Excitation vibration method, device and equipment based on layered constant amplitude load conversion

Abstract

This invention discloses an excitation and vibration method, apparatus, and equipment based on layered equal-amplitude load conversion, comprising: preprocessing the variable amplitude load spectrum of a vehicle durability test to obtain vehicle load time series data; performing full-cycle statistics using a three-parameter rainflow counting method and decoupling multi-channel loads to obtain the overall load statistical characteristics of the vehicle; dividing multiple equal-amplitude load intervals according to the load amplitude probability distribution and damage contribution ratio; calculating the cumulative damage ratio of each low-amplitude small-load cycle and performing damage reduction processing on each low-amplitude small-load cycle based on the cumulative damage ratio and a preset critical value; calculating the precise loading cycle number corresponding to each equal-amplitude load interval stepwise back-calculating according to the total damage equivalence constraint and the segmented damage trend equivalence constraint; and reconstructing the multi-equal-amplitude load loading time series of each equal-amplitude load interval to obtain a multi-level layered equal-amplitude load spectrum. This invention improves the reliability of vehicle durability testing and can be applied to the field of vehicle testing technology.

Description

Technical Field

[0001] This invention relates to the field of vehicle testing technology, and in particular to an excitation vibration method, apparatus and equipment based on layered equal amplitude load conversion. Background Technology

[0002] Existing vehicle durability testing largely involves applying simulated loads to the vehicle on a laboratory bench based on a vehicle durability amplitude load spectrum to quickly verify its durability performance. However, the processing of the vehicle durability amplitude load spectrum often involves simplification with single-amplitude scaling, small load truncation, and rough equivalence of total damage. This commonly results in problems such as deviations in damage trends, loss of mean load, distortion of multi-channel coupling in the vehicle, inconsistencies between bench failure modes and real-vehicle failure modes, and unreasonable cyclic distribution of large loads, all of which affect the reliability of vehicle durability testing. Furthermore, existing vertical vibration platforms suffer from high costs. Summary of the Invention

[0003] The purpose of this invention is to at least partially solve one of the technical problems existing in the prior art.

[0004] Therefore, one objective of this invention is to provide an excitation and vibration method based on layered equal amplitude load conversion. This method achieves high-precision conversion of the original variable amplitude random load spectrum of the whole vehicle to a multi-level layered equal amplitude load spectrum, and uses a whole vehicle vibration platform to apply vertical load excitation to the vehicle under test based on lateral loading, thereby improving the reliability of whole vehicle durability testing and reducing the cost of whole vehicle durability testing.

[0005] Another objective of this invention is to provide an excitation and vibration device based on layered equal amplitude load conversion.

[0006] To achieve the above-mentioned technical objectives, the technical solutions adopted in the embodiments of the present invention include: On one hand, embodiments of the present invention provide an excitation and vibration method based on layered constant amplitude load conversion, comprising the following steps: Obtain the vehicle durability variable load spectrum, and preprocess the vehicle durability variable load spectrum to obtain vehicle load time series data; The three-parameter rainflow counting method is used to perform full-cycle statistics on the vehicle load time series data to obtain a three-dimensional data matrix corresponding to multiple load cycles. Multi-channel load decoupling is performed on the coupled loads of each channel of the vehicle to obtain the full-domain load statistical characteristics of the vehicle. The load amplitude probability distribution and the damage contribution ratio of each load interval are determined based on the statistical characteristics of the vehicle's overall load. Multiple equal-amplitude load intervals are then divided based on the load amplitude probability distribution and the damage contribution ratio. Traverse the low-amplitude, low-load cycles, calculate the cumulative damage percentage of each low-amplitude, low-load cycle, and perform damage reduction processing on each low-amplitude, low-load cycle based on the cumulative damage percentage and a preset threshold value. Construct equivalent constraints for total damage and equivalent constraints for segmented damage trends, and calculate the precise number of loading cycles corresponding to each of the equal amplitude load intervals step by step based on the equivalent constraints for total damage and equivalent constraints for segmented damage trends. The loading time sequence of multiple equal amplitude loads is reconstructed for each equal amplitude load interval to obtain a multi-level layered equal amplitude load spectrum. The vehicle vibration platform is laterally loaded according to the multi-level layered equal amplitude load spectrum, so that the vehicle vibration platform applies a vertical load to the vehicle under test fixed on the vehicle vibration platform.

[0007] Furthermore, in one embodiment of the present invention, the step of obtaining the vehicle durability variable load spectrum and preprocessing the vehicle durability variable load spectrum to obtain vehicle load time series data specifically includes: During the vehicle road durability test, sensors installed at various parts of the vehicle are used to collect the time-domain signal of the original variable amplitude random load with full-domain multi-channel coupling, and the vehicle durability variable amplitude load spectrum is obtained. The vehicle durability variable load spectrum is processed by detrending term removal, abnormal spur removal, channel signal calibration, invalid data segment filtering, and baseline correction to obtain the vehicle load time series data.

[0008] Furthermore, in one embodiment of the present invention, the step of performing full-cycle statistical analysis on the vehicle load time-series data using the three-parameter rainflow counting method to obtain a three-dimensional data matrix corresponding to multiple load cycles, and performing multi-channel load decoupling on the coupled loads of each channel of the vehicle to obtain the overall load statistical characteristics of the vehicle, specifically includes: The load amplitude, load mean, and number of cycles corresponding to each load cycle of the vehicle load time series data are obtained by the three-parameter rainflow counting method. The three-dimensional data matrix corresponding to each load cycle is determined based on the load amplitude, the load mean, and the number of cycles. By using matrix decomposition and signal separation, the coupled loads of each channel of the vehicle are decoupled, and the independent load cycles of the body, suspension, chassis and transmission system are obtained. The statistical characteristics of the overall load of the vehicle are determined based on the independent load cycles and the three-dimensional data matrix.

[0009] Furthermore, in one embodiment of the present invention, the step of determining the load amplitude probability distribution and the damage contribution ratio of each load interval based on the statistical characteristics of the vehicle's overall load, and dividing multiple equal-amplitude load intervals based on the load amplitude probability distribution and the damage contribution ratio, specifically includes: A probability distribution analysis is performed on the statistical characteristics of the vehicle's total load to obtain the probability distribution of the load amplitude. The damage contribution percentage for each load range is calculated based on the Miner criterion. Starting from the maximum load amplitude, the intervals are divided in descending order of the proportion of damage contribution, and the reference amplitude and the original load mean value corresponding to each level of equal amplitude load are determined in turn to obtain multiple equal amplitude load intervals.

[0010] Furthermore, in one embodiment of the present invention, the step of traversing low-amplitude, low-load cycles, calculating the cumulative damage percentage of each low-amplitude, low-load cycle, and performing damage reduction processing on each low-amplitude, low-load cycle based on the cumulative damage percentage and a preset threshold value specifically includes: Traverse all low-amplitude, low-load cycles and calculate the proportion of cumulative damage of each low-amplitude, low-load cycle to the original total damage according to the Miner criterion to obtain the cumulative damage proportion. When the cumulative damage percentage is greater than or equal to the critical value, the corresponding low-amplitude small load will be cyclically assigned to the corresponding low-level equal-amplitude load range. When the cumulative damage percentage is less than the critical value, the corresponding low-amplitude small load cycle is converted into the number of cycles according to the Miner damage equivalence criterion and then equivalently incorporated into the adjacent upper-level equal-amplitude load interval.

[0011] Furthermore, in one embodiment of the present invention, the construction of the total damage equivalent constraint and the segmented damage trend equivalent constraint, and the step-by-step back-calculation of the precise loading cycle number corresponding to each of the equal amplitude load intervals based on the total damage equivalent constraint and the segmented damage trend equivalent constraint, specifically includes: Construct the total damage equivalent constraint, which ensures that the total cumulative damage of all multi-equal amplitude loads after transformation remains consistent with the total damage of the original load; Construct a segmented damage trend equivalent constraint, which makes the cumulative damage ratio and interval damage growth gradient trend corresponding to each amplitude interval consistent with the corresponding interval of the whole vehicle durability variable amplitude load spectrum. A system of equations is established based on the total damage equivalent constraint and the segmented damage trend equivalent constraint; The equations are solved using an iterative method to obtain the precise number of loading cycles corresponding to each of the constant amplitude load intervals.

[0012] Furthermore, in one embodiment of the present invention, the vehicle vibration enhancement platform includes multiple tire vertical vibration enhancement devices. Each tire vertical vibration enhancement device includes a platform fixing plate, a lifting clamp frame, a bearing seat, a vertical lifting connecting rod, a hydraulic drive rod, a guide shaft, a wheel placement plate, and an adjusting limit block. The lifting clamp frame is fixed on the platform fixing plate. One end of the bearing seat is connected to the hydraulic drive rod, and the other end of the bearing seat is connected to the bottom of the vertical lifting connecting rod, for driving the vertical lifting connecting rod to vibrate up and down under the lateral loading of the hydraulic drive rod. The bottom of the guide shaft is telescopically connected to the lifting clamp frame. The top of the vertical lifting connecting rod and the top of the guide shaft are both fixedly connected to the wheel placement plate. The adjusting limit block is disposed on the wheel placement plate.

[0013] On the other hand, embodiments of the present invention provide an excitation and vibration device based on layered constant amplitude load conversion, comprising: The variable amplitude load spectrum processing module is used to acquire the vehicle durability variable amplitude load spectrum, preprocess the vehicle durability variable amplitude load spectrum, and obtain the vehicle load time series data. The multi-channel load decoupling module is used to perform full-cycle statistics on the vehicle load time series data using the three-parameter rainflow counting method to obtain a three-dimensional data matrix corresponding to multiple load cycles, and to perform multi-channel load decoupling on the coupled loads of each channel of the vehicle to obtain the full-domain load statistical characteristics of the vehicle. The equal-amplitude load interval division module is used to determine the load amplitude probability distribution and the damage contribution ratio of each load interval based on the statistical characteristics of the vehicle's overall load, and to divide multiple equal-amplitude load intervals based on the load amplitude probability distribution and the damage contribution ratio. An adaptive damage reduction processing module is used to traverse low-amplitude small-load cycles, calculate the cumulative damage ratio of each low-amplitude small-load cycle, and perform damage reduction processing on each low-amplitude small-load cycle according to the cumulative damage ratio and a preset threshold value. The loop count calculation module is used to construct the total damage equivalent constraint and the segmented damage trend equivalent constraint, and to calculate the precise loading loop count corresponding to each of the equal amplitude load intervals step by step based on the total damage equivalent constraint and the segmented damage trend equivalent constraint. The loading timing reconstruction module is used to reconstruct the loading timing of multiple equal-amplitude loads in each equal-amplitude load interval to obtain a multi-level layered equal-amplitude load spectrum. The excitation and vibration module is used to apply lateral loading to the vehicle vibration platform according to the multi-level layered equal amplitude load spectrum, so that the vehicle vibration platform applies a vertical load to the vehicle under test fixed on the vehicle vibration platform.

[0014] On the other hand, embodiments of the present invention provide an electronic device, including: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the above-described excitation and vibration method based on hierarchical equal-amplitude load conversion.

[0015] On the other hand, embodiments of the present invention also provide a computer-readable storage medium storing a processor-executable computer program that, when executed by a processor, implements the above-described excitation and vibration method based on layered constant amplitude load conversion.

[0016] On the other hand, embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the above-described excitation and vibration method based on layered equal-amplitude load conversion.

[0017] The advantages and beneficial effects of the present invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention: This invention acquires the vehicle durability variable amplitude load spectrum, preprocesses it to obtain vehicle load time series data, performs full-cycle statistics on the vehicle load time series data using the three-parameter rainflow counting method, obtains three-dimensional data matrices corresponding to multiple load cycles, and decouples the coupled loads of each channel of the vehicle through multi-channel load decoupling to obtain the vehicle's global load statistical characteristics. Based on the vehicle's global load statistical characteristics, the load amplitude probability distribution and the damage contribution ratio of each load interval are determined. Based on the load amplitude probability distribution and the damage contribution ratio, multiple equal amplitude load intervals are divided, and low-amplitude small load cycles are traversed to calculate each low-amplitude... The invention employs a method to calculate the cumulative damage percentage of small-amplitude load cycles and perform damage reduction processing on each low-amplitude small-load cycle based on the cumulative damage percentage and a preset critical value. This constructs equivalent constraints for total damage and equivalent constraints for segmented damage trends. Based on these constraints, the precise number of loading cycles corresponding to each equal-amplitude load interval is calculated step-by-step. The loading sequence of multiple equal-amplitude load intervals is reconstructed to obtain a multi-level layered equal-amplitude load spectrum. Lateral loading is applied to the vehicle vibration platform based on this multi-level layered load spectrum, thereby applying a vertical load to the vehicle under test fixed on the platform. This embodiment of the invention achieves high-precision conversion from the original variable-amplitude random load spectrum of the vehicle to a multi-level layered equal-amplitude load spectrum. Furthermore, by utilizing the vehicle vibration platform to apply vertical load excitation to the vehicle under test based on lateral loading, the reliability of vehicle durability testing is improved, and the cost of vehicle durability testing is reduced. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments of the present invention are described below. It should be understood that the drawings described below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating the steps of an excitation and vibration method based on layered constant amplitude load conversion, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the tire vertical vibration enhancement device provided in an embodiment of the present invention; Figure 3 A structural block diagram of an excitation and vibration device based on layered constant amplitude load conversion provided in an embodiment of the present invention; Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention as detailed in the appended claims.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to limit the invention.

[0022] The excitation and vibration method based on hierarchical equal-amplitude load conversion provided in this invention can be applied to terminals, servers, or software running on either terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited thereto; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the server can also be a node server in a blockchain network; the software can be an application implementing the excitation and vibration method based on hierarchical equal-amplitude load conversion, but is not limited to the above forms.

[0023] This invention can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0024] It should be noted that in various specific embodiments of the present invention, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user parking space location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of the present invention require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to a confirmation page. Only after obtaining the user's separate permission or consent is the necessary user-related data for the normal operation of the embodiments of the present invention acquired.

[0025] Reference Figure 1 This invention provides an excitation and vibration method based on layered constant amplitude load conversion, specifically including the following steps: S101. Obtain the vehicle durability variable load spectrum, preprocess the vehicle durability variable load spectrum, and obtain the vehicle load time series data. S102. Perform full-cycle statistics on the time-series load data of the whole vehicle using the three-parameter rainflow counting method to obtain a three-dimensional data matrix corresponding to multiple load cycles. Decouple the coupled loads of each channel of the whole vehicle through multiple channels to obtain the statistical characteristics of the whole vehicle's global load. S103. Determine the load amplitude probability distribution and the damage contribution ratio of each load interval based on the statistical characteristics of the vehicle's total load. Divide the load amplitude probability distribution and the damage contribution ratio into multiple equal-amplitude load intervals. S104. Traverse the low-amplitude small-load cycles, calculate the cumulative damage ratio of each low-amplitude small-load cycle, and perform damage conversion processing on each low-amplitude small-load cycle based on the cumulative damage ratio and the preset critical value. S105. Construct equivalent constraints for total damage and equivalent constraints for segmented damage trends. Based on the equivalent constraints for total damage and equivalent constraints for segmented damage trends, calculate the precise loading cycle number corresponding to each equal amplitude load interval step by step. S106. Perform multi-equal-amplitude load loading sequence reconstruction on each equal-amplitude load interval to obtain a multi-level layered equal-amplitude load spectrum. S107. Apply lateral loading to the vehicle vibration platform according to the multi-level layered equal amplitude load spectrum, so that the vehicle vibration platform applies vertical load to the vehicle under test fixed on the vehicle vibration platform.

[0026] Specifically, this invention, based on Miner's linear cumulative fatigue damage theory, constructs a dual-constraint system of strict equivalence of total damage and equivalence of segmented damage trends across the entire load interval. It employs improved three-parameter rainflow counting, vehicle load decoupling, adaptive multi-interval layering, full retention of mean load, adaptive conversion of small loads, step-by-step iteration count back-calculation, loading sequence reconstruction, and error closed-loop iterative correction to achieve high-precision conversion from the original variable amplitude random load spectrum of the vehicle to a multi-level layered constant amplitude load spectrum. The specific process is as follows: Step 1: Preprocessing of raw load spectrum data of the whole vehicle The original variable amplitude random load time-domain signal of the whole vehicle road durability test was collected through multi-channel coupling. The original load spectrum was then cleaned and processed sequentially, including detrending, abnormal glitch removal, channel signal calibration, invalid data segment filtering, and baseline correction to remove noise interference and obtain a clean and effective whole vehicle load time-domain sequence, which served as the basis for subsequent transformation.

[0027] Step 2: Three-parameter rainflow counting statistics and multi-channel load decoupling The three-parameter rainflow counting method (load amplitude, load mean, and number of cycles) is used to perform full-cycle statistics on the preprocessed vehicle load sequence, and obtain the three-dimensional data matrix of amplitude, mean, and number of cycles corresponding to all load cycles. At the same time, the coupling load of each channel of the vehicle is decoupled, and the independent load cycles of the body, suspension, chassis, and transmission system are separated, so as to fully preserve the statistical characteristics of the load across the entire vehicle.

[0028] Step 3: Adaptive multi-level load range hierarchical division Based on the statistically completed probability distribution of load amplitude and the proportion of damage contribution in each interval, N levels of equal-amplitude load intervals are dynamically and adaptively divided, with N≥3 levels. The interval division boundaries are not manually fixed but automatically optimized according to the original load distribution characteristics. The reference amplitude and the corresponding original load mean are determined sequentially for each level of equal-amplitude load, forming a multi-level equal-amplitude load basic sequence, ensuring complete separation of large, medium, and small load levels, and no overlapping of interval boundaries.

[0029] Step 4: Adaptive Damage Calculation under Small Load Instead of directly eliminating small loads using a fixed amplitude threshold, this method iterates through all low-amplitude small load cycles, calculates the proportion of cumulative damage of each small load to the original total damage, and sets a critical threshold for the damage proportion. (1) If the proportion of damage caused by small loads is not lower than the set critical value, the load is directly retained and classified into the corresponding low-level constant amplitude load range; (2) If the proportion of small load damage is lower than the set critical value, it is not directly discarded. Instead, in strict accordance with the Miner damage equivalence criterion, the small load damage is converted into the number of cycles and equivalently incorporated into the adjacent upper level equal amplitude load, thus completely retaining all the accumulated damage of the small load.

[0030] Step 5: Back-calculation of the number of load cycles at each stage under dual constraint conditions According to Miner's linear cumulative damage criterion, the formula for calculating the total damage under the original load is as follows:

[0031] in: This represents the original number of cycles for each load. This represents the material's fatigue limit cycle number under the corresponding load amplitude. This is the total number of original load cycles.

[0032] This invention employs dual equivalent constraints: First constraint: Total damage equivalence. The total cumulative damage of all multi-equal amplitude loads after transformation remains consistent with the total damage of the original loads, that is:

[0033] in: It is the converted number The number of cycles for a constant amplitude load. This refers to the number of fatigue failure cycles under the stress level corresponding to this level of constant amplitude load. It is the total number of load cycles after conversion.

[0034] Second constraint: Segmented damage trend equivalence. The proportion of cumulative damage to total damage and the gradient trend of damage growth in each amplitude interval are completely consistent with the corresponding intervals of the original load spectrum.

[0035] Based on the above dual constraints, the precise number of loading cycles corresponding to each level of constant amplitude load is calculated step by step. .

[0036] Step 6: Timing reconstruction of multi-equal amplitude load application Based on the timing of the occurrence of large loads and the distribution of damage weights in the original random load, the loading order of each level of equal-amplitude load with determined amplitude, mean, and number of cycles is rearranged. The loading order of each level of load is arranged according to the original load timing characteristics to avoid disordered and random stacking of loads and ensure the consistency of the stress characteristics of the entire vehicle loading process.

[0037] Step 7: Closed-loop verification and iterative correction of conversion error Automatically calculates the total relative error of the converted load spectrum and the segmented damage trend deviation rate of each interval; preset accuracy control thresholds: total relative error of damage ≤1%, and damage proportion deviation of each interval ≤3%.

[0038] If the calculation error is within the allowable threshold range, the final load spectrum is directly output; if the error exceeds the allowable threshold, the system automatically iteratively optimizes the load layer boundary, small load conversion factor, and load cycle number parameters at each level, and recalculates until the double constraint accuracy requirements are met.

[0039] Step 8: Final constant amplitude load spectrum output It outputs a multi-level, layered constant amplitude durability load spectrum for the whole vehicle. The data includes the load amplitude, load mean, number of loading cycles, and complete loading time sequence for each level. It can be directly imported into the vehicle durability bench control system to complete automated constant amplitude loading tests.

[0040] In addition, the embodiments of the present invention pre-design a platform that can achieve vertical vibration of the entire vehicle by simply pushing and pulling laterally using the lever principle. Through the vehicle's actuation mechanism, the vertical constant amplitude vibration of the road surface facing the wheel center during durable driving is restored. At the same time, replaceable tire fixing fixtures and wheel hub bearing torsional vibration fixtures are designed to ensure that the platform can meet different loading requirements.

[0041] It is understood that the embodiments of the present invention achieve high-precision conversion from the original variable amplitude random load spectrum of the whole vehicle to the multi-level layered constant amplitude load spectrum, and use the whole vehicle vibration platform to apply vertical load excitation to the vehicle under test based on lateral loading, thereby improving the reliability of the whole vehicle durability test and reducing the cost of the whole vehicle durability test.

[0042] As a further optional implementation, the vehicle durability variable load spectrum is obtained, and the vehicle durability variable load spectrum is preprocessed to obtain vehicle load time series data, which specifically includes: S1011. During the vehicle road durability test, sensors installed at various parts of the vehicle are used to collect the original variable amplitude random load time domain signal of the whole domain multi-channel coupling to obtain the vehicle durability variable amplitude load spectrum. S1012. Perform detrending term removal, abnormal spur removal, channel signal calibration, invalid data segment filtering, and baseline correction on the vehicle durability variable amplitude load spectrum to obtain the vehicle load time series data.

[0043] Specifically, during the vehicle road durability test, sensors installed on the body, suspension, chassis, and transmission system are used to collect full-domain, multi-channel coupled original variable-amplitude random load time-domain signals. The data acquisition process must ensure coverage of different driving conditions, such as acceleration, deceleration, turning, and driving on bumpy roads, to guarantee the comprehensiveness of the data.

[0044] The data preprocessing for the vehicle durability variable load spectrum includes the following steps: Detrending term: Using methods such as polynomial fitting, the trend component in the load signal is removed, eliminating the overall signal offset caused by factors such as slope and load changes during vehicle travel.

[0045] Abnormal spikes and glitch removal: By setting a reasonable threshold, abnormal peaks and glitch in the signal can be identified and removed. These abnormal values ​​may be caused by instantaneous impact or electromagnetic interference to the sensor.

[0046] Channel signal calibration: The sensor signals of each channel are calibrated to ensure that the signal amplitude, phase and other parameters of different channels are consistent, and to avoid signal deviation caused by individual sensor differences or installation errors.

[0047] Invalid data segment filtering: Delete invalid data segments generated during the acquisition process due to equipment failure, signal loss, etc., and retain only continuous and valid payload signals.

[0048] Baseline correction: Adjusting the signal baseline to bring the signal mean back to a reasonable range ensures the accuracy of subsequent analysis. After the above processing, a clean and effective time-domain sequence of vehicle load is obtained, which serves as the basis for subsequent transformations.

[0049] As a further optional implementation, the three-parameter rainflow counting method is used to perform full-cycle statistical analysis on the vehicle load time series data to obtain a three-dimensional data matrix corresponding to multiple load cycles. Furthermore, multi-channel load decoupling is performed on the coupled loads of each channel of the vehicle to obtain the overall vehicle load statistical characteristics, which specifically include: S1021. Obtain the load amplitude, load mean, and number of cycles corresponding to each load cycle of the vehicle load time series data through the three-parameter rainflow counting method. S1022. Determine the three-dimensional data matrix corresponding to each load cycle based on the load amplitude, load mean, and number of cycles. S1023. Using matrix decomposition and signal separation, the coupled loads of each channel of the vehicle are decoupled to obtain independent load cycles of the body, suspension, chassis and transmission system. Based on the independent load cycles and the three-dimensional data matrix, the statistical characteristics of the overall load of the vehicle are determined.

[0050] Specifically, a three-parameter rainflow counting method (load amplitude, load mean, and number of cycles) is used to perform full-cycle statistics on the preprocessed vehicle load sequence. The specific operation is as follows: 1) Rotate the load time-domain sequence so that the load axis is vertically downward and the time axis is horizontally to the right.

[0051] 2) Starting from the first peak and valley value of the load sequence, trace the flow path of the "raindrop" sequentially, and record the load amplitude, load mean, and number of cycles for each cycle. For example, when the "raindrop" flows from one peak value to an adjacent valley value and then flows back to another peak value, forming a complete cycle, record the amplitude of this cycle as half the difference between the peak value and the valley value, the mean value as the average of the peak value and the valley value, and the number of cycles as 1.

[0052] 3) Repeat the above process until all load cycles have been statistically analyzed, and obtain a three-dimensional data matrix of amplitude, mean, and number of cycles corresponding to all load cycles.

[0053] By employing algorithms such as matrix factorization and signal separation, the coupled loads of each channel in the vehicle are decoupled, separating the independent load cycles of the body, suspension, chassis, and transmission system. For example, by establishing mechanical models between each component and combining the collected multi-channel signals, the independent loads of each component are solved using methods such as the least squares method, thus fully preserving the statistical characteristics of the overall vehicle load.

[0054] As a further optional implementation, the load amplitude probability distribution and the damage contribution ratio of each load interval are determined based on the statistical characteristics of the vehicle's overall load. Multiple equal-amplitude load intervals are then divided based on the load amplitude probability distribution and damage contribution ratio, specifically including: S1031. Perform probability distribution analysis on the statistical characteristics of the load across the entire vehicle to obtain the probability distribution of load amplitude; S1032. Calculate the damage contribution ratio for each load range according to the Miner criterion. S1033. Starting from the maximum load amplitude, divide the intervals in descending order of damage contribution ratio, and determine the reference amplitude and the original load mean value corresponding to each level of equal amplitude load in turn to obtain multiple equal amplitude load intervals.

[0055] Specifically, a probability distribution analysis is performed on the statistically completed load amplitudes, and frequency distribution histograms and probability density curves of the load amplitudes are plotted to understand the distribution law of the load amplitudes, such as normal distribution, Weibull distribution, etc. At the same time, the damage contribution ratio of each load amplitude interval is calculated. According to the Miner criterion, the damage contribution ratio is proportional to the m-th power of the load amplitude (m is the fatigue index of the material, which can be obtained through material testing).

[0056] Based on the probability distribution of load amplitude and the proportion of damage contribution in each interval, N levels of equal-amplitude load intervals (N≥3) are dynamically and adaptively divided. The specific steps are as follows: 1) Starting from the maximum load amplitude, divide the load intervals in descending order of damage contribution percentage. For example, first determine the load interval with the largest damage contribution percentage, and automatically optimize the boundary of this interval based on the load distribution characteristics to ensure that the load amplitude within the interval contributes significantly to the total damage.

[0057] 2) Determine the reference amplitude and the corresponding original load mean value for each level of equal amplitude load in sequence. The reference amplitude can be selected as the average or median of the load amplitude within the interval, and the original load mean value is the average of the load mean values ​​of all cycles within the interval.

[0058] 3) Repeat the above process until N equal-amplitude load intervals are defined, ensuring that the large, medium and small load levels are completely separated and that the boundaries of each interval do not overlap, thus forming a multi-level equal-amplitude load basic sequence.

[0059] As a further optional implementation, the low-amplitude, low-load cycles are traversed, the cumulative damage percentage of each low-amplitude, low-load cycle is calculated, and damage reduction processing is performed on each low-amplitude, low-load cycle based on the cumulative damage percentage and a preset threshold value. Specifically, this includes: S1041. Traverse all low-amplitude small-load cycles and calculate the proportion of cumulative damage of each low-amplitude small-load cycle to the original total damage according to the Miner criterion to obtain the cumulative damage ratio. S1042. When the cumulative damage percentage is greater than or equal to the critical value, the corresponding low-amplitude small load will be cyclically assigned to the corresponding low-level equal-amplitude load range. S1043. When the cumulative damage percentage is less than the critical value, the corresponding low-amplitude small load cycle is converted into the number of cycles according to the Miner damage equivalence criterion and then equivalently incorporated into the adjacent upper-level equal-amplitude load interval.

[0060] Specifically, it iterates through all low-amplitude, small-load cycles and calculates the proportion of cumulative damage from each small load to the original total damage based on the Miner criterion. The specific calculation method is as follows: first, determine the stress level corresponding to the small load, and then... The fatigue failure cycle count at this stress level can be obtained from the curve. Combined with the number of cycles under small loads Calculate damage Finally, the damage under this small load is calculated. Compared with the original total damage The ratio of (original total damage can be obtained by summing the damage over all load cycles).

[0061] If the proportion of damage from small loads exceeds a set threshold (e.g., 1%), that portion of the load is retained and classified into the corresponding lower-level constant-amplitude load range. This is because although these small loads have small amplitudes, their contribution to the total damage is not negligible due to the large number of cycles.

[0062] If the proportion of minor load damage is below the set critical value, it is not directly discarded. Instead, strictly following the Miner damage equivalence criterion, this portion of minor load damage is converted into cycle counts and equivalently incorporated into the adjacent upper-level equal-amplitude load. The conversion formula is: ,in To calculate the equivalent number of cycles to the higher-level load, Damage caused by small loads, The damage caused by the upper load in each cycle. This represents the original cycle number of the higher-level load. In this way, all cumulative damage from minor loads is fully preserved.

[0063] As an optional implementation, a total damage equivalent constraint and a segmented damage trend equivalent constraint are constructed. Based on the total damage equivalent constraint and the segmented damage trend equivalent constraint, the precise number of loading cycles corresponding to each equal amplitude load interval is calculated step by step. Specifically, this includes: S1051. Construct a total damage equivalent constraint, which ensures that the total cumulative damage of all multi-equal amplitude loads after the transformation is consistent with the total damage of the original load. S1052. Construct equivalent constraints for segmented damage trends. The equivalent constraints for segmented damage trends ensure that the cumulative damage ratio and the gradient trend of damage growth in each amplitude interval are consistent with the corresponding intervals of the vehicle durability variable amplitude load spectrum. S1053. Establish a system of equations based on the total damage equivalent constraint and the segmented damage trend equivalent constraint; S1054. The equation system is solved by iterative method to obtain the precise number of loading cycles corresponding to each equal amplitude load interval.

[0064] Specifically, the total damage equivalence constraint ensures that the overall cumulative damage of all equal-amplitude loads after conversion remains consistent with the total damage of the original loads; the segmented damage trend equivalence constraint ensures that the proportion of cumulative damage in each amplitude interval to the total damage and the gradient trend of damage growth in each interval are completely consistent with the corresponding intervals of the original load spectrum. For example, if the damage in a certain load interval in the original load spectrum accounts for 20% of the total damage, the proportion of damage in the corresponding equal-amplitude load interval after conversion should also remain at 20%; at the same time, the gradient of damage growth with the number of cycles in this interval should be consistent with the original interval.

[0065] Based on the above dual constraints, a system of equations is established, and the precise number of loading cycles corresponding to each level of constant amplitude load is calculated step by step. An iterative method can be used to solve this problem. First, assume a set of iterations and calculate the degree to which the double constraint conditions are satisfied. Then, adjust the number of iterations based on the calculation results until the constraint requirements are met.

[0066] In some optional embodiments, the loading time sequence of multiple equal-amplitude loads is reconstructed for each equal-amplitude load interval to obtain a multi-level layered equal-amplitude load spectrum, which specifically includes: The study analyzes the temporal patterns of large loads in the original random load analysis, such as whether large loads occur in a concentrated manner or are evenly distributed, and the driving conditions during which large loads occur. Simultaneously, it investigates the damage weight distribution pattern to understand how the contribution of different loads to the total damage changes over time.

[0067] Based on the original load timing characteristics and damage weight distribution patterns, the loading order of equal-amplitude loads with determined amplitudes, mean values, and cycle counts is rearranged. For example, according to the frequency and interval of large loads in the original load, the loading order of large loads is rationally arranged in the converted equal-amplitude load spectrum. At the same time, considering the impact of damage accumulation, loads that contribute significantly to the total damage are appropriately dispersed to avoid disordered and random stacking of loads and ensure the consistency of the stress characteristics throughout the vehicle's loading process.

[0068] In some optional embodiments, the method further includes steps for closed-loop verification and iterative correction of conversion errors, as detailed below: The total relative damage error and the segmented damage trend deviation rate for each interval are automatically calculated after the conversion of the load spectrum. The formula for the total relative damage error is: ,in It is the total damage of the converted load spectrum. It represents the total damage of the original load spectrum; the segmented damage trend deviation rate for each interval is the ratio of the difference between the damage growth gradient of each interval after conversion and the damage growth gradient of the original interval to the original gradient.

[0069] Preset accuracy control threshold, such as relative error of total damage Deviation in the proportion of damage in each interval If the calculation error is within the allowable threshold, the final load spectrum is directly output; if the error exceeds the allowable threshold, the system automatically iteratively optimizes the load stratification boundaries, small load reduction factors, and cycle count parameters for each load level, and recalculates until the double-constraint accuracy requirements are met. For example, if the relative error of the total damage is too large, the division boundaries of the load interval or the reduction factors of the small load can be appropriately adjusted, and then the cycle count for each load level can be recalculated, and the error can be checked again.

[0070] The final output is a multi-level, layered constant amplitude durability load spectrum specific to the entire vehicle. The data includes the load amplitude, load mean, number of loading cycles, and complete loading time sequence for each level. The output format should be easy to import into the vehicle durability test bench control system, and can be a text file (such as CSV format) or a dedicated database file format, ensuring that the test bench control system can directly read and execute automated constant amplitude loading tests.

[0071] Reference Figure 2 As an optional implementation, the vehicle vibration platform includes multiple tire vertical vibration devices. Each tire vertical vibration device includes a platform fixing plate 1, a lifting clamp frame 2, a bearing seat 3, a vertical lifting connecting rod 4, a hydraulic drive rod 5, a guide shaft 6, a wheel placement plate 7, and an adjustment limit block 8. The lifting clamp frame 2 is fixed on the platform fixing plate 1. One end of the bearing seat 3 is connected to the hydraulic drive rod 5, and the other end of the bearing seat 3 is connected to the bottom of the vertical lifting connecting rod 4. It is used to drive the vertical lifting connecting rod 4 to vibrate up and down under the lateral loading of the hydraulic drive rod 5. The bottom of the guide shaft 6 is telescopically connected to the lifting clamp frame 2. The top of the vertical lifting connecting rod 4 and the top of the guide shaft 6 are both fixedly connected to the wheel placement plate 7. The adjustment limit block 8 is set on the wheel placement plate 7.

[0072] like Figure 2 The diagram shows a schematic of the tire vertical vibration device provided in an embodiment of the present invention. The vehicle vibration platform of the present invention includes four of these tire vertical vibration devices. When conducting a vehicle durability test, the vehicle is installed on the vibration platform, and the tires are firmly fixed on the platform using a tire fixing fixture to ensure that the vehicle does not shift during loading.

[0073] The converted multi-amplitude load spectrum is imported into the vehicle durability test bench control system, and the loading parameters, such as loading frequency and number of cycles, are set. The vibration platform is started, and the hydraulic drive rod is driven to move laterally according to the loading sequence, thereby performing vertical vibration tests on the entire vehicle.

[0074] During the test, the number of loading cycles and the response data of various parts of the vehicle were recorded. After the test, the recorded data were analyzed to evaluate the fatigue performance of the vehicle under constant amplitude load, and to verify the accuracy of the load spectrum conversion and the reliability of the vibration platform. If the test results deviate from expectations, the load spectrum conversion process or the vibration platform can be further optimized and adjusted.

[0075] Through the above process, a high-precision conversion can be achieved from the original variable amplitude random load spectrum of the whole vehicle to a multi-level layered constant amplitude load spectrum, and an automated constant amplitude loading test can be completed using the whole vehicle vibration platform, providing an important basis for the fatigue performance evaluation and durability design of the whole vehicle.

[0076] The method steps of the embodiments of the present invention have been described above. It can be understood that the embodiments of the present invention achieve high-precision conversion from the original variable amplitude random load spectrum of the whole vehicle to a multi-level layered constant amplitude load spectrum, and apply vertical load excitation to the vehicle under test based on lateral loading using a whole vehicle vibration platform, thereby improving the reliability of whole vehicle durability testing and reducing the cost of whole vehicle durability testing.

[0077] Reference Figure 3 This invention provides an excitation and vibration device based on layered constant amplitude load conversion, comprising: The variable amplitude load spectrum processing module is used to acquire the vehicle durability variable amplitude load spectrum, preprocess the vehicle durability variable amplitude load spectrum, and obtain the vehicle load time series data. The multi-channel load decoupling module is used to perform full-cycle statistics on the time-series load data of the whole vehicle using the three-parameter rainflow counting method, obtain a three-dimensional data matrix corresponding to multiple load cycles, and perform multi-channel load decoupling on the coupled loads of each channel of the whole vehicle to obtain the statistical characteristics of the load across the entire vehicle. The equal-amplitude load interval division module is used to determine the load amplitude probability distribution and the damage contribution ratio of each load interval based on the statistical characteristics of the load across the entire vehicle, and to divide multiple equal-amplitude load intervals based on the load amplitude probability distribution and the damage contribution ratio. The adaptive damage reduction processing module is used to traverse low-amplitude small-load cycles, calculate the cumulative damage ratio of each low-amplitude small-load cycle, and perform damage reduction processing on each low-amplitude small-load cycle according to the cumulative damage ratio and the preset critical value. The loop count calculation module is used to construct the total damage equivalent constraint and the segmented damage trend equivalent constraint. Based on the total damage equivalent constraint and the segmented damage trend equivalent constraint, the precise loading loop count corresponding to each equal amplitude load interval is calculated step by step. The loading timing reconstruction module is used to reconstruct the loading timing of multiple equal-amplitude loads in each equal-amplitude load interval to obtain a multi-level layered equal-amplitude load spectrum. The excitation and vibration module is used to apply lateral loading to the vehicle vibration platform according to the multi-level layered constant amplitude load spectrum, so that the vehicle vibration platform applies vertical load to the vehicle under test fixed on the vehicle vibration platform.

[0078] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0079] Reference Figure 4 This invention provides an electronic device, comprising: At least one processor; At least one memory for storing at least one program; When the above-mentioned at least one program is executed by the above-mentioned at least one processor, the above-mentioned at least one processor implements the above-mentioned excitation and vibration method based on hierarchical equal amplitude load conversion.

[0080] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0081] This invention also provides a computer-readable storage medium storing a processor-executable computer program that, when executed by a processor, implements the above-described excitation and vibration method based on layered constant amplitude load conversion.

[0082] This invention provides a computer-readable storage medium that can execute an excitation and vibration method based on layered equal-amplitude load conversion provided in the method embodiments of this invention. It can execute any combination of the implementation steps of the method embodiments and has the corresponding functions and beneficial effects of the method.

[0083] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described excitation and vibration method based on layered constant amplitude load conversion.

[0084] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0085] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0086] The embodiments described in this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0087] The terms "second," "third," "fourth," etc. (if present) in the specification and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0088] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the aforementioned blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0089] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the aforementioned functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0090] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0091] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0092] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the aforementioned program can be printed, because the aforementioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0093] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0094] In the foregoing description of this specification, references to terms such as "one embodiment," "another embodiment," or "some embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0095] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0096] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for excitation and vibration based on layered constant amplitude load conversion, characterized in that, Includes the following steps: Obtain the vehicle durability variable load spectrum, and preprocess the vehicle durability variable load spectrum to obtain vehicle load time series data; The three-parameter rainflow counting method is used to perform full-cycle statistics on the vehicle load time series data to obtain a three-dimensional data matrix corresponding to multiple load cycles. Multi-channel load decoupling is performed on the coupled loads of each channel of the vehicle to obtain the full-domain load statistical characteristics of the vehicle. The load amplitude probability distribution and the damage contribution ratio of each load interval are determined based on the statistical characteristics of the vehicle's overall load. Multiple equal-amplitude load intervals are then divided based on the load amplitude probability distribution and the damage contribution ratio. Traverse the low-amplitude, low-load cycles, calculate the cumulative damage percentage of each low-amplitude, low-load cycle, and perform damage reduction processing on each low-amplitude, low-load cycle based on the cumulative damage percentage and a preset threshold value. Construct equivalent constraints for total damage and equivalent constraints for segmented damage trends, and calculate the precise number of loading cycles corresponding to each of the equal amplitude load intervals step by step based on the equivalent constraints for total damage and equivalent constraints for segmented damage trends. The loading time sequence of multiple equal amplitude loads is reconstructed for each equal amplitude load interval to obtain a multi-level layered equal amplitude load spectrum. The vehicle vibration platform is laterally loaded according to the multi-level layered equal amplitude load spectrum, so that the vehicle vibration platform applies a vertical load to the vehicle under test fixed on the vehicle vibration platform.

2. The excitation and vibration method based on layered constant amplitude load conversion according to claim 1, characterized in that, The process of obtaining the vehicle durability variable load spectrum and preprocessing the vehicle durability variable load spectrum to obtain vehicle load time series data specifically includes: During the vehicle road durability test, sensors installed at various parts of the vehicle are used to collect the time-domain signal of the original variable amplitude random load with full-domain multi-channel coupling, and the vehicle durability variable amplitude load spectrum is obtained. The vehicle durability variable load spectrum is processed by detrending term removal, abnormal spur removal, channel signal calibration, invalid data segment filtering, and baseline correction to obtain the vehicle load time series data.

3. The excitation and vibration method based on layered constant amplitude load conversion according to claim 1, characterized in that, The process involves performing full-cycle statistical analysis on the vehicle load time-series data using a three-parameter rainflow counting method to obtain a three-dimensional data matrix corresponding to multiple load cycles. Furthermore, multi-channel load decoupling is performed on the coupled loads of each channel of the vehicle to obtain the overall vehicle load statistical characteristics, specifically including: The load amplitude, load mean, and number of cycles corresponding to each load cycle of the vehicle load time series data are obtained by the three-parameter rainflow counting method. The three-dimensional data matrix corresponding to each load cycle is determined based on the load amplitude, the load mean, and the number of cycles. By using matrix decomposition and signal separation, the coupled loads of each channel of the vehicle are decoupled, and the independent load cycles of the body, suspension, chassis and transmission system are obtained. The statistical characteristics of the overall load of the vehicle are determined based on the independent load cycles and the three-dimensional data matrix.

4. The excitation and vibration method based on layered constant amplitude load conversion according to claim 1, characterized in that, The step of determining the load amplitude probability distribution and the damage contribution ratio of each load interval based on the statistical characteristics of the vehicle's overall load, and dividing multiple equal-amplitude load intervals based on the load amplitude probability distribution and the damage contribution ratio, specifically includes: A probability distribution analysis is performed on the statistical characteristics of the vehicle's total load to obtain the probability distribution of the load amplitude. The damage contribution percentage for each load range is calculated based on the Miner criterion. Starting from the maximum load amplitude, the intervals are divided in descending order of the proportion of damage contribution, and the reference amplitude and the original load mean value corresponding to each level of equal amplitude load are determined in turn to obtain multiple equal amplitude load intervals.

5. The excitation and vibration method based on layered constant amplitude load conversion according to claim 1, characterized in that, The process of traversing low-amplitude, low-load cycles, calculating the cumulative damage percentage of each low-amplitude, low-load cycle, and performing damage reduction processing on each low-amplitude, low-load cycle based on the cumulative damage percentage and a preset threshold value specifically includes: Traverse all low-amplitude, low-load cycles and calculate the proportion of cumulative damage of each low-amplitude, low-load cycle to the original total damage according to the Miner criterion to obtain the cumulative damage proportion. When the cumulative damage percentage is greater than or equal to the critical value, the corresponding low-amplitude small load will be cyclically assigned to the corresponding low-level equal-amplitude load range. When the cumulative damage percentage is less than the critical value, the corresponding low-amplitude small load cycle is converted into the number of cycles according to the Miner damage equivalence criterion and then equivalently incorporated into the adjacent upper-level equal-amplitude load interval.

6. The excitation and vibration method based on layered equal-amplitude load conversion according to claim 1, characterized in that, The construction of the total damage equivalent constraint and the segmented damage trend equivalent constraint, and the step-by-step back-calculation of the precise loading cycle number corresponding to each of the equal amplitude load intervals based on the total damage equivalent constraint and the segmented damage trend equivalent constraint, specifically includes: Construct the total damage equivalent constraint, which ensures that the total cumulative damage of all multi-equal amplitude loads after transformation remains consistent with the total damage of the original load; Construct a segmented damage trend equivalent constraint, which makes the cumulative damage ratio and interval damage growth gradient trend corresponding to each amplitude interval consistent with the corresponding interval of the whole vehicle durability variable amplitude load spectrum. A system of equations is established based on the total damage equivalent constraint and the segmented damage trend equivalent constraint; The equations are solved using an iterative method to obtain the precise number of loading cycles corresponding to each of the constant amplitude load intervals.

7. A method for excitation and vibration based on layered constant amplitude load conversion according to any one of claims 1 to 6, characterized in that, The vehicle vibration platform includes multiple tire vertical vibration devices. Each tire vertical vibration device includes a platform fixing plate, a lifting clamp frame, a bearing seat, a vertical lifting connecting rod, a hydraulic drive rod, a guide shaft, a wheel placement plate, and an adjusting limit block. The lifting clamp frame is fixed on the platform fixing plate. One end of the bearing seat is connected to the hydraulic drive rod, and the other end of the bearing seat is connected to the bottom of the vertical lifting connecting rod. The bearing seat is used to drive the vertical lifting connecting rod to vibrate up and down under the lateral loading of the hydraulic drive rod. The bottom of the guide shaft is telescopically connected to the lifting clamp frame. The top of the vertical lifting connecting rod and the top of the guide shaft are both fixedly connected to the wheel placement plate. The adjusting limit block is set on the wheel placement plate.

8. An excitation and vibration device based on layered constant amplitude load conversion, characterized in that, include: The variable amplitude load spectrum processing module is used to acquire the vehicle durability variable amplitude load spectrum, preprocess the vehicle durability variable amplitude load spectrum, and obtain the vehicle load time series data. The multi-channel load decoupling module is used to perform full-cycle statistics on the vehicle load time series data using the three-parameter rainflow counting method to obtain a three-dimensional data matrix corresponding to multiple load cycles, and to perform multi-channel load decoupling on the coupled loads of each channel of the vehicle to obtain the full-domain load statistical characteristics of the vehicle. The equal-amplitude load interval division module is used to determine the load amplitude probability distribution and the damage contribution ratio of each load interval based on the statistical characteristics of the vehicle's overall load, and to divide multiple equal-amplitude load intervals based on the load amplitude probability distribution and the damage contribution ratio. An adaptive damage reduction processing module is used to traverse low-amplitude small-load cycles, calculate the cumulative damage ratio of each low-amplitude small-load cycle, and perform damage reduction processing on each low-amplitude small-load cycle according to the cumulative damage ratio and a preset threshold value. The loop count calculation module is used to construct the total damage equivalent constraint and the segmented damage trend equivalent constraint, and to calculate the precise loading loop count corresponding to each of the equal amplitude load intervals step by step based on the total damage equivalent constraint and the segmented damage trend equivalent constraint. The loading timing reconstruction module is used to reconstruct the loading timing of multiple equal-amplitude loads in each equal-amplitude load interval to obtain a multi-level layered equal-amplitude load spectrum. The excitation and vibration module is used to apply lateral loading to the vehicle vibration platform according to the multi-level layered equal amplitude load spectrum, so that the vehicle vibration platform applies a vertical load to the vehicle under test fixed on the vehicle vibration platform.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements an excitation and vibration method based on layered constant amplitude load conversion as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements an excitation and vibration method based on layered constant amplitude load conversion as described in any one of claims 1 to 7.

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