the set of candidate impact factors.

[0095] In this embodiment, the above steps are performed sequentially on humidity, external force magnitude, area of ​​impact, peak impact, and impact time in the candidate influencing factor set. Tests revealed that the ΔV for humidity under a high humidity gradient meets the standard, while the ΔV for external force magnitude and peak impact significantly exceeds the standard. The ΔV for area of ​​impact and impact time does not meet the standard (although the rate of decrease in area of ​​impact increases, the change does not exceed 10%). Therefore, the temporary set of core influencing factors includes temperature, humidity, external force magnitude, and peak impact.

[0096] Step S1339: Remove duplicate factors from the temporary set of core impact factors, and add corresponding single factor impact test data for each core impact factor, including value gradient data, bumper deformation propagation rate numerical data, and deformation propagation rate change data, to form a core impact factor set. This core impact factor set is used to construct the core impact factor coupling relationship matrix in the future.

[0097] In this embodiment, the temporary set of core influencing factors has no duplicate factors. Test data is added to each factor: five gradients of temperature and their corresponding V and ΔV; five gradients of humidity and their corresponding V and ΔV; five gradients of external force magnitude (from smallest to largest) and their corresponding V and ΔV; and five gradients of impact peak magnitude (from smallest to largest) and their corresponding V and ΔV. This forms the core influencing factor set, which is stored as "core factor set.xlsx" and includes fields such as factor name, type (environment / external force), and test data.

[0098] Step S134: Determine the type of each core impact factor in the core impact factor set, and divide the core impact factors into environmental core impact factors and external force core impact factors. Environmental core impact factors include air temperature data and air humidity data, while external force core impact factors include external force magnitude data and impact peak data.

[0099] In this embodiment, the classification of core influencing factors is based on the parameter source: temperature and humidity are derived from environmental parameter data and belong to the environmental category of core influencing factors; the magnitude of external force (static) and the peak impact (dynamic) are derived from external force action parameter data and belong to the external force category of core influencing factors. The classification results are recorded in the "Type" field of "Core Factor Set.xlsx" for easy subsequent coupling analysis.

[0100] Step S135: Construct a core impact factor coupling relationship matrix. Use environmental core impact factors and external force core impact factors as the rows and columns of the core impact factor coupling relationship matrix. Fill in the change data of deformation propagation rate when the two types of core impact factors work together in the element positions of the core impact factor coupling relationship matrix to form the core impact factor coupling relationship matrix.

[0101] In this embodiment, the core influencing factor coupling relationship matrix is ​​a 2-row (environmental: temperature, humidity) × 2-column (external force: magnitude of external force, peak impact) matrix. Matrix element (i, j) represents the rate change ΔV coupling when environmental factor i and external force factor j act together. The test method is as follows: keeping other factors constant, setting a high value for environmental factor i (gradient T5 / humidity H5) and a high value for external force factor j (magnitude of external force F5 / peak impact P5), testing the rate V coupling under their combined action, and calculating ΔV coupling = V coupling - (V environment i alone + V external force j alone - V standard), where V environment i alone is the rate when environmental factor i has a high value, V external force j alone is the rate when external force factor j has a high value, and V standard is the rate under standard conditions. For example, when temperature (T5) and external force magnitude (F5) act together, ΔV coupling = V(T5, F5) - (V(T5) + V(F5) - V standard). Fill this value into the position of (temperature, external force magnitude) in the matrix. Calculate all elements in this way to form the core influence factor coupling relationship matrix.

[0102] Step S136: Analyze the data in the core influence factor coupling relationship matrix, identify the core influence factor combinations corresponding to elements in the core influence factor coupling relationship matrix whose change data exceeds a preset change threshold, and determine the interaction type between the core influence factor combinations, including synergistic effect type and superimposed effect type. The synergistic effect type is when the change in deformation propagation rate when two types of factors act together is greater than the sum of the changes when the two types of factors act alone. The superimposed effect type is when the change in deformation propagation rate when two types of factors act together is equal to the sum of the changes when the two types of factors act alone.

[0103] In this embodiment, the preset change threshold is set to 15% of the standard rate V. Among the matrix elements, the ΔV coupling between temperature and external force magnitude is 20% of the standard rate V (>15%), and ΔV coupling > ΔV temperature alone + ΔV external force magnitude alone (synergistic effect); the ΔV coupling between humidity and impact peak is 12% of the standard rate V (<15%), and ΔV coupling ≈ ΔV humidity alone + ΔV impact peak alone (superimposed effect). Temperature-external force magnitude is identified as a synergistic combination, humidity-impact peak is identified as a superimposed combination, and the changes in other elements do not exceed the threshold or are superimposed effects.

[0104] Step S137: Based on the core influencing factor set, the core influencing factor coupling relationship matrix, and the interaction type, generate a multi-scenario bumper deformation influencing factor coupling analysis result. This multi-scenario bumper deformation influencing factor coupling analysis result includes a core influencing factor list, a core influencing factor coupling relationship matrix chart, and an interaction type description. Each part is associated with the corresponding test scenario identifier and the deformation propagation path data in the bumper deformation propagation path model.

[0105] In this embodiment, the results of the multi-scenario influencing factor coupling analysis are presented in report form. The core influencing factor list lists environmental factors (temperature, humidity) and external force factors (magnitude of external force, peak impact) and their individual impact test data; the coupling relationship matrix chart displays the magnitude of ΔV coupling in the form of a heatmap (the darker the color, the greater the change); the interaction type description details the performance and mechanism of synergistic (temperature-magnitude of external force) and superposition (humidity-peak impact) effects (e.g., increased temperature reduces material stiffness, which, together with increased external force, accelerates deformation propagation). Each part is associated with the propagation path model through a scenario identifier (static / dynamic) and propagation path data ID. For example, the synergistic effect of temperature-magnitude of external force corresponds to the propagation path data in the left-middle region of the static scenario, ensuring that the analysis results are traceable and verifiable.

[0106] Step S140: Based on the coupling analysis results of the multi-scenario bumper deformation influencing factors, calibrate the dynamic deformation threshold of the bumper, and combine the rate change characteristics of the deformation propagation path in the bumper deformation propagation path model to adjust the safety threshold range of bumper deformation under different scenarios, and generate the calibrated dynamic deformation threshold of the bumper.

[0107] In this embodiment, the calibration of the dynamic deformation threshold requires multiple adjustments to the initial threshold, taking into account propagation rate characteristics and factor coupling effects, to ensure that the threshold reflects the safe deformation range under actual working conditions. The calibration targets are the static and dynamic deformation thresholds of the front bumper. The initial threshold is set based on the material yield strength and needs to be corrected using the propagation path model and coupling analysis results.

[0108] Step S141: Obtain initial bumper deformation threshold data. The initial bumper deformation threshold data is the maximum allowable deformation of the bumper without considering the coupling effect of deformation propagation path and influencing factors. The initial bumper deformation threshold data includes the initial threshold for static scenes and the initial threshold for dynamic scenes.

[0109] In this embodiment, the initial threshold is obtained through materials mechanics testing. The yield strength of the front bumper material is tested to a specific value. Based on the bumper thickness and structure, the maximum allowable deformation is calculated: in a static scenario, the critical value for the material to undergo plastic deformation under constant external force is the initial threshold for the static scenario (e.g., a specific number of millimeters); in a dynamic scenario, the critical value for the material to crack under impact is the initial threshold for the dynamic scenario (e.g., a specific number of millimeters, less than the static threshold). The initial threshold data is stored as "initial threshold.xlsx", containing information such as scenario type, threshold value, and material parameters.

[0110] Step S142: Extract the correlation data between deformation propagation rate and deformation degree from the bumper deformation propagation path model, analyze the cumulative law of deformation degree when the deformation propagation rate exceeds the preset rate value, determine the corresponding deformation degree critical value when the deformation propagation rate exceeds the preset rate value, compare the deformation degree critical value with the static scene initial threshold, if the deformation degree critical value is less than the static scene initial threshold, adjust the static scene initial threshold to the deformation degree critical value, and obtain the static scene one-time calibration threshold.

[0111] In this embodiment, the correlation data between deformation propagation rate and deformation degree is extracted from the output log of the propagation path model, including real-time deformation at different rates. The preset rate value is set to 1.5 times the average propagation rate of the static scene (obtained from all static rate data in the statistical model). Analysis shows that when the rate exceeds this preset value, the accumulation speed of deformation degree increases significantly (deformation increases per unit time). The critical value of deformation degree at this time (the maximum deformation when the rate exceeds the preset value) is calculated to be a specific number of millimeters, which is less than the initial threshold of the static scene (due to rapid propagation causing the material to enter plastic deformation prematurely). Therefore, the initial threshold of the static scene is adjusted to this critical value, resulting in the first calibration threshold of the static scene.

[0112] Step S143: Extract the synergistic effect data of environmental core influencing factors and external force core influencing factors from the multi-scenario bumper deformation influencing factor coupling analysis results. When the environmental core influencing factor is within a specific value range and the external force core influencing factor is within a specific value range, calculate the deformation degree critical value corresponding to the deformation propagation rate at this time. Compare the deformation degree critical value with the static scene primary calibration threshold. If the deformation degree critical value is less than the static scene primary calibration threshold, adjust the static scene primary calibration threshold to the deformation degree critical value to obtain the static scene secondary calibration threshold.

[0113] In this embodiment, the synergistic effect data comes from the temperature-external force magnitude combination in the coupling analysis results. A specific value range is set where the temperature is higher than a preset high-temperature threshold (e.g., a specific degree Celsius) and the external force magnitude is higher than a preset high-force threshold (e.g., a specific value). At this point, the synergistic effect of the two significantly increases the propagation rate. The critical value for deformation under this combination is calculated using a propagation path model and found to be less than the static scene's first calibration threshold (high temperature + high external force leads to a significant reduction in material stiffness, further decreasing the critical deformation value). Therefore, the static scene's first calibration threshold is adjusted to this critical value, resulting in the static scene's second calibration threshold, which serves as the final calibration threshold for the static scene.

[0114] Step S144: Process the initial threshold of the dynamic scene using the same method, extract the correlation data between the dynamic deformation propagation rate and the degree of deformation from the bumper deformation propagation path model, determine the critical value of the degree of deformation when the dynamic deformation propagation rate exceeds the preset rate value, compare the critical value of the degree of deformation with the initial threshold of the dynamic scene, if the critical value of the degree of deformation is less than the initial threshold of the dynamic scene, then adjust the initial threshold of the dynamic scene to the critical value of the degree of deformation, and obtain the first calibration threshold of the dynamic scene.

[0115] In this embodiment, the preset rate value of the dynamic scene is set to 1.5 times the average propagation rate of the dynamic scene. Correlation data between dynamic rate and deformation degree is extracted from the propagation path model. It is found that when the rate exceeds the preset value, the critical value of deformation degree (the critical deformation that causes cracks due to impact) is less than the initial threshold of the dynamic scene (because dynamic impact propagates faster, the material is more likely to reach its fracture limit). Therefore, the initial threshold of the dynamic scene is adjusted to this critical value, resulting in the first calibration threshold for the dynamic scene.

[0116] Step S145: Extract the coupling effect data of the core influencing factors under dynamic scenarios from the coupling analysis results of the multi-scenario bumper deformation influencing factors, calculate the critical value of deformation degree under a specific factor combination, compare the critical value of deformation degree with the first calibration threshold of the dynamic scenario, if the critical value of deformation degree is less than the first calibration threshold of the dynamic scenario, then adjust the first calibration threshold of the dynamic scenario to the critical value of deformation degree to obtain the second calibration threshold of the dynamic scenario.

[0117] In this embodiment, the coupling effect data of the core influencing factors in dynamic scenarios is the superposition effect of humidity and impact peak. The specific factor combination is set to humidity being higher than a preset high humidity threshold (such as a specific percentage) and impact peak being higher than a preset high impact threshold (such as a specific value).

[0118] Step S1451: Extract the core influence factor coupling relationship matrix corresponding to the dynamic test scenario from the multi-scenario bumper deformation influence factor coupling analysis results. The core influence factor coupling relationship matrix contains the coupling effect data of environmental core influence factors and external force core influence factors under the dynamic scenario.

[0119] In this embodiment, the coupling relationship matrix of the dynamic scene is extracted from the coupling analysis result report. The coupling relationship matrix is ​​2 rows (environmental type: temperature, humidity) × 1 column (external force type: impact peak) (because there is no external force magnitude factor in the dynamic scene). The elements (humidity, impact peak) correspond to the ΔV coupling data of the superimposed effect.

[0120] Step S1452: Identify the elements in the core impact factor coupling relationship matrix whose change data exceeds a preset change threshold, determine the value range of the environmental core impact factor and the value range of the external force core impact factor corresponding to the element, and combine the value range of the environmental core impact factor and the value range of the external force core impact factor as a specific factor combination.

[0121] In this embodiment, the preset change threshold of the dynamic scene coupling matrix is ​​12% of the dynamic standard rate, and the ΔV coupling of the elements (humidity, impact peak) is 12% (equal to the threshold), which is considered effective coupling. The corresponding environmental factors (humidity) have values ​​higher than the preset high humidity threshold (e.g., a specific percentage), and the external force factors (impact peak) have values ​​higher than the preset high impact threshold (e.g., a specific value). The combination of the two constitutes a specific factor combination.

[0122] Step S1453: Based on the specific factor combination, in the parameter setting stage of the dynamic test scenario, adjust the environmental parameters to the range of values ​​for the core environmental influencing factors, and adjust the external force parameters to the range of values ​​for the core external force influencing factors.

[0123] In this embodiment, the environmental parameters of the test chamber are adjusted to a specific percentage of humidity (high humidity), the impact peak value of the drop hammer impact tester is set to a specific value (high impact), and other parameters (temperature, impact time) are set to standard values ​​to simulate working conditions with a specific combination of factors.

[0124] Step S1454: Under the test conditions corresponding to the specific combination of factors, perform dynamic bumper deformation test, and collect data on the degree of deformation and deformation propagation rate at each position of the bumper at preset time intervals.

[0125] In this embodiment, a dynamic impact test is performed on the left-center area of ​​the front bumper. A high-speed camera and a laser displacement sensor collect deformation and rate data at specific millisecond intervals, and the test is conducted a specific number of times to ensure data reliability.

[0126] Step S1455: Monitor the changing trend of deformation propagation rate data. When the deformation propagation rate data exceeds the preset dynamic rate threshold in the bumper deformation propagation path model, record the deformation degree data of each position of the bumper at this time.

[0127] In this embodiment, the preset dynamic rate threshold is the rate value corresponding to the one-time calibration threshold of the dynamic scene. During the test, when the rate exceeds this threshold, the system automatically records the deformation at each position at the current moment, and the deformation in the left-middle region reaches a specific number of millimeters.

[0128] Step S1456: Select the largest deformation value from the recorded deformation data of each position of the bumper, and use the largest deformation value as the critical value of deformation under a specific combination of factors.

[0129] In this embodiment, among the recorded deformation values ​​at each location, the value in the left-middle region is the largest (a specific number of millimeters), and this value is determined as the critical value for the degree of deformation under a specific combination of factors.

[0130] Step S1457: Obtain the dynamic scene one-time calibration threshold, and compare the deformation degree critical value under a specific factor combination with the dynamic scene one-time calibration threshold.

[0131] In this embodiment, the threshold for one calibration in a dynamic scene is a specific number of millimeters, and the critical value for the degree of deformation under a specific combination of factors is a specific number of millimeters (less than the threshold for one calibration).

[0132] Step S1458: If the critical value of deformation degree under a specific factor combination is less than the dynamic scene primary calibration threshold, then the dynamic scene primary calibration threshold is adjusted to the critical value of deformation degree under the specific factor combination to obtain the dynamic scene secondary calibration threshold.

[0133] In this embodiment, since the critical value under a specific combination of factors is less than the first calibration threshold, the first calibration threshold of the dynamic scene is adjusted to the critical value to obtain the second calibration threshold of the dynamic scene.

[0134] Step S1459: If the critical value of deformation degree under a specific factor combination is greater than or equal to the dynamic scene first calibration threshold, then keep the dynamic scene first calibration threshold unchanged and use the dynamic scene first calibration threshold as the dynamic scene second calibration threshold.

[0135] In this embodiment, this situation does not occur, and this step is unnecessary.

[0136] Step S14510: Add corresponding specific factor combination information, test condition information and deformation propagation rate monitoring data to the dynamic scene secondary calibration threshold.

[0137] In this embodiment, metadata is added to the dynamic scene secondary calibration threshold: specific factor combination (humidity > specific percentage, impact peak > specific value), test conditions (specific temperature in degrees Celsius, specific impact time in milliseconds), and rate monitoring data (rate value when exceeding the threshold), which is stored as "dynamic secondary calibration threshold.json", containing the threshold value and associated metadata.

[0138] Step S146: Integrate the static scene secondary calibration threshold and the dynamic scene secondary calibration threshold, and combine the corresponding test scene parameter data and core influence factor data to generate the calibrated bumper dynamic deformation threshold. The calibrated bumper dynamic deformation threshold includes the static scene calibration threshold and the dynamic scene calibration threshold, and each threshold is marked with the corresponding influence factor value range and deformation propagation rate range.

[0139] In this embodiment, the calibrated dynamic deformation threshold integrates static and dynamic secondary calibration thresholds. The static scene calibration threshold specifies the value ranges of environmental factors (temperature, humidity) and external force factors (magnitude of external force) (e.g., temperature < specific degree Celsius, humidity < specific percentage, magnitude of external force < specific value) and the corresponding rate ranges (< preset static rate). The dynamic scene calibration threshold specifies the value ranges of environmental factors (humidity) and external force factors (impact peak value) (e.g., humidity < specific percentage, impact peak value < specific value) and the corresponding rate ranges (< preset dynamic rate). The threshold data is stored as "calibrated dynamic deformation threshold.xlsx", containing fields such as scene type, threshold value, factor value range, and rate range.

[0140] Step S150: Integrate the bumper deformation propagation path model, the results of the coupling analysis of bumper deformation influencing factors in multiple scenarios, and the calibrated bumper dynamic deformation threshold to generate a comprehensive analysis report on bumper deformation testing that includes deformation propagation laws, the mechanism of action of influencing factors, and dynamic threshold standards.

[0141] In this embodiment, the comprehensive analysis report is a systematic integration of the results of all preceding steps, and it needs to fully present the deformation propagation law, the mechanism of action of influencing factors, and the dynamic threshold standard. The report is organized in a modular structure, with each module linked by a data ID to ensure the coherence and traceability of the content.

[0142] Step S151: Extract key data from the bumper deformation propagation path model. The key data includes deformation propagation starting point distribution data, propagation direction statistics data, and propagation rate change data. Organize the deformation propagation starting point distribution data, propagation direction statistics data, and propagation rate change data into a deformation propagation path information module. Each data entry in the deformation propagation path information module is associated with a test scenario identifier.

[0143] In this embodiment, the key data of the deformation propagation path information module is extracted from the output file of the propagation path model. The starting point distribution data includes the starting position coordinates and clustering analysis results for each location type in both static and dynamic scenes (e.g., the proportion of starting positions in the left corner region); the propagation direction statistics include the vector frequency distribution of the static and dynamic direction sub-models (e.g., the static propagation direction in the left-middle region is mainly towards the left corner, accounting for a specific percentage); and the propagation rate change data includes the mean and maximum rates of both static and dynamic scenes, as well as correlation curves with environmental / external force parameters (e.g., a temperature-rate positive correlation curve). Each data entry is associated with the corresponding test scene through a scene identifier (static scene IDS001, dynamic scene IDD001), for example, the static scene starting point distribution data is associated with S001, ensuring a clear data source.

[0144] Step S152: Extract the core content from the multi-scenario bumper deformation influencing factor coupling analysis results. The core content includes a list of core influencing factors, simplified data of the core influencing factor coupling relationship matrix, and a summary of interaction types. Organize the list of core influencing factors, the simplified data of the core influencing factor coupling relationship matrix, and the summary of interaction types into an influencing factor action mechanism information module. Each content item in this influencing factor action mechanism information module is associated with the deformation propagation path data in the corresponding bumper deformation propagation path model.

[0145] In this embodiment, the core content of the influencing factor mechanism information module is extracted from the coupling analysis results report. The core influencing factor list lists environmental factors (temperature, humidity) and external force factors (magnitude of external force, peak impact) and the key conclusions of their single impact tests (e.g., for every specific degree Celsius increase in temperature, the rate increases by a specific percentage); the coupling relationship matrix simplifies the data to the key elements of the original matrix (e.g., the synergistic effect ΔV coupling value of temperature-magnitude external force); the interaction type summary describes in detail the performance of synergistic and superimposed effects and their impact on the propagation path (e.g., the synergistic effect of temperature-magnitude external force shortens the static propagation path length in the left-middle region by a specific number of millimeters). Each content item is associated with the propagation path model through the propagation path data ID (e.g., static left-middle path ID P001). For example, the content related to the synergistic effect of temperature-magnitude external force is associated with P001, and the rate change curve of this path under the synergistic effect can be directly viewed.

[0146] Step S153: Extract the specific values ​​and related information from the calibrated bumper dynamic deformation threshold. The related information includes the range of influence factors and the range of propagation rate corresponding to the threshold. Organize the specific values ​​and the corresponding range of influence factors and the range of propagation rate from the calibrated bumper dynamic deformation threshold into a dynamic threshold standard information module. Each threshold data in the dynamic threshold standard information module is associated with the test scenario type and the combination of influence factors.

[0147] In this embodiment, the data for the dynamic threshold standard information module is extracted from "Calibrated Dynamic Deformation Threshold.xlsx". The static scene calibration threshold value is a specific number of millimeters, and the associated influence factor values ​​range from temperature < a specific degree Celsius, humidity < a specific percentage, external force magnitude < a specific value, and propagation rate range < a preset static rate. The dynamic scene calibration threshold value is also a specific number of millimeters, and the associated influence factor ranges from humidity < a specific percentage, impact peak value < a specific value, and propagation rate range < a preset dynamic rate. Each threshold data is associated with a scene type (static / dynamic) and an influence factor combination ID (e.g., temperature-external force magnitude combination IDC001). For example, the static scene threshold is associated with combination IDC001, allowing you to view the threshold calibration process data under this combination.

[0148] Step S154: Analyze the intrinsic relationship between the deformation propagation path information module, the influencing factor action mechanism information module, and the dynamic threshold standard information module; summarize the correspondence between the deformation propagation rate change and the coupling effect of the core influencing factor, as well as the correspondence between the coupling effect of the core influencing factor and the dynamic threshold adjustment, and form a correlation pattern analysis text.

[0149] In this embodiment, the intrinsic correlation analysis is achieved by cross-referencing data from three modules. The correspondence between the deformation propagation rate change and the coupling effect of the core influencing factors is as follows: the synergistic effect of temperature and external force increases the static rate by a specific percentage, corresponding to a decrease in the critical value of deformation by a specific number of millimeters; the correspondence between the coupling effect of the core influencing factors and the dynamic threshold adjustment is as follows: this synergistic effect causes the initial threshold of the static scene to be adjusted from a specific number of millimeters to a specific number of millimeters of the secondary calibration threshold. The correlation analysis text describes these correspondences and their intrinsic logic in natural language (e.g., increased rate accelerates deformation accumulation, requiring a reduction in the threshold to ensure safety), and is supplemented with data charts (e.g., rate-threshold relationship curves) to enhance readability.

[0150] Step S155: Organize the deformation propagation path information module, the influencing factor mechanism information module, the dynamic threshold standard information module, and the correlation pattern analysis text according to the preset report structure. First, present an overview of the test scenario, then sequentially display the content of the deformation propagation path information module, the influencing factor mechanism information module, and the dynamic threshold standard information module, and finally present the correlation pattern analysis text to form a preliminary comprehensive analysis report.

[0151] In this embodiment, the preset report structure references the industry standard test report template and is divided into six chapters: 1. Test Scenario Overview (introducing the definition of static and dynamic scenarios, parameter settings, and test object information); 2. Deformation Propagation Path Analysis (deformation propagation path information module content); 3. Influence Factor Coupling Analysis (influence factor action mechanism information module content); 4. Dynamic Deformation Threshold Calibration (dynamic threshold standard information module content); 5. Correlation Pattern Analysis (correlation pattern analysis text); 6. Conclusions and Recommendations. The preliminary comprehensive analysis report is filled with content according to this structure, and subheadings and charts are used within each chapter (e.g., Chapter 3 includes 3.1 a list of core influence factors, 3.2 a coupling relationship matrix, and 3.3 an explanation of interaction types) to ensure clear hierarchy.

[0152] Step S156: Supplement the preliminary comprehensive analysis report by adding corresponding module data source descriptions after the deformation propagation path information module, the influencing factor action mechanism information module, and the dynamic threshold standard information module. Each data source description is marked with the specific subset name and data entry number of the multi-scenario bumper deformation test data set from which the data comes, so that all data in the comprehensive analysis report can be queried to the original test record through the marked subset name and entry number, and finally, a comprehensive analysis report of bumper deformation test is generated.

[0153] In this embodiment, the supplementary content focuses on the data source description. The data source description is added after the deformation propagation path information module: the starting point distribution data comes from "Static Starting Position Label.json" (entries IDS001-001 to S001-100) and "Dynamic Starting Position Label.json" (entries IDD001-001 to D001-100); the propagation direction data comes from "Propagation Direction Model.obj" (model IDM001); and the propagation rate data comes from "Propagation Rate Model.pkl" (model IDM002). After the influencing factor mechanism information module, the core factor data is labeled as coming from "Core Factor Set.xlsx" (entries IDF001-001 to F001-004), and the coupling matrix comes from "Coupling Relationship Matrix.csv" (entries IDC001-001 to C001-004). After the dynamic threshold standard information module, the threshold data is labeled as coming from "Calibrated Dynamic Deformation Threshold.xlsx" (entries IDT001-001 to T001-002). All data source descriptions ensure that any data in the report can be retrieved from the original test record in the test database using the subset name and entry number (e.g., S001-001 corresponds to the first starting position data in the left corner area of ​​the static scene). The final comprehensive analysis report of bumper deformation test is in PDF format, containing approximately a certain number of pages, covering all module content, data source descriptions, and correlation analysis, meeting engineering application requirements.

[0154] Figure 2 The diagram illustrates exemplary hardware and software components of a bumper deformation test data analysis system 100 that can implement the ideas of this application, according to some embodiments of this application. For example, a processor 120 can be used in the bumper deformation test data analysis system 100 and to perform the functions described in this application.

[0155] For example, the bumper deformation test data analysis system 100 may include a network port 110 connected to a network, one or more processors 120 for executing program instructions, a communication bus 130, and various forms of storage media 140, such as a disk, ROM, or RAM, or any combination thereof. Exemplarily, the bumper deformation test data analysis system 100 may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The methods of this application can be implemented according to these program instructions. The bumper deformation test data analysis system 100 also includes an I / O interface 150 between the computer and other input / output devices.

[0156] Furthermore, this embodiment of the invention also provides a readable storage medium, wherein computer-executable instructions are preset in the readable storage medium, and when the processor executes the computer-executable instructions, the above-mentioned bumper deformation test data analysis method is implemented.

[0157] It should be noted that, in order to simplify the description of the present invention and thus help to understand one or more embodiments of the invention, multiple features may sometimes be grouped into one embodiment, drawing or description thereof in the foregoing description of the embodiments of the present invention.

Claims

1. A method for analyzing bumper deformation test data, characterized in that, The method includes: A multi-scenario bumper deformation test data set is obtained, which includes bumper deformation data under static test scenarios and bumper deformation data under dynamic test scenarios, as well as environmental parameter data and external force parameter data corresponding to the test scenarios. Based on the multi-scenario bumper deformation test data set, a bumper deformation propagation path model is constructed. The deformation time sequence features in the static and dynamic test data of the multi-scenario bumper deformation test data set are extracted to determine the starting position, propagation direction and propagation rate of the deformation on the bumper surface, thus forming the bumper deformation propagation path model. Based on the bumper deformation propagation path model, a coupling analysis of the influencing factors of bumper deformation under multiple scenarios is conducted. The core influencing factors affecting the deformation propagation rate are screened, and the interaction between different core influencing factors is analyzed to obtain the coupling analysis results of the influencing factors of bumper deformation under multiple scenarios. Based on the coupling analysis results of the multi-scenario bumper deformation influencing factors, the dynamic deformation threshold of the bumper is calibrated. Combined with the rate change characteristics of the deformation propagation path in the bumper deformation propagation path model, the range of the safe threshold for bumper deformation under different scenarios is adjusted to generate the calibrated dynamic deformation threshold of the bumper. By integrating the aforementioned bumper deformation propagation path model, the coupling analysis results of multi-scenario bumper deformation influencing factors, and the calibrated bumper dynamic deformation threshold, a comprehensive analysis report on bumper deformation testing is generated, which includes deformation propagation laws, the mechanism of action of influencing factors, and dynamic threshold standards. The process of calibrating the dynamic deformation threshold of the bumper based on the coupling analysis results of the multi-scenario bumper deformation influencing factors, and adjusting the range of the safe threshold for bumper deformation under different scenarios by combining the rate change characteristics of the deformation propagation path in the bumper deformation propagation path model, generates the calibrated dynamic deformation threshold for the bumper, including: Acquire initial bumper deformation threshold data, which is the maximum allowable deformation of the bumper without considering the deformation propagation path and the coupling effect of influencing factors. The initial bumper deformation threshold data includes the initial threshold for static scenes and the initial threshold for dynamic scenes. The correlation data between deformation propagation rate and deformation degree are extracted from the bumper deformation propagation path model. The cumulative law of deformation degree when the deformation propagation rate exceeds the preset rate value is analyzed. When the deformation propagation rate exceeds the preset rate value, the corresponding deformation degree critical value is determined. The deformation degree critical value is compared with the static scene initial threshold. If the deformation degree critical value is less than the static scene initial threshold, the static scene initial threshold is adjusted to the deformation degree critical value to obtain the static scene first calibration threshold. The synergistic effect data of environmental core influencing factors and external force core influencing factors are extracted from the multi-scenario bumper deformation influencing factor coupling analysis results. When the environmental core influencing factor is within a specific value range and the external force core influencing factor is within a specific value range, the deformation degree critical value corresponding to the deformation propagation rate is calculated. The deformation degree critical value is compared with the static scene first calibration threshold. If the deformation degree critical value is less than the static scene first calibration threshold, the static scene first calibration threshold is adjusted to the deformation degree critical value to obtain the static scene second calibration threshold. The same method is used to process the initial threshold of the dynamic scene. The correlation data between the dynamic deformation propagation rate and the degree of deformation is extracted from the bumper deformation propagation path model. The critical value of the degree of deformation when the dynamic deformation propagation rate exceeds the preset rate value is determined. The critical value of the degree of deformation is compared with the initial threshold of the dynamic scene. If the critical value of the degree of deformation is less than the initial threshold of the dynamic scene, the initial threshold of the dynamic scene is adjusted to the critical value of the degree of deformation to obtain the first calibration threshold of the dynamic scene. Extract the coupling effect data of the core influencing factors in the dynamic scene from the coupling analysis results of the multi-scenario bumper deformation influencing factors, calculate the critical value of deformation degree under a specific factor combination, compare the critical value of deformation degree with the first calibration threshold of the dynamic scene, if the critical value of deformation degree is less than the first calibration threshold of the dynamic scene, then adjust the first calibration threshold of the dynamic scene to the critical value of deformation degree to obtain the second calibration threshold of the dynamic scene. By integrating the static scene secondary calibration threshold and the dynamic scene secondary calibration threshold, and combining the corresponding test scene parameter data and core influence factor data, a calibrated bumper dynamic deformation threshold is generated. This calibrated bumper dynamic deformation threshold includes the static scene calibration threshold and the dynamic scene calibration threshold, and each threshold is labeled with the corresponding influence factor value range and deformation propagation rate range.

2. The method for analyzing bumper deformation test data according to claim 1, characterized in that, The acquisition of the multi-scenario bumper deformation test data set includes: The bumper deformation test scenario types are divided into static test scenarios and dynamic test scenarios. Static test scenarios are test scenarios in which a constant external force is continuously applied, while dynamic test scenarios are test scenarios in which an instantaneous impact external force is applied. Bumper deformation data is extracted from static test scenarios. Data on the degree of bumper deformation corresponding to different external force application positions and the cumulative deformation data corresponding to the duration of external force holding are collected in static test scenarios. The data on the degree of bumper deformation corresponding to different external force application positions and the cumulative deformation data corresponding to the duration of external force holding are organized into a static test data subset. The static test data subset includes data corresponding to the external force application position and the degree of deformation, and data corresponding to the duration of external force holding and the cumulative deformation. Bumper deformation data is extracted from dynamic test scenarios. Instantaneous changes in bumper deformation corresponding to different impact forces and deformation recovery data corresponding to different impact frequencies are collected in dynamic test scenarios. The instantaneous changes in bumper deformation corresponding to different impact forces and deformation recovery data corresponding to different impact frequencies in dynamic test scenarios are organized into a dynamic test data subset. The dynamic test data subset includes data corresponding to impact force-instantaneous changes in deformation and data corresponding to impact frequency-deformation recovery. Collect environmental parameter data for the corresponding test scenario. Collect air temperature data, air humidity data, and ambient air pressure data during the test process in both static and dynamic test scenarios. Associate the environmental parameter data of the static test scenario with the static test data subset, and associate the environmental parameter data of the dynamic test scenario with the dynamic test data subset to form a static test data subset with environmental parameters and a dynamic test data subset with environmental parameters. Collect external force parameter data for the corresponding test scenario. In the static test scenario, collect the magnitude data of the constant external force and the area of ​​the external force. In the dynamic test scenario, collect the peak value data of the instantaneous impact force and the impact time data. Associate the external force parameter data of the static test scenario with the static test data subset with environmental parameters. Associate the external force parameter data of the dynamic test scenario with the dynamic test data subset with environmental parameters. A subset of static test data with environmental parameters and external force parameters and a subset of dynamic test data with environmental parameters and external force parameters are integrated to form a multi-scenario bumper deformation test data set. Each data entry in the multi-scenario bumper deformation test data set includes a test scenario type identifier, deformation data, environmental parameter data, and external force parameter data.

3. The method for analyzing bumper deformation test data according to claim 1, characterized in that, The process involves constructing a bumper deformation propagation path model based on the multi-scenario bumper deformation test data set. This includes extracting deformation timing features from the static and dynamic test data in the multi-scenario bumper deformation test data set, determining the starting position, propagation direction, and propagation rate of the deformation on the bumper surface, and forming the bumper deformation propagation path model. The model includes: Deformation start position data is extracted from the static test data subset of the multi-scenario bumper deformation test data set. The deformation start position data is the position coordinate data of the bumper when the external force is first applied in the static test scenario. The position coordinate data of the bumper when the external force is first applied in the static test scenario is marked on the three-dimensional structural model of the bumper to obtain the static deformation start position annotation set. Deformation start position data is extracted from the dynamic test data subset of the multi-scenario bumper deformation test data set. The deformation start position data is the position coordinate data of the earliest deformation of the bumper when the impact force is applied in the dynamic test scenario. The position coordinate data of the earliest deformation of the bumper when the impact force is applied in the dynamic test scenario is marked on the three-dimensional structure model of the bumper to obtain the dynamic deformation start position annotation set. By integrating the static deformation initiation position annotation set and the dynamic deformation initiation position annotation set, the distribution characteristics of deformation initiation positions under different test scenarios are analyzed, and common features of deformation initiation positions are extracted to form a feature set of the starting point of bumper deformation propagation. Deformation time series data is extracted from the static test data subset. The deformation time series data is the deformation degree data of each position of the bumper at different time nodes under the static test scenario. Based on the deformation degree data of each position of the bumper at different time nodes under the static test scenario, the change in deformation degree between adjacent time nodes is calculated to determine the direction of deformation spreading from the starting position to other positions, and a set of static deformation propagation directions is obtained. Deformation time series data is extracted from the dynamic test data subset. The deformation time series data is the deformation degree data of each position of the bumper corresponding to different time nodes in the dynamic test scenario. Based on the deformation degree data of each position of the bumper corresponding to different time nodes in the dynamic test scenario, the change in deformation degree between adjacent time nodes is calculated to determine the direction of deformation spreading from the starting position to other positions, and a set of dynamic deformation propagation directions is obtained. By integrating the set of static deformation propagation directions and the set of dynamic deformation propagation directions, and combining the surface curvature data of the three-dimensional structural model of the bumper, abnormal direction data in the deformation propagation direction are corrected to form a bumper deformation propagation direction model. The deformation propagation rate is calculated from the deformation time series data in the static test data subset. The time difference from the propagation of deformation from the starting position to the preset distance position is selected. The static deformation propagation rate data is obtained by dividing the preset distance by the time difference, thus forming a static deformation propagation rate set. The deformation propagation rate is calculated from the deformation time series data in the dynamic test data subset. The time difference from the start position to the preset distance position is selected. The dynamic deformation propagation rate data is obtained by dividing the preset distance by the time difference, thus forming a dynamic deformation propagation rate set. By integrating the set of static deformation propagation rates and the set of dynamic deformation propagation rates, and combining the environmental parameter data and external force parameter data of the corresponding test scenario, a correlation between deformation propagation rate and scenario parameters is established to form a bumper deformation propagation rate model. Based on the feature set of the starting point of the bumper deformation propagation, the model of the direction of the bumper deformation propagation, and the model of the rate of the bumper deformation propagation, a model of the propagation path of the bumper deformation is constructed. The model of the propagation path of the bumper deformation includes the deformation starting position identifier, the propagation direction vector and the propagation rate value, and each propagation path data is associated with the corresponding test scenario parameter data.

4. The method for analyzing bumper deformation test data according to claim 1, characterized in that, The step involves performing a multi-scenario coupling analysis of bumper deformation influencing factors based on the bumper deformation propagation path model, screening the core influencing factors affecting the deformation propagation rate, analyzing the interaction relationships between different core influencing factors, and obtaining the multi-scenario bumper deformation influencing factor coupling analysis results, including: Extract all possible parameters that may affect the deformation from the multi-scenario bumper deformation test data set. The parameter data includes air temperature data, air humidity data, and ambient air pressure data from the environmental parameter data, and external force magnitude data, external force area data, impact peak data, and impact time data from the external force parameter data. The parameter data is correlated with the deformation propagation rate data in the bumper deformation propagation path model. The correlation degree between each parameter data and the deformation propagation rate data is calculated. Parameter data whose correlation degree meets the preset requirements are retained as candidate influencing factors to form a set of candidate influencing factors. For each candidate impact factor in the candidate impact factor set, a single factor impact test is performed. While keeping other candidate impact factors unchanged, the value of the target candidate impact factor is changed, and the deformation propagation rate change data corresponding to the change of the target candidate impact factor value is recorded. Candidate impact factors that can cause the deformation propagation rate to change in accordance with the preset change standard are selected as core impact factors, forming a core impact factor set. The type of each core impact factor in the core impact factor set is determined, and the core impact factors are divided into environmental core impact factors and external force core impact factors. Environmental core impact factors include air temperature data and air humidity data, while external force core impact factors include external force magnitude data and impact peak data. Construct a core impact factor coupling relationship matrix, with environmental core impact factors and external force core impact factors as the rows and columns of the core impact factor coupling relationship matrix. Fill in the element positions of the core impact factor coupling relationship matrix with the change data of deformation propagation rate when the two types of core impact factors act together, and form the core impact factor coupling relationship matrix. Analyze the data in the core influence factor coupling relationship matrix, identify the core influence factor combinations corresponding to elements whose change data in the core influence factor coupling relationship matrix exceeds a preset change threshold, and determine the interaction type between the core influence factor combinations, including synergistic effect type and superimposed effect type. The synergistic effect type is when the change in deformation propagation rate when two types of factors act together is greater than the sum of the changes when the two types of factors act alone. The superimposed effect type is when the change in deformation propagation rate when two types of factors act together is equal to the sum of the changes when the two types of factors act alone. Based on the core influencing factor set, the core influencing factor coupling relationship matrix, and the interaction type, a multi-scenario bumper deformation influencing factor coupling analysis result is generated. This multi-scenario bumper deformation influencing factor coupling analysis result includes a core influencing factor list, a core influencing factor coupling relationship matrix chart, and an interaction type description. Each part is associated with the corresponding test scenario identifier and the deformation propagation path data in the bumper deformation propagation path model.

5. The method for analyzing bumper deformation test data according to claim 1, characterized in that, The integrated bumper deformation propagation path model, multi-scenario bumper deformation influencing factor coupling analysis results, and calibrated bumper dynamic deformation threshold generate a comprehensive bumper deformation test analysis report containing deformation propagation laws, influencing factor mechanisms, and dynamic threshold standards, including: Key data are extracted from the bumper deformation propagation path model. The key data includes deformation propagation starting point distribution data, propagation direction statistics data, and propagation rate change data. The deformation propagation starting point distribution data, propagation direction statistics data, and propagation rate change data are organized into a deformation propagation path information module. Each data entry in this deformation propagation path information module is associated with a test scenario identifier. The core content of the multi-scenario bumper deformation influencing factor coupling analysis results is extracted. The core content includes a list of core influencing factors, simplified data of the core influencing factor coupling relationship matrix, and a summary of interaction types. The list of core influencing factors, the simplified data of the core influencing factor coupling relationship matrix, and the summary of interaction types are organized into an influencing factor action mechanism information module. Each content item in this influencing factor action mechanism information module is associated with the deformation propagation path data in the corresponding bumper deformation propagation path model. Extract the specific values ​​and related information from the calibrated bumper dynamic deformation threshold. The related information includes the range of values ​​of the influencing factors and the range of propagation rates corresponding to the threshold. Organize the specific values ​​and the corresponding range of values ​​of the influencing factors and the range of propagation rates from the calibrated bumper dynamic deformation threshold into a dynamic threshold standard information module. Each threshold data in this dynamic threshold standard information module is associated with the test scenario type and the combination of influencing factors. The intrinsic relationship between the deformation propagation path information module, the influencing factor action mechanism information module, and the dynamic threshold standard information module is analyzed. The correspondence between the deformation propagation rate change and the coupling effect of the core influencing factor, as well as the correspondence between the coupling effect of the core influencing factor and the dynamic threshold adjustment, is summarized to form a correlation pattern analysis text. The deformation propagation path information module, the influencing factor mechanism information module, the dynamic threshold standard information module, and the correlation pattern analysis text are organized according to the preset report structure. First, an overview of the test scenario is presented, then the contents of the deformation propagation path information module, the influencing factor mechanism information module, and the dynamic threshold standard information module are displayed in sequence, and finally the correlation pattern analysis text is presented to form a preliminary comprehensive analysis report. The preliminary comprehensive analysis report is supplemented by adding corresponding data source descriptions after the deformation propagation path information module, the influencing factor mechanism information module, and the dynamic threshold standard information module. Each data source description indicates the specific subset name and data entry number from the multi-scenario bumper deformation test data set, so that all data in the comprehensive analysis report can be queried to the original test record through the labeled subset name and entry number, ultimately generating a comprehensive analysis report of bumper deformation tests.

6. The method for analyzing bumper deformation test data according to claim 2, characterized in that, The process involves extracting bumper deformation data from a static test scenario, collecting data on the degree of bumper deformation at different applied force locations and the cumulative deformation data corresponding to the duration of force application in the static test scenario. This data is then organized into a static test data subset, which includes data corresponding to the applied force location and the degree of deformation, as well as data corresponding to the duration of force application and the cumulative deformation. Determine the type of external force application location in the static test scenario, divide the bumper surface into multiple preset areas, each preset area is a type of external force application location, and record the coordinate range data of each type of external force application location. For each type of external force application location, a constant magnitude external force is applied. During the application of the constant magnitude external force, the deformation degree data of the bumper corresponding to the external force application location type is collected at preset time intervals. The deformation degree data is the deformation value of the bumper at the location corresponding to the external force application location type, forming the original data of external force application location-deformation degree for each type of external force application location. The raw data of the external force application location and deformation degree are sorted out to remove abnormal values ​​that occurred during the acquisition process. Abnormal values ​​are those that differ from the values ​​acquired in adjacent time intervals by more than a preset difference threshold. The sorted values ​​are classified according to the type of external force application location to form data corresponding to the external force application location and deformation degree. For each type of external force application location, a constant external force is continuously applied. During the process of maintaining the constant external force, the cumulative deformation data of the bumper corresponding to the type of external force application location is collected at preset time intervals. The cumulative deformation data is the total deformation value from the start of the application of the external force to the current time point, forming the original data of external force holding time - cumulative deformation for each type of external force application location. The original data of external force holding time and deformation accumulation is sorted out, and outlier values ​​are removed. Outlier values ​​are values ​​that do not conform to the preset deformation accumulation law. The sorted values ​​are classified according to the type of external force application location to form corresponding data of external force holding time and deformation accumulation. By integrating the data corresponding to the location of external force application and the degree of deformation, and the data corresponding to the duration of external force application and the cumulative deformation, a static test scenario identifier and an external force application location type identifier are added to each data entry to form a static test data subset. This static test data subset can be used to extract deformation time sequence features when constructing a bumper deformation propagation path model.

7. The method for analyzing bumper deformation test data according to claim 3, characterized in that, The step involves extracting deformation time-series data from the static test data subset. This deformation time-series data comprises the deformation degree data of each position of the bumper at different time points in the static test scenario. Based on the deformation degree data of each position of the bumper at different time points in the static test scenario, the change in deformation degree between adjacent time points is calculated to determine the direction of deformation propagation from the initial position to other positions, thus obtaining a set of static deformation propagation directions, including: Extract the corresponding data of external force application location and deformation degree for each type of external force application location from the static test data subset. The data of external force application location and deformation degree includes multiple time nodes and the deformation degree data of each position of the bumper corresponding to each time node. The deformation data of each position of the bumper at each time point is associated with the coordinate data of the three-dimensional structural model of the bumper. The deformation values ​​of each position at each time point are marked on the three-dimensional structural model of the bumper, forming a time point-deformation annotation model sequence. Select the models corresponding to two adjacent time nodes in the time node-deformation annotation model sequence, and denot them as the preceding time node model and the following time node model, respectively. Compare the deformation values ​​at each position in the preceding time node model and the following time node model, and calculate the change in the deformation value at each position. The change is the value in the following time node model minus the value in the preceding time node model. Identify locations where the change is greater than zero. These locations represent new locations to which the deformation has spread. Record the coordinate data of these locations and the corresponding change values. Using the starting position coordinates in the set of static deformation starting positions as a reference, calculate the direction vector of the coordinates of each position with a change greater than zero relative to the starting position coordinates. The direction of the direction vector is the direction in which the deformation spreads from the starting position to the position with a change greater than zero. For all adjacent time node models in the time node-deformation annotation model sequence, the above comparison, calculation, identification and direction vector determination steps are performed. All obtained direction vectors are collected, duplicate direction vectors are removed, and a set of static deformation propagation directions is formed. Add corresponding time node information, external force application location type information, and deformation degree change information to each direction vector in the set of static deformation propagation directions, so that each direction vector in the set of static deformation propagation directions can be associated with the original data in the subset of static test data, which can be used to construct the bumper deformation propagation direction model in the future.

8. The method for analyzing bumper deformation test data according to claim 4, characterized in that, The process involves performing a single-factor impact test on each candidate impact factor in the candidate impact factor set. While keeping other candidate impact factors constant, the value of the target candidate impact factor is changed. The change in deformation propagation rate after changing the target candidate impact factor value is recorded. Candidate impact factors that cause changes in the deformation propagation rate that meet preset change criteria are selected as core impact factors, forming a core impact factor set, including: Select one candidate impact factor from the set of candidate impact factors as the target candidate impact factor, and record the current value of the target candidate impact factor and the current values ​​of other candidate impact factors; Set multiple value gradients for the target candidate impact factor. The value gradient consists of multiple consecutive values ​​ranging from below the current value to above the current value, with a consistent interval between each value. While keeping the current values ​​of other candidate impact factors unchanged, the values ​​of the target candidate impact factors are adjusted sequentially to the values ​​corresponding to each value gradient, and bumper deformation tests are conducted in static or dynamic test scenarios under each value. For each target candidate influence factor value, the corresponding bumper deformation propagation rate data is collected. This bumper deformation propagation rate data is calculated through the bumper deformation propagation path model, and the bumper deformation propagation rate value corresponding to each value is recorded. Calculate the difference between the value of the bumper deformation propagation rate under each gradient and the value of the bumper deformation propagation rate under the current value. This difference is used as the deformation propagation rate change data. Set a preset change standard, which is a preset proportion in which the absolute value of the deformation propagation rate change data is greater than the current value of the bumper deformation propagation rate. Determine whether the deformation propagation rate change data of each target candidate impact factor meets the preset change criteria. If the deformation propagation rate change data under at least one value gradient meets the preset change criteria, then the target candidate impact factor is determined to be a core impact factor. Candidate impact factors identified as core impact factors are added to a temporary set of core impact factors. The above-described selection, setting, testing, collection, calculation, and judgment steps are performed on each candidate impact factor in the set of candidate impact factors. Duplicate factors are removed from the temporary set of core impact factors. For each core impact factor, corresponding single factor impact test data is added, including value gradient data, bumper deformation propagation rate numerical data, and deformation propagation rate change data, to form a core impact factor set. This core impact factor set is used to construct the core impact factor coupling relationship matrix in the subsequent process.

9. The method for analyzing bumper deformation test data according to claim 1, characterized in that, The process involves extracting coupling data of core influencing factors under dynamic scenarios from the multi-scenario bumper deformation influencing factor coupling analysis results, calculating the deformation degree critical value under a specific factor combination, comparing this deformation degree critical value with the dynamic scenario primary calibration threshold, and if the deformation degree critical value is less than the dynamic scenario primary calibration threshold, adjusting the dynamic scenario primary calibration threshold to this deformation degree critical value to obtain the dynamic scenario secondary calibration threshold, including: The coupling analysis results of the multi-scenario bumper deformation influencing factors are used to extract the core influencing factor coupling relationship matrix corresponding to the dynamic test scenario. This core influencing factor coupling relationship matrix contains the coupling effect data of environmental core influencing factors and external force core influencing factors under the dynamic scenario. Identify elements in the core impact factor coupling relationship matrix whose change data exceeds a preset change threshold, determine the value range of the environmental core impact factor and the value range of the external force core impact factor corresponding to the element, and combine the value range of the environmental core impact factor and the value range of the external force core impact factor as a specific factor combination; Based on the specific combination of factors, in the parameter setting stage of the dynamic test scenario, the environmental parameters are adjusted to the range of values ​​of the core environmental influencing factors, and the external force parameters are adjusted to the range of values ​​of the core external force influencing factors. Under the test conditions corresponding to this specific combination of factors, a dynamic bumper deformation test is conducted, and data on the degree of deformation and the rate of deformation propagation at each position of the bumper are collected at preset time intervals. Monitor the changing trend of deformation propagation rate data. When the deformation propagation rate data exceeds the preset dynamic rate threshold in the bumper deformation propagation path model, record the deformation degree data of each position of the bumper at this time. The maximum deformation value is selected from the recorded deformation data of each position of the bumper, and this maximum deformation value is used as the critical value of deformation under a specific combination of factors. Obtain the dynamic scene one-time calibration threshold, and compare the deformation degree critical value under a specific factor combination with the dynamic scene one-time calibration threshold; If the critical value of deformation degree under a specific factor combination is less than the first calibration threshold of the dynamic scene, then the first calibration threshold of the dynamic scene is adjusted to the critical value of deformation degree under the specific factor combination to obtain the second calibration threshold of the dynamic scene. If the critical value of deformation degree under a specific combination of factors is greater than or equal to the dynamic scene first calibration threshold, then the dynamic scene first calibration threshold is kept unchanged and the dynamic scene first calibration threshold is used as the dynamic scene second calibration threshold. Add corresponding specific factor combination information, test condition information, and deformation propagation rate monitoring data to the dynamic scene secondary calibration threshold.

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