Accelerated random vibration spectrum determination method based on road load spectrum
By using an accelerated random vibration spectrum determination method based on road load spectrum, the high cost and long cycle of vehicle structural component reliability verification were solved, achieving efficient and accurate bench testing, reducing testing costs and improving the accuracy and comparability of test results.
Patent Information
- Application Number
- CN202411645157.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-18
- Publication Date
- 2026-05-19
AI Technical Summary
In the existing technology, the reliability verification methods for vehicle structural components have problems such as high cost, long cycle, and large difference between test results and the reliability of the whole vehicle. Furthermore, the existing bench test methods need to be improved in terms of accuracy and efficiency.
An accelerated random vibration spectrum determination method based on road load spectrum is adopted. By selecting, editing and processing road load spectrum data, the impact response spectrum and fatigue damage spectrum under various working conditions are calculated. Combining fatigue accumulation theory and damage equivalence principle, the accelerated random vibration spectrum is generated, and ERS calculation is performed to verify its correctness and rationality.
It achieves an effective link between bench testing and road testing, improves testing accuracy and efficiency, reduces testing costs, has strong applicability, and the test results are quantifiable and highly comparable, reducing the impact of driver operation and road surface differences.
Smart Images
Figure CN122062860A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle assembly vibration fatigue testing technology, specifically to a method for determining accelerated random vibration spectrum based on road load spectrum. Background Technology
[0002] Vehicle structural components play a crucial role in supporting and suspending the vehicle, and their structural reliability is critical to vehicle driving safety. However, most vehicle structural components are non-standard designs, lacking specific testing standards to verify their reliability. Among current verification methods, laboratory bench testing is widely used due to its good consistency of test results and short sample rectification cycle. Determining the test load is the primary issue in bench testing, as accurate test loads can truly reflect the stress situation on the entire vehicle. Currently, for verifying the reliability of structural components, some test loads directly use road load spectra collected from full-vehicle road testing, conducting tests through road simulation technology. This method has a strong correlation with the full-vehicle road reliability, resulting in high accuracy and strong comparability of test results. However, the investment and operating costs of road simulation testing equipment are relatively high, and the testing cycle is also relatively long. Another type of test load is derived from the reliability standards of the components supported or suspended by the structural components. This method has a relatively short testing cycle and lower investment and operating costs for testing equipment. However, during the testing process, it is found that the obtained test results differ significantly from the full-vehicle reliability test results, and the lateral comparability of the test results is poor. Therefore, there is an urgent need for an accurate, efficient, and low-cost testing method to verify the reliability of vehicle structural components.
[0003] For example, patent application CN201710981361.2, entitled "A method for accelerating the random vibration fatigue of electric vehicle battery packs based on real road spectra," discloses a method that specifically includes the following steps:
[0004] (1) Road load spectrum acquisition and analysis;
[0005] (2) Calculation of fatigue damage spectrum of battery pack throughout its entire life cycle;
[0006] (3) Accelerated vibration fatigue of battery pack, i.e., the establishment of laboratory standards.
[0007] This method, based on the measured road spectrum of electric vehicles, conducts accelerated vibration fatigue testing of electric vehicle battery packs on laboratory benches for different installation positions of battery packs of different models. It solves the problem of the single evaluation standard for electric vehicle battery packs. However, the road spectrum working conditions are singular, and the influence of various noises such as differences in driver operation and road surface on the road spectrum is not considered. Therefore, the accuracy of the accelerated random spectrum of the bench test needs to be improved. Summary of the Invention
[0008] To address the problems existing in the prior art, this invention provides a method for determining the accelerated random vibration spectrum based on the road load spectrum.
[0009] The technical solution adopted by this invention to solve its technical problem is: a method for determining the accelerated random vibration spectrum based on road load spectrum, comprising the following steps:
[0010] S1: Select road load spectrum data;
[0011] S2: Edit and process road load spectrum data;
[0012] S3: Select the effective data of the i-th cycle of each characteristic road surface under full load, half load and no load conditions as the original data for accelerated random vibration spectrum calculation, and calculate the impact response spectrum and fatigue damage spectrum of the i-th cycle data of each characteristic road surface.
[0013] S4: The fatigue damage spectrum statistical values of the road load spectrum of the entire characteristic pavement under the working conditions are obtained by summing the fatigue damage spectrum statistical values of the unloaded, half-loaded and fully loaded working conditions respectively.
[0014] S5: The maximum value of the impact response spectrum under no-load, half-load, and full-load conditions is obtained to obtain the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic pavement under the condition.
[0015] S6: According to the fatigue damage accumulation theory, the fatigue damage spectrum of the overall target mileage is obtained by accumulating the fatigue damage spectrum statistics of the entire characteristic road surface under the no-load, half-load and full-load conditions by adding the number of cycles of no-load, half-load and full-load conditions.
[0016] S7: The maximum value of the impact response spectrum of the characteristic road surface under no-load, half-load and full-load conditions is obtained to obtain the maximum value of the impact response spectrum of the overall target mileage.
[0017] S8: Based on the principle of damage equivalence, a random vibration spectrum of equal duration to the total target mileage is synthesized using the fatigue damage spectrum of the total target mileage. This spectrum is then accelerated to obtain an accelerated random vibration spectrum. An appropriate safety factor value is selected based on the importance of the sample. The random vibration spectrum is calculated using the following formula:
[0018]
[0019] In the formula, k is the safety factor, ∑FDS(f n ) is the fatigue damage spectrum of the total target mileage, K is the stiffness of the SDOF system, T is the duration of the input acceleration PSD, and b and C are the fatigue parameters of the SN curve.
[0020] S9: Perform ERS calculation on the generated accelerated random vibration spectrum. Compare the calculation results with the maximum values of the fatigue damage spectrum and the impact response spectrum of the overall target mileage to verify the correctness and rationality of the accelerated random vibration spectrum. ERS calculation formula:
[0021]
[0022] In the formula: It refers to the magnitude of the acceleration PSD curve at fn; Q is the dynamic amplification factor.
[0023] Preferably, the selection of road load spectrum data involves directly selecting the acceleration data of a single fixed point or approximately a single fixed point as the input data for calculating the accelerated random vibration spectrum; for samples with multiple fixed points, considering the rationality of the existence of maximum vibration, the acceleration data of the fixed point with the largest RMS value is selected as the input data for calculating the accelerated random vibration spectrum.
[0024] Preferably, the road load spectrum editing process involves preprocessing the acceleration data, segmenting it according to road surface type, deleting transitional road surfaces, recording the time and mileage of each characteristic road surface segment, and performing high-pass filtering on the processed acceleration data. The upper and lower limits of the filtering are determined based on the installation position of the sample on the vehicle and the operating frequency of the test equipment.
[0025] Preferably, the cumulative fatigue damage spectrum statistics under no-load, half-load, and full-load conditions are calculated by first calculating the fatigue damage spectrum statistics of i-cycle data for each characteristic road surface under full-load conditions, then calculating the fatigue damage spectrum statistics of i-cycle data for each characteristic road surface under half-load conditions, and finally calculating the fatigue damage spectrum statistics of i-cycle data for each characteristic road surface under no-load conditions. Under the same conditions, the fatigue damage spectrum statistics of each characteristic road segment are accumulated according to the proportional coefficient required by the test to obtain the fatigue damage spectrum statistics of the entire characteristic road surface road load spectrum under the same conditions. This can eliminate the influence of noise such as driver operation differences and road surface differences on the accuracy of acceleration random vibration spectrum data.
[0026] Preferably, the maximum value of the impact response spectrum for the unloaded, half-loaded, and fully loaded conditions is obtained by sequentially encapsulating the maximum value of the impact response spectrum of each characteristic road surface i-cycle data under the fully loaded condition, thus obtaining the maximum value of the impact response spectrum of the entire characteristic road surface load spectrum under the fully loaded condition; under the half-loaded condition, the maximum value of the impact response spectrum of each characteristic road surface i-cycle data is obtained by sequentially encapsulating the maximum value of the impact response spectrum of the entire characteristic road surface load spectrum under the half-loaded condition; and under the unloaded condition, the maximum value of the impact response spectrum of the entire characteristic road surface load spectrum is obtained by sequentially encapsulating the maximum value of the impact response spectrum of each characteristic road surface i-cycle data.
[0027] The present invention has the following beneficial effects:
[0028] 1) This method is based on the road load spectrum of the whole vehicle, which can truly reflect the vibration of the structural components on the actual road surface. It realizes the effective correlation between bench test and road test or actual user operating conditions. The test accuracy is high, the test results are quantifiable and highly comparable, and it is not affected by the inherent frequency of the sample system itself.
[0029] 2) This method, based on the fatigue cumulative damage theory and fatigue damage equivalence theory, transforms the time-domain road load spectrum of the total target mileage into a random vibration spectrum of equal duration, and accelerates it to obtain an accelerated random vibration spectrum. This significantly shortens the test cycle and product rectification cycle, and improves test efficiency.
[0030] 3) The test equipment used in this method is generally an electric vibration test system, which greatly reduces the test cost compared to road simulation test equipment;
[0031] 4) This method can be applied to both bench tests and virtual tests, making it highly applicable. Attached Figure Description
[0032] Figure 1 This is a flowchart of an embodiment of the present invention. Detailed Implementation
[0033] The technical solutions of the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.
[0034] like Figure 1 As shown, a method for determining the accelerated random vibration spectrum based on road load spectrum includes the following steps:
[0035] S1: Selection of Road Load Spectrum Data: For specimens with a single fixed point or approximately a single fixed point, the acceleration data of that point is directly selected as the input data for the accelerated vibration spectrum calculation. For specimens with multiple fixed points, considering the rationality of the existence of maximum vibration, the acceleration data of the fixed point with the largest RMS value is selected as the input data for the accelerated vibration spectrum calculation.
[0036] S2: Road load spectrum editing and processing: preprocessing the acceleration data such as deburring and drift removal; segmenting according to road type, deleting transitional road surfaces, and recording the time and mileage of each characteristic road surface segment; performing high-pass filtering on the processed acceleration data, with the upper and lower limits of the filter determined according to the installation position of the sample on the vehicle and the operating frequency of the vibration testing equipment.
[0037] S3: Select the effective data of i cycles of each characteristic road surface under three working conditions of full load, half load and no load as the raw data for accelerated random vibration spectrum calculation, and calculate the impact response spectrum and fatigue damage spectrum of i cycles of data of each characteristic road surface (i is the number of cycles of road load spectrum acquisition, recommended value is 2-4).
[0038] S4: Accumulate the fatigue damage spectrum statistics for the unloaded, half-loaded, and fully loaded conditions to obtain the fatigue damage spectrum statistics for the entire characteristic pavement load spectrum under that condition. First, calculate the fatigue damage spectrum statistics for each characteristic pavement in the i-th cycle under the fully loaded condition, then calculate the fatigue damage spectrum statistics for each characteristic pavement in the i-th cycle under the half-loaded condition, and finally calculate the fatigue damage spectrum statistics for each characteristic pavement in the i-th cycle under the unloaded condition. Under the same condition, accumulate the fatigue damage spectrum statistics for each characteristic road segment according to the required proportionality coefficient to obtain the fatigue damage spectrum statistics for the entire characteristic pavement load spectrum under that condition.
[0039] S5: The maximum impact response spectrum values for unloaded, half-loaded, and fully loaded conditions are used to obtain the maximum impact response spectrum value of the entire characteristic pavement load spectrum under these conditions. Under full load, the maximum impact response spectrum values for each characteristic pavement (i-cycle data) are sequentially encapsulated to obtain the maximum impact response spectrum value of the entire characteristic pavement load spectrum under full load. Under half load, the maximum impact response spectrum values for each characteristic pavement (i-cycle data) are sequentially encapsulated to obtain the maximum impact response spectrum value of the entire characteristic pavement load spectrum under half load. Under unloaded conditions, the maximum impact response spectrum values for each characteristic pavement (i-cycle data) are sequentially encapsulated to obtain the maximum impact response spectrum value of the entire characteristic pavement load spectrum under unloaded conditions.
[0040] S6: According to the fatigue damage accumulation theory, the fatigue damage spectrum of the overall target mileage is obtained by accumulating the fatigue damage spectrum statistics of the entire characteristic road surface under the no-load, half-load and full-load conditions by adding the number of cycles of no-load, half-load and full-load conditions.
[0041] S7: The maximum value of the impact response spectrum of the characteristic road surface under no-load, half-load and full-load conditions is obtained to obtain the maximum value of the impact response spectrum of the overall target mileage.
[0042] S8: Based on the principle of damage equivalence, the fatigue damage spectrum of the total target mileage is used to synthesize a random vibration spectrum of the same duration as the total target mileage. Then, it is accelerated to become an accelerated random vibration spectrum. The appropriate safety factor value is selected according to the importance of the sample. The random vibration spectrum is calculated as shown in Formula 1.
[0043]
[0044] In the formula, k is the safety factor, ∑FDS(f n() represents the fatigue damage spectrum of the total target mileage, K is the stiffness of the SDOF system, T is the duration of the input acceleration PSD, and b and C are the fatigue parameters of the SN curve.
[0045] The random vibration spectrum of the overall target mileage and the time period is generally not used for time bench vibration tests due to the long time period. In actual calculations, the accelerated random vibration spectrum is directly synthesized from the fatigue damage spectrum of the overall target mileage.
[0046] S9: Verification of accelerated random vibration spectrum on the test bench. Perform ERS calculation on the generated accelerated random vibration spectrum as shown in Formula 2. Compare the calculation results with the maximum values of the fatigue damage spectrum and the impact response spectrum of the overall target mileage to verify the correctness and rationality of the accelerated random vibration spectrum. That is, the fatigue damage spectrum obtained by the accelerated random vibration spectrum calculation should be basically consistent with the fatigue damage spectrum of the overall target mileage, and the acceleration coefficient should be less than 1.5. In addition, the characteristics of the test specimen and the actual load-bearing conditions of the test equipment should also be considered. Repeat S8 and S9 until the accelerated random vibration spectrum that meets the requirements is obtained.
[0047]
[0048] In the formula: It refers to the magnitude of the acceleration PSD curve at fn; Q is the dynamic amplification factor.
[0049] This invention proposes the concept of a frequency domain acceleration coefficient to quantitatively evaluate the rationality of accelerated random vibration spectra. Through experimental design and verification, it is found that the acceleration coefficient range is less than 1.5, thus improving experimental efficiency. It also introduces the concept of FDS statistical values to eliminate the influence of various noises, such as driver operation differences and road surface variations, on road load spectrum data, thereby improving the accuracy of experimental data. Furthermore, considering three operating conditions—empty, half-loaded, and fully loaded—closer to actual user conditions, further enhances the accuracy of experimental data.
[0050] Example
[0051] like Figure 1 As shown, the specific implementation of the present invention is illustrated using the method for determining the accelerated random vibration spectrum of a mudguard bracket as an example, and the commercial software nCode is used to complete the task.
[0052] S1: Road load spectrum data selection: Find the acceleration data of the vehicle frame fixing point collected by the mudguard bracket at a test site in China, and select the effective acceleration data of 3 revolutions under no-load, half-load and full-load conditions as the input data to determine the acceleration random vibration spectrum.
[0053] S2: Road Load Spectrum Data Editing and Processing
[0054] (1) Preprocess the three valid data under the selected no-load, half-load and full-load conditions to remove zero drift and burrs.
[0055] (2) Under full load conditions, the effective data from the three laps were segmented into 12 characteristic pavement load spectra according to pavement type. Transitional pavements were deleted, and the time and mileage of the 12 types of pavement were recorded and named. Under half load conditions, the effective data from the three laps were segmented into 12 characteristic pavement load spectra according to pavement type. Transitional pavements were deleted, and the time and mileage of the 12 types of pavement were recorded and named. Under no-load conditions, the effective data from the three laps were segmented into 12 characteristic pavement load spectra according to pavement type. Transitional pavements were deleted, and the time and mileage of the 12 types of pavement were recorded and named.
[0056] (3) Bandpass filtering was performed on the 12 types of road surface features. Considering the installation position of the bracket on the vehicle and the working frequency of the electric vibration test system, the filtering range was (5-100)Hz.
[0057] S3: Calculate the impact response spectrum and fatigue damage spectrum of 12 characteristic road sections under no-load, half-load and full-load conditions.
[0058] S4: Accumulate the fatigue damage spectrum statistics of the unloaded, half-loaded and fully loaded conditions to obtain the fatigue damage spectrum statistics of the road load spectrum of the entire characteristic pavement under this condition.
[0059] (1) Calculate the average of the fatigue damage spectrum of the three load spectra of the first type of pavement under full load condition, then calculate the variance of the fatigue damage spectrum of the three load spectra of the first type of pavement under full load condition, and then sum the average value and variance of the fatigue damage spectrum to obtain the statistical value of the fatigue damage spectrum. The calculation of the statistical value of the fatigue damage spectrum of the other 11 types of pavement is similar.
[0060] (2) The fatigue damage spectrum statistics of the 12 characteristic road load spectra under full load conditions are accumulated proportionally to obtain the fatigue damage spectrum statistics of the entire characteristic road load spectrum under full load conditions.
[0061] (3) Calculate the average of the fatigue damage spectrum of the three load cycles of the first type of pavement under half-load conditions, then calculate the variance of the fatigue damage spectrum of the three load cycles of the first type of pavement under half-load conditions, and then sum the average value and variance of the fatigue damage spectrum to obtain the statistical value of the fatigue damage spectrum. The calculation of the statistical value of the fatigue damage spectrum of the other 11 types of pavement is similar.
[0062] (4) The fatigue damage spectrum statistics of the 12 characteristic road load spectra under half-load conditions are accumulated proportionally to obtain the fatigue damage spectrum statistics of the entire characteristic road load spectrum under half-load conditions.
[0063] (5) Calculate the average of the fatigue damage spectrum of the three load cycles of the first type of pavement under no-load conditions, then calculate the variance of the fatigue damage spectrum of the three load cycles of the first type of pavement under no-load conditions, and then sum the average value and variance of the fatigue damage spectrum to obtain the statistical value of the fatigue damage spectrum. The calculation of the statistical value of the fatigue damage spectrum of the other 11 types of pavement is similar.
[0064] (6) The fatigue damage spectrum statistics of the 12 characteristic road load spectra under no-load conditions are accumulated proportionally to obtain the fatigue damage spectrum statistics of the entire characteristic road load spectrum under no-load conditions.
[0065] S5: The maximum value of the impact response spectrum under no-load, half-load, and full-load conditions is obtained to obtain the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic pavement under the condition.
[0066] (1) Find the maximum value of the impact response spectrum of the first type of road surface under full load conditions. The maximum value of the impact response spectrum of the first type of road surface under full load conditions is obtained. The maximum value of the impact response spectrum of the other 11 types of road surfaces is encapsulated in the same way.
[0067] (2) Encapsulate the maximum value of the impact response spectrum of 12 characteristic pavements under full load conditions to obtain the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic pavement under full load conditions.
[0068] (3) The maximum value of the impact response spectrum of the first type of road surface under half-load conditions is obtained by encapsulating the three-cycle data of the first type of road surface under half-load conditions. The maximum value of the impact response spectrum of the other 11 types of road surfaces is encapsulated in the same way.
[0069] (4) Encapsulate the maximum value of the impact response spectrum of 12 characteristic pavements under half-load conditions to obtain the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic pavement under half-load conditions.
[0070] (5) The maximum value of the impact response spectrum of the first type of road surface under no-load conditions is obtained by encapsulating the three-cycle data of the first type of road surface under no-load conditions. The maximum value of the impact response spectrum of the other 11 types of road surfaces is encapsulated in the same way.
[0071] (6) Encapsulate the maximum value of the impact response spectrum of 12 characteristic pavements under no-load conditions to obtain the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic pavement under no-load conditions.
[0072] S6: Based on the fatigue damage accumulation theory, the fatigue damage spectrum of the overall target mileage is obtained by accumulating the fatigue damage spectrum statistics of the entire characteristic road surface under the no-load, half-load and full-load conditions by adding the number of cycles.
[0073] (1) Based on the ratio of no-load, half-load and full-load to 1:1:8 and the target mileage of 12,000 kilometers, the number of working cycle cycles is calculated as follows: 202 cycles for no-load, 202 cycles for half-load, and 1516 cycles for full-load.
[0074] (2) The fatigue damage spectrum of the total target mileage is obtained by summing the fatigue damage spectrum statistics of 202 laps under no-load conditions, 202 laps under half-load conditions, and 1818 laps under full-load conditions.
[0075] S7: Encapsulate the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic road surface under no-load, half-load and full-load conditions, and obtain the maximum value of the impact response spectrum of the overall target.
[0076] S8: Considering the actual load on the mudguard bracket and the fatigue strength of the material, a safety factor of 1 is selected, and the accelerated random vibration spectrum is synthesized using the fatigue damage spectrum of the overall target mileage according to the damage equivalence principle.
[0077] S9: Bench acceleration random vibration spectrum verification until a bench acceleration vibration spectrum that meets the requirements is obtained.
[0078] (1) Perform ERS calculation on the synthesized accelerated random vibration spectrum to obtain the limit response spectrum and fatigue damage spectrum of the synthesized accelerated random vibration spectrum.
[0079] (2) Compare the fatigue damage spectrum obtained from the accelerated random vibration spectrum with the fatigue damage spectrum of the total target mileage. The two should be basically consistent.
[0080] (3) Compare the limit response spectrum curve obtained by accelerating random vibration spectrum calculation with the maximum value curve of impact response spectrum of total target mileage, and compare the distribution of the maximum value in the low frequency (generally within 30Hz). The maximum value of the maximum value curve of impact response at the same frequency should be as large as possible than the maximum value of the limit response spectrum curve.
[0081] (4) Calculate the mean of the limit response spectrum curve and the maximum value curve of the impact response spectrum, calculate the acceleration coefficient, and ensure that the acceleration coefficient is less than 1.5.
[0082] (5) In addition, the characteristics of the test specimen and the actual load of the electric vibration system should also be considered. Repeat steps S8 and S9 until the ZYX triaxial accelerated random vibration spectrum that meets the requirements is obtained.
[0083] The accelerated random vibration spectrum of the mudguard bracket determined according to the above steps is imported into the electric vibration testing system to carry out vibration fatigue testing of the mudguard bracket, and to assess whether its vibration fatigue performance meets the design requirements.
[0084] Figure 1In this context, SRS represents the impact response spectrum, FDS represents the fatigue damage spectrum, i represents the number of road load spectrum acquisition cycles, and n represents the number of characteristic road surfaces.
[0085] This invention is not limited to the above-described embodiments. Anyone should know that any structural changes made under the guidance of this invention, and any technical solutions that are the same as or similar to this invention, fall within the protection scope of this invention.
[0086] The technologies, shapes, and structures not described in detail in this invention are all known technologies.
Claims
1. A method for determining the accelerated random vibration spectrum based on road load spectrum, characterized in that, Includes the following steps: S1: Select road load spectrum data; S2: Edit and process road load spectrum data; S3: Select the effective data of the i-th cycle of each characteristic road surface under full load, half load and no load conditions as the original data for accelerated random vibration spectrum calculation, and calculate the impact response spectrum and fatigue damage spectrum of the i-th cycle data of each characteristic road surface. S4: The fatigue damage spectrum statistical values of the road load spectrum of the entire characteristic pavement under the working conditions are obtained by summing the fatigue damage spectrum statistical values of the unloaded, half-loaded and fully loaded working conditions respectively. S5: The maximum value of the impact response spectrum under no-load, half-load, and full-load conditions is obtained to obtain the maximum value of the impact response spectrum of the road load spectrum of the entire characteristic pavement under the condition. S6: According to the fatigue damage accumulation theory, the fatigue damage spectrum of the overall target mileage is obtained by accumulating the fatigue damage spectrum statistics of the entire characteristic road surface under the no-load, half-load and full-load conditions by adding the number of cycles of no-load, half-load and full-load conditions. S7: The maximum value of the impact response spectrum of the characteristic road surface under no-load, half-load and full-load conditions is obtained to obtain the maximum value of the impact response spectrum of the overall target mileage. S8: Based on the principle of damage equivalence, a random vibration spectrum of equal duration to the total target mileage is synthesized using the fatigue damage spectrum of the total target mileage. This spectrum is then accelerated to obtain an accelerated random vibration spectrum. An appropriate safety factor value is selected based on the importance of the sample. The random vibration spectrum is calculated using the following formula: In the formula, k is the safety factor, ∑FDS(f n ) is the fatigue damage spectrum of the total target mileage, K is the stiffness of the SDOF system, T is the duration of the input acceleration PSD, and b and C are the fatigue parameters of the SN curve. S9: Perform ERS calculation on the generated accelerated random vibration spectrum. Compare the calculation results with the maximum values of the fatigue damage spectrum and the impact response spectrum of the overall target mileage to verify the correctness and rationality of the accelerated random vibration spectrum. ERS calculation formula: In the formula: Q refers to the magnitude of the acceleration PSD curve at point fn; Q is the dynamic amplification factor.
2. The method for determining the accelerated random vibration spectrum based on the road load spectrum according to claim 1, characterized in that, The selection of road load spectrum data involves directly selecting the acceleration data of a single fixed point or approximately a single fixed point as the input data for accelerating random vibration spectrum calculation. For samples with multiple fixed points, considering the rationality of the existence of maximum vibration, the acceleration data of the fixed point with the largest RMS value is selected as the input data for accelerating random vibration spectrum calculation.
3. The method for determining the accelerated random vibration spectrum based on the road load spectrum according to claim 1, characterized in that, The road load spectrum editing process involves preprocessing the acceleration data, segmenting it according to road surface type, deleting transitional road surfaces, recording the time and mileage of each characteristic road surface segment, and performing high-pass filtering on the processed acceleration data. The upper and lower limits of the filtering are determined based on the installation position of the sample on the vehicle and the operating frequency of the test equipment.
4. The method for determining the accelerated random vibration spectrum based on the road load spectrum according to claim 1, characterized in that, The cumulative fatigue damage spectrum statistics under no-load, half-load, and full-load conditions are calculated by first calculating the fatigue damage spectrum statistics of i-cycle data for each characteristic pavement under full-load conditions, then calculating the fatigue damage spectrum statistics of i-cycle data for each characteristic pavement under half-load conditions, and finally calculating the fatigue damage spectrum statistics of i-cycle data for each characteristic pavement under no-load conditions. Under the same conditions, the fatigue damage spectrum statistics of each characteristic road segment are accumulated according to the proportional coefficient required by the test to obtain the fatigue damage spectrum statistics of the entire characteristic pavement road load spectrum under the same conditions.
5. The method for determining the accelerated random vibration spectrum based on the road load spectrum according to claim 1, characterized in that, The maximum impact response spectrum values for the unloaded, half-loaded, and fully loaded conditions are obtained by first encapsulating the maximum impact response spectrum values of each characteristic road surface i-cycle data under the fully loaded condition, thus obtaining the maximum impact response spectrum value of the entire characteristic road surface load spectrum under the fully loaded condition; then, under the half-loaded condition, encapsulating the maximum impact response spectrum values of each characteristic road surface i-cycle data, thus obtaining the maximum impact response spectrum value of the entire characteristic road surface load spectrum under the half-loaded condition; finally, under the unloaded condition, encapsulating the maximum impact response spectrum values of each characteristic road surface i-cycle data, thus obtaining the maximum impact response spectrum value of the entire characteristic road surface load spectrum under the unloaded condition.