A fatigue acceleration detection method and system for high fatigue resistance cast wheels

Abstract

The present invention relates to the technical field of material fatigue performance testing, and in particular to a fatigue acceleration detection method and system for a highly fatigue-resistant cast wheel. The method comprises: generating a dynamic load spectrum including a multi-axial composite load based on the actual operating conditions of the target cast wheel; applying the dynamic load spectrum to the target cast wheel for accelerated testing, and monitoring the dynamic strain response of the target cast wheel surface and interior in real time based on a distributed sensing array; establishing a damage accumulation calculation model using the loading parameters of the dynamic load spectrum as additional correlation conditions, and calculating the equivalent fatigue damage accumulation value based on the dynamic strain response; when the equivalent fatigue damage accumulation value reaches a preset damage threshold, determining that the target cast wheel has reached the end of its fatigue life, wherein the damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating conditions. The present invention effectively solves the problems of multi-axial load simulation distortion, incomplete damage monitoring, and low life prediction accuracy in traditional fatigue testing.

Description

Technical Field

[0001] The present invention relates to the technical field of material fatigue performance testing, and in particular to a fatigue acceleration detection method and system for a high fatigue resistance cast wheel. Background Art

[0002] In the fatigue performance assessment of high-fatigue-resistant cast wheels, accelerated testing technology is a key means of shortening R&D cycles and ensuring service safety. Traditional methods often use constant amplitude or simplified uniaxial load spectra for fatigue testing, relying on single-point strain gauges or visual inspection of localized cracks to determine failure, and using linear cumulative damage models to predict service life.

[0003] However, existing technologies have limitations in practical application. Traditional fatigue damage monitoring solutions are unable to support the high-precision fatigue-resistant design of existing cast wheels. Single-point or single-modal sensing monitoring struggles to capture complex dynamic strains, making it impossible to accurately determine the location of fatigue damage or cracks. Simplified uniaxial load spectra based on dynamic response cannot replicate the complex loads experienced by cast wheels in actual service, leading to increased errors in the life prediction of high-fatigue-resistant cast wheels. Furthermore, existing accelerated testing requires hundreds to thousands of hours to maintain consistent damage mechanisms, making it impossible to meet the rapid, iterative verification requirements for cast wheels made of new materials.

[0004] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present disclosure and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0005] The present invention provides a fatigue acceleration detection method and system for a high fatigue resistance cast wheel, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A fatigue acceleration detection method for a high fatigue resistance cast wheel, the method comprising:

[0008] Generate a dynamic load spectrum including multi-axial composite loads according to the actual operating conditions of the target cast wheel;

[0009] Applying the dynamic load spectrum to the target casting wheel to perform an accelerated test, and monitoring the dynamic strain response of the surface and interior of the target casting wheel in real time based on a distributed sensing array;

[0010] Establishing a damage accumulation calculation model using the loading parameters of the dynamic load spectrum as additional correlation conditions, and calculating an equivalent fatigue damage accumulation value based on the dynamic strain response;

[0011] When the equivalent fatigue damage accumulation value reaches a preset damage threshold, it is determined that the target cast wheel has reached the end of fatigue life, wherein the damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating condition.

[0012] Furthermore, a dynamic load spectrum including multi-axial composite loads is generated, including:

[0013] Obtaining radial, tangential and axial multi-axis vibration signals and material stress concentration coefficients of the target casting wheel during actual operation;

[0014] performing load characteristic analysis on the multi-axis vibration signal to extract a plurality of three-dimensional load segments;

[0015] In combination with the material stress concentration factor, converting the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load;

[0016] The damage contribution rate of each of the three-dimensional load segments is calculated, and the loading sequence and the number of cycles of the equivalent symmetrical cyclic load are optimized according to the damage contribution rate to generate the dynamic load spectrum.

[0017] Furthermore, converting the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load comprises:

[0018] Based on the material stress concentration factor, correcting the local stress amplitude of the asymmetric cyclic load in the three-dimensional load segment;

[0019] Establishing a stress-life correlation relationship, and converting the corrected local stress amplitude into the local stress amplitude of the equivalent symmetrical cyclic load;

[0020] Perform multi-axis synchronization calibration on the equivalent symmetrical cyclic load to confirm that the loading phases of the radial, tangential, and axial loads are consistent with the timing relationship in the actual working conditions;

[0021] According to a preset fatigue damage screening threshold, the three-dimensional load segments in the equivalent symmetric cyclic load whose local stress amplitude is lower than the fatigue damage screening threshold are screened to generate the equivalent symmetric cyclic load that only retains high damage contribution loads.

[0022] Furthermore, calculating the damage contribution rate of each of the three-dimensional load segments includes:

[0023] Determining, based on the material fatigue performance parameters of the target casting wheel, the influence weight coefficient of the local stress amplitude and the number of cycles in each of the three-dimensional load segments on the fatigue life;

[0024] Correcting the local stress amplitude of each three-dimensional load segment according to the material stress concentration factor, and calculating a corrected single-cycle equivalent damage value;

[0025] Counting the number of cycles of each three-dimensional load segment within the total test time, and multiplying the single-cycle equivalent damage value by the number of cycles to obtain a cumulative damage value of each three-dimensional load segment;

[0026] The cumulative damage value of each of the three-dimensional load segments is divided by the sum of the cumulative damage values of all the three-dimensional load segments to obtain the damage contribution rate of each load segment.

[0027] Furthermore, calculating the equivalent fatigue damage accumulation value based on the dynamic strain response includes:

[0028] Extracting an effective frequency band from the dynamic strain signal collected by the distributed sensing array to generate a strain fluctuation component;

[0029] Obtaining the local strain energy density distributed at key parts of the target casting wheel according to the strain fluctuation component;

[0030] Inputting the local strain energy density into the damage accumulation calculation model, and calculating the equivalent damage increment of a single cycle in combination with the stress state correction coefficient under the current loading parameters;

[0031] The equivalent damage increments of all loading cycles are accumulated to generate the equivalent fatigue damage accumulation value updated in real time, wherein the accumulation process introduces a multiaxial fatigue coupling factor to correct the synergistic damage effect of strains in different directions.

[0032] Furthermore, obtaining the local strain energy density distributed at key parts of the target casting wheel includes:

[0033] Performing multi-band signal decomposition on the strain fluctuation component, extracting the main frequency band signal associated with fatigue damage evolution, and generating a transient strain amplitude;

[0034] According to the nonlinear relationship between stress and strain of the material of the target casting wheel, the transient strain amplitude is converted into local stress fluctuation data;

[0035] Calculating the strain energy density of a single cycle based on the local stress fluctuation data;

[0036] reconstructing the strain energy density of uncovered areas by interpolation based on the spatial position information of the distributed sensing array;

[0037] The region where the strain energy density peak exceeds the preset damage threshold is identified and marked as a key region, and the local strain energy density is generated.

[0038] Furthermore, the multi-axial fatigue coupling factor includes:

[0039] Based on the local strain energy density, the independent influence weights of radial, tangential and axial strain components on the total damage are quantified respectively;

[0040] Calibrate the synergistic damage effect under the combination of radial, tangential and axial strain directions to obtain synergistic effect data;

[0041] Constructing a multi-axis coupling model based on the independent influence weights and the synergistic effect data and calculating and outputting a multi-axis fatigue coupling factor, wherein the multi-axis fatigue coupling factor value is dynamically adjusted according to the strain direction combination and the phase difference;

[0042] The multiaxial fatigue coupling factor is embedded in the cumulative calculation process of the equivalent damage increment in real time, specifically, the equivalent damage increment of each loading cycle is multiplied by the multiaxial fatigue coupling factor corresponding to the current cycle, so as to correct the synergistic damage effect.

[0043] Furthermore, the dynamic strain response of the surface and interior of the target casting wheel is monitored in real time based on a distributed sensing array, including:

[0044] Pre-embedding a sensor array in a stress concentration area on the surface of the target casting wheel to generate the distributed sensor array;

[0045] Collecting the original signal of the distributed sensing array and performing temperature drift compensation to extract the damage characteristic frequency band;

[0046] Performing time domain alignment and spatial registration on the original signal to establish a coordinate mapping relationship between the sensor position and the three-dimensional model of the target casting wheel;

[0047] Associating the coordinate mapping relationship with the damage characteristic frequency band to generate the dynamic strain response and mark potential damage hotspots;

[0048] The dynamic strain response is transmitted to the damage accumulation calculation model in real time, and a timestamp is recorded to match the current loading parameters.

[0049] A fatigue acceleration detection system for a high fatigue resistance cast wheel, the system comprising:

[0050] The load analysis module generates a dynamic load spectrum including multi-axial composite loads based on the actual operating conditions of the target cast wheel;

[0051] The strain monitoring module applies a dynamic load spectrum to the target casting wheel for accelerated testing, and monitors the dynamic strain response of the target casting wheel surface and interior in real time based on a distributed sensing array;

[0052] The damage calculation module establishes a damage accumulation calculation model using the loading parameters of the dynamic load spectrum as additional correlation conditions, and calculates the equivalent fatigue damage accumulation value based on the dynamic strain response;

[0053] The fatigue judgment module determines that the target cast wheel has reached the end of its fatigue life when the equivalent fatigue damage accumulation value reaches the preset damage threshold. The damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating conditions.

[0054] Furthermore, the load analysis module includes:

[0055] The data acquisition unit acquires the radial, tangential and axial multi-axis vibration signals and material stress concentration coefficient of the target casting wheel during actual operation;

[0056] Feature analysis unit, which performs load feature analysis on multi-axis vibration signals and extracts multiple three-dimensional load segments;

[0057] Equivalent conversion unit, combined with the material stress concentration factor, converts the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load;

[0058] The spectrum generation unit calculates the damage contribution rate of each three-dimensional load segment, optimizes the loading sequence and cycle number distribution of the equivalent symmetrical cyclic load according to the damage contribution rate, and generates a dynamic load spectrum.

[0059] The technical solution of the present invention can achieve the following technical effects:

[0060] By generating dynamic load spectra and integrating multimodal sensing, high-precision reproduction of complex working conditions and early capture of microcracks are achieved, thereby improving the accuracy of prediction of the initiation location of cracks or fatigue damage. Combined with the multi-axis coupled damage model, the life prediction error is reduced, while the test cycle is shortened, thereby improving the R&D efficiency and service reliability assessment capabilities of high-fatigue-resistant cast wheels.

[0061] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0063] Figure 1 The figure is a flow chart of a fatigue acceleration detection method for a high fatigue resistance cast wheel;

[0064] Figure 2 Schematic diagram of the process for generating dynamic load spectrum;

[0065] Figure 3 Schematic diagram of the process for calculating the equivalent fatigue damage accumulation value;

[0066] Figure 4 Schematic diagram of the process for monitoring dynamic strain response. DETAILED DESCRIPTION

[0067] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0068] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0069] Embodiment 1;

[0070] like Figure 1 As shown, the present application provides a fatigue acceleration detection method for a high fatigue resistance cast wheel, the method comprising:

[0071] S10: generating a dynamic load spectrum including multi-axial composite loads according to the actual operating conditions of the target cast wheel;

[0072] S20: applying a dynamic load spectrum to the target casting wheel for accelerated testing, and monitoring the dynamic strain response of the target casting wheel surface and interior in real time based on the distributed sensing array;

[0073] S30: A damage accumulation calculation model is established with the loading parameters of the dynamic load spectrum as additional correlation conditions, and the equivalent fatigue damage accumulation value is calculated based on the dynamic strain response;

[0074] S40: When the equivalent fatigue damage accumulation value reaches a preset damage threshold, it is determined that the target cast wheel has reached the end of fatigue life, wherein the damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating condition.

[0075] Specifically, a dynamic load spectrum containing multiaxial composite loads is generated based on the actual operating conditions of the target cast wheel. This process analyzes the cast wheel's operating condition data, extracts load characteristics in multiple directions, and performs multi-dimensional characteristic analysis of the load based on the material's stress concentration factor to obtain a dynamic load spectrum suitable for the target cast wheel. The generated dynamic load spectrum is then applied to the target cast wheel for accelerated testing. During the accelerated test, a distributed sensing array is used to monitor the real-time strain response of the target cast wheel's surface and interior. The data collected by the sensors can be used to obtain information on the strain changes of the cast wheel under dynamic loads. Based on the loading parameters of the dynamic load spectrum and the real-time dynamic strain response data, a damage accumulation calculation model is established. This model uses the loading parameters of the dynamic load spectrum as additional correlation conditions and calculates the equivalent fatigue damage accumulation value of the cast wheel based on the strain response data. When the calculated equivalent fatigue damage accumulation value reaches the preset damage threshold, the target cast wheel is determined to have reached the end of its fatigue life. During this process, the damage evolution law in the accelerated test is kept consistent with the damage mechanism of the target cast wheel's actual operating conditions to ensure the reliability of the test results.

[0076] Through the technical solution of the present invention, high-precision reproduction of complex working conditions and early capture of microcracks are achieved, thereby improving the accuracy of prediction of crack or fatigue damage initiation locations; combined with the multi-axis coupled damage model, the life prediction error is reduced, and the test cycle is shortened, thereby improving the research and development efficiency of high fatigue-resistant cast wheels and the service reliability assessment capability.

[0077] Further, if Figure 2 As shown, a dynamic load spectrum containing multiaxial combined loads is generated, including:

[0078] Obtain the radial, tangential and axial multi-axis vibration signals and material stress concentration factors of the target casting wheel during actual operation;

[0079] Perform load feature analysis on multi-axis vibration signals and extract multiple three-dimensional load segments;

[0080] Combined with the material stress concentration factor, the asymmetric cyclic load in the three-dimensional load segment is converted into an equivalent symmetric cyclic load;

[0081] The damage contribution rate of each three-dimensional load segment is calculated, and the loading sequence and cycle number distribution of the equivalent symmetric cyclic load are optimized according to the damage contribution rate to generate a dynamic load spectrum.

[0082] As a preferred embodiment of the above, in the actual operating environment of the cast wheel, a distributed sensor array (such as optical fiber sensors, strain gauges, etc.) is used to collect multi-axis vibration signals of the cast wheel in real time. These signals include radial vibration signals of the cast wheel along the spoke direction; tangential vibration signals of the cast wheel in the tangential direction; and axial vibration signals of the cast wheel along the axial direction. Sensors should be arranged at key parts of the cast wheel (such as the rim, spoke joints, axles, etc.) to accurately obtain vibration data in various directions. At the same time, the material stress concentration coefficient of the cast wheel is collected. This coefficient can be obtained by finite element analysis (FEA) simulation calculation to reflect the stress concentration degree of each part of the cast wheel under different loading conditions, especially the stress concentration. The acquisition of stress concentration coefficient can be accurately calibrated by the geometric shape, material properties and actual load conditions of the cast wheel for subsequent damage analysis and load conversion; the collected multi-axis vibration signal is subjected to frequency domain analysis (such as fast Fourier transform (FFT)) or time domain feature extraction to extract the characteristic frequency bands in the load signal. These characteristic frequency bands are usually closely related to the actual working state of the cast wheel and can reflect its vibration characteristics. Through signal analysis, a series of three-dimensional load fragments are extracted. These load fragments are obtained by combining vibration signals in different directions (radial, tangential, axial), which are three-dimensional information of load changes over time. Each load fragment corresponds to a specific time period. The strain response in all directions of the casting wheel can be analyzed by time-frequency analysis methods such as wavelet transform to identify the non-stationary features in the load signal and extract these multi-axis load fragments in time-frequency-space. The asymmetric cyclic load is further analyzed based on the three-dimensional load fragments. Asymmetric cyclic load means that in each loading cycle, the forward and reverse loads are asymmetric, resulting in an uneven distribution of cyclic loads. The load balance conversion method is used to convert these asymmetric cyclic loads into equivalent symmetric cyclic loads in combination with the material stress concentration coefficient. The load areas that contribute more to material damage during load fluctuations are identified based on the stress concentration coefficient. The asymmetric loads in these areas are corrected to balance their forward and reverse load amplitudes. value; through the balanced load form, an equivalent symmetrical cyclic load is constructed to more accurately reflect the damage generated in actual work; using the equivalent symmetrical cyclic load as the load input, combined with fatigue damage models (such as Miner's rule, Coffin-Manson model, etc.), the damage contribution rate of each three-dimensional load segment is calculated. The damage contribution rate refers to the contribution of each load segment to the total fatigue damage of the cast wheel. Through the stress-strain curve and fatigue crack growth model, the damage accumulation effect of different load segments in the cast wheel material can be evaluated. The calculation of the damage contribution rate takes into account the combined effect of stresses in different directions, as well as the influence of the amplitude and frequency of each load cycle on the fatigue performance of the material;Based on the damage contribution rate of each three-dimensional load segment, the load segments in the entire load spectrum are optimized and sorted. This optimization process aims to place load segments with higher damage contributions in priority loading positions to avoid unnecessary damage to the material caused by excessive and repeated loading. The loading sequence of the load segments is adjusted according to the damage contribution rate, so that the loading sequence matches the stress sequence under actual working conditions of the cast wheel. This method can simulate a more realistic working environment and improve the accuracy of fatigue acceleration testing. By analyzing the damage contribution of each load segment, the number of cycles for each load segment is reasonably allocated to ensure that the fatigue damage of each part is fully tested and avoid overloading or underloading of certain segments. Based on the optimized load sequence and cycle allocation, a dynamic load spectrum is generated. This spectrum includes the amplitude and frequency of the multi-axial composite load at different time periods, which meets the fatigue acceleration testing requirements of the actual operating conditions of the cast wheel.

[0083] Furthermore, the asymmetric cyclic loads in the 3D load segment are converted into equivalent symmetric cyclic loads, including:

[0084] Based on the material stress concentration factor, the local stress amplitude of asymmetric cyclic load in the three-dimensional load segment is corrected;

[0085] Establish a stress-life correlation relationship and convert the corrected local stress amplitude into the local stress amplitude of equivalent symmetrical cyclic loading;

[0086] Perform multi-axis synchronization calibration on equivalent symmetrical cyclic loads to confirm that the loading phases of radial, tangential, and axial loads are consistent with the timing relationships in actual working conditions;

[0087] According to the preset fatigue damage screening threshold, three-dimensional load segments with local stress amplitudes lower than the fatigue damage screening threshold in the equivalent symmetric cyclic load are screened to generate an equivalent symmetric cyclic load that only retains high damage contribution loads.

[0088] As a preferred embodiment of the above, in actual working conditions, stress concentration may occur in different areas of the target casting wheel, especially in places with complex structures and irregular surfaces. The distribution of load will be affected by the material stress concentration coefficient. Therefore, for each three-dimensional load segment, it is necessary to first calculate the material stress concentration coefficient. This coefficient reflects the amplification effect of the local stress at that location relative to the average stress. Based on the material stress concentration coefficient, the local stress amplitude in the three-dimensional load segment is corrected to make it more consistent with the actual stress distribution. The correction of the local stress amplitude is obtained by multiplying the stress concentration coefficient by the stress amplitude of the original load to obtain the corrected local stress amplitude. After the local stress amplitude is corrected , the next step is to convert these local stress amplitudes into local stress amplitudes of equivalent symmetrical cyclic loads. This process needs to be carried out according to the stress-life correlation relationship, which is usually completed through the stress-life curve of the material. The stress-life correlation relationship is based on experimental data or fatigue data in the material manual, which describes the life of the material under different stress amplitudes. Through this curve, the corrected local stress amplitude can be converted into the corresponding local stress amplitude of the equivalent symmetrical cyclic load, and the equivalent load that meets the fatigue test standard can be obtained; in the accelerated test of high fatigue resistance cast wheels, the load of the cast wheel is usually multi-axial composite, including radial, tangential and axial loads. Therefore, in order to ensure the accuracy of the test results, multiple Axis synchronization calibration, that is, calibrating the loading phases of these loads in different axial directions. First, based on the equivalent symmetrical cyclic load data obtained in the three-dimensional load segment, the load timing is aligned to ensure that the loading phases in each direction are consistent with the timing relationship in the actual working conditions during the experiment. Specifically, the phases of radial, tangential and axial loads must be precisely synchronized to ensure that the loads in different directions can simulate the loading process in actual use. Because in actual operation, the loads in each direction usually act alternately, and multi-axis synchronization calibration ensures that the timing of load loading during the test is highly consistent with the actual working conditions, avoiding the influence of errors on the test results; the fatigue damage screening threshold is obtained by fatigue testing the cast wheel material. The threshold is determined by fatigue performance analysis. Usually, this threshold is the minimum value that the local stress amplitude can withstand when the influence of fatigue damage is small. After obtaining the corrected equivalent symmetrical cyclic load, the local stress amplitude in each load segment needs to be screened. For those load segments whose local stress amplitude is lower than the preset fatigue damage screening threshold, they are removed from the load sequence because the contribution of these loads to the fatigue damage of the cast wheel is very small and does not affect the fatigue life prediction. Finally, the generated equivalent symmetrical cyclic load only contains those load segments that have a significant contribution to fatigue damage. Through this screening process, the test will focus on the main loads that affect fatigue damage, which improves the test efficiency and ensures the accuracy of the results.

[0089] Furthermore, the damage contribution rate of each 3D load segment is calculated, including:

[0090] Based on the material fatigue performance parameters of the target cast wheel, the weight coefficient of the influence of local stress amplitude and number of cycles on fatigue life in each three-dimensional load segment is determined;

[0091] Correct the local stress amplitude of each three-dimensional load segment according to the material stress concentration factor and calculate the corrected single-cycle equivalent damage value;

[0092] Count the number of cycles of each three-dimensional load segment within the total test time, multiply the equivalent damage value of a single cycle by the number of cycles to obtain the cumulative damage value of each three-dimensional load segment;

[0093] The cumulative damage value of each three-dimensional load segment is divided by the sum of the cumulative damage values of all three-dimensional load segments to obtain the damage contribution rate of each load segment.

[0094] As a preferred embodiment of the above, it is first necessary to obtain the fatigue performance parameters of the material used in the target casting wheel, including the material's SN curve (stress-cycle number curve), which describes the relationship between the material's fatigue life and the number of cycles under different stress amplitudes. Other fatigue performance parameters that may be involved include the material's yield strength, tensile strength, elastic modulus, etc. Based on these parameters, for each three-dimensional load segment, a weight coefficient of the influence of the local stress amplitude and the number of cycles on the fatigue life is calculated. Each three-dimensional load segment has a local stress amplitude and a corresponding number of cycles. The role of the weight coefficient is to reflect the relative contribution of each load segment to the total fatigue life. Generally, the weight coefficient can be calculated using a fatigue life model (such as Miner's rule). The local stress amplitude and the number of cycles are combined to derive the contribution of the segment to fatigue damage. In actual working conditions, the local stress of the casting wheel material may be concentrated due to factors such as structural defects, geometric shape or surface irregularities. Therefore, it is necessary to introduce a stress concentration coefficient to correct the local stress amplitude in each three-dimensional load segment. The finite element analysis (FEA) method or experimental determination of the material under specific conditions can be used. The stress concentration factor under the structure is calculated. The local stress amplitude is corrected by the stress concentration factor to obtain the corrected local stress amplitude. Based on the corrected local stress amplitude and the material fatigue life curve (SN curve), the single-cycle equivalent damage value of each three-dimensional load segment can be calculated. This represents the degree of damage to the material caused by the stress amplitude during a single load cycle. For each three-dimensional load segment, the number of cycles within the total test duration needs to be counted. The number of cycles for each load segment can be obtained through experimental data or simulation calculations, or this information can be obtained in real time through a data recording system. The single-cycle equivalent damage value of each three-dimensional load segment is multiplied by the number of cycles for that load segment to obtain the cumulative damage value of that load segment. The cumulative damage value reflects the degree of fatigue damage accumulated in that load segment during the test. The cumulative damage values of all three-dimensional load segments are summed up. For each three-dimensional load segment, its cumulative damage value is divided by the sum of the cumulative damage values of all load segments to obtain the damage contribution rate of that load segment. The damage contribution rate indicates the relative contribution of each load segment to the fatigue damage process.

[0095] Further, if Figure 3 As shown in Figure 2, the equivalent fatigue damage accumulation value is calculated based on the dynamic strain response, including:

[0096] Extracting effective frequency bands from dynamic strain signals collected by distributed sensing arrays to generate strain fluctuation components;

[0097] According to the strain fluctuation component, the local strain energy density of the key parts of the target casting wheel is obtained;

[0098] The local strain energy density is input into the damage accumulation calculation model, and the equivalent damage increment of a single cycle is calculated by combining the stress state correction coefficient under the current loading parameters;

[0099] The equivalent damage increments of all loading cycles are accumulated to generate a real-time updated equivalent fatigue damage accumulation value. The accumulation process introduces a multiaxial fatigue coupling factor to correct the synergistic damage effect of strains in different directions.

[0100] As a preferred embodiment of the above, during the fatigue acceleration test of the high fatigue resistance cast wheel, a distributed strain sensor array (such as a fiber grating sensor, a strain gauge, etc.) is used to collect the dynamic strain signal of the cast wheel in real time. The sensor array is arranged at different parts of the cast wheel, and can capture the strain response of each part of the cast wheel. The original dynamic strain signal is filtered in the frequency domain to extract the effective frequency band of interest. The effective frequency band is usually related to the fatigue behavior of the cast wheel under actual working conditions. These frequency bands can reflect the dynamic strain fluctuation of the cast wheel. Fast Fourier transform (FFT) or other spectrum analysis technology is used to extract each frequency band from the collected strain signal. After extracting the effective strain fluctuation components, the local strain energy density of the key parts of the casting wheel is further calculated based on the strain fluctuation data. The strain energy density is the energy stored in the material due to strain per unit volume, which is usually used to describe the deformation behavior of the material under stress. The strain energy density formula (for example, energy density is proportional to the square of the strain) is used to calculate the local strain energy density of different key parts of the casting wheel (such as the rim, spokes, and wheel-axle contact parts) according to the dynamic strain fluctuation components of different parts. The local strain energy density is input into a damage accumulation calculation model and combined with the current loading conditions. The damage accumulation calculation model can be based on the classic Miner's rule or a more complex multi-axial fatigue damage model. These models describe how the material accumulates damage in each loading cycle under stress. Considering that the cast wheel will experience a variety of complex loading conditions in actual use (such as the combined effect of radial, tangential and axial loads), it is necessary to correct the damage increment according to the current stress state correction factor. The stress state correction factor can adjust the damage calculation according to the loading direction, stress amplitude and material properties to ensure the accuracy of the damage increment; by accumulating each loading cycle The equivalent damage increment in the accumulator is used to generate a real-time updated equivalent fatigue damage accumulation value. This process is a gradual updating process. By accumulating the damage increment of each loading cycle, the fatigue damage accumulation of the cast wheel during the entire test process can be tracked in real time. Since the cast wheel is subjected to multi-directional loads, the synergistic damage effect of strains in different directions must also be considered when calculating the cumulative damage. In order to accurately correct this effect, a multi-axial fatigue coupling factor needs to be introduced. This factor considers the coupling effect of fatigue damage of the cast wheel material in various directions under the action of loads in various directions, ensuring that loads in all directions can be correctly reflected in the total damage calculation.

[0101] Furthermore, the local strain energy density of the key parts of the target casting wheel is obtained, including:

[0102] Perform multi-band signal decomposition on the strain fluctuation component, extract the main frequency band signal associated with fatigue damage evolution, and generate the transient strain amplitude;

[0103] According to the nonlinear relationship between stress and strain of the target casting wheel material, the transient strain amplitude is converted into local stress fluctuation data;

[0104] Calculate the strain energy density of a single cycle based on local stress fluctuation data;

[0105] Based on the spatial position information of the distributed sensing array, the strain energy density of the uncovered area is reconstructed by interpolation;

[0106] The areas where the strain energy density peak exceeds the preset damage threshold are identified and marked as key areas, and local strain energy density is generated.

[0107] As a preferred embodiment of the above, the dynamic strain signal obtained by the distributed strain sensor array is subjected to preliminary filtering processing to extract the effective strain fluctuation component, and the multi-band signal decomposition technology (such as wavelet transform, wavelet packet decomposition or empirical mode decomposition EMD) is used to decompose the strain fluctuation component into multiple frequency bands. Based on the material fatigue behavior database or prior test results, the main frequency band signal most relevant to the evolution of fatigue damage is identified. The main frequency band usually contains the main stress frequency components of the initiation and expansion of microcracks in the casting wheel during service. The main frequency band signal is subjected to envelope analysis or instantaneous amplitude extraction to generate a transient strain amplitude representing the local high-frequency response characteristics, which is used for subsequent nonlinear stress analysis. Force conversion; Considering that the stress-strain relationship of high-strength cast wheel materials (such as high-strength aluminum alloys, magnesium alloys or special steels) has obvious nonlinear characteristics, especially in the plastic deformation stage, the transient strain amplitude is input into the material constitutive model (such as Ramberg-Osgood model, Chaboche model, etc.), combined with the nonlinear stress-strain parameters of the material at room temperature or high temperature, the corresponding local stress fluctuation data is calculated. This conversion process retains the nonlinear characteristics in the strain response, making the estimation of stress fluctuation closer to the actual loading condition, and improving the accuracy of subsequent energy calculation; according to the theoretical strain energy density expression, the local stress and local strain fluctuation are multiplied and integrated to obtain the single stress The strain energy density value absorbed by unit volume of material during the load cycle can be integrated in a local area in combination with the finite element method or analytical approximation to calculate the fatigue energy input of the cast wheel under the current stress state; due to the limited number of sensor array points, the actual strain energy density can only be obtained at some nodes. In order to realize fatigue analysis of the entire cast wheel surface or volume, it is necessary to perform spatial interpolation reconstruction on the area where no sensors are installed. Using the sensor spatial layout data and the local strain energy density distribution, an interpolation algorithm (such as inverse distance weighted method IDW, radial basis function interpolation RBF or Krige interpolation) is used to reconstruct data in the blank area. The interpolation process needs to take into account the geometric characteristics of the cast wheel structure and the stress field distribution. The system takes into account coupling factors such as regularity and thermal gradient to improve the physical rationality and accuracy of the interpolation results, and finally forms a local strain energy density spatial distribution map covering the entire wheel; combined with the material fatigue threshold strain energy density or the preset damage threshold determined by the experiment, the strain energy density spatial distribution map is analyzed point by point. When the strain energy density peak value in a certain local area exceeds the threshold continuously or frequently, the system automatically identifies the area as a potential fatigue-sensitive area or key fatigue part, and marks, numbers and tracks these areas for subsequent fatigue damage accumulation, crack prediction and structural life assessment. At the same time, it outputs local strain energy density report data containing indicators such as the coordinates of key parts, strain energy density peak value, and duration.

[0108] Furthermore, the multiaxial fatigue coupling factors include:

[0109] Based on the local strain energy density, the independent influence weights of radial, tangential and axial strain components on the total damage are quantified respectively;

[0110] Calibrate the synergistic damage effect under the combination of radial, tangential and axial strain directions to obtain synergistic effect data;

[0111] A multi-axial coupling model is constructed based on the independent influence weights and synergistic effect data, and the multi-axial fatigue coupling factor is calculated and output. The multi-axial fatigue coupling factor value is dynamically adjusted with the strain direction combination and phase difference;

[0112] The multiaxial fatigue coupling factor is embedded in the cumulative calculation process of the equivalent damage increment in real time. Specifically, the equivalent damage increment of each loading cycle is multiplied by the multiaxial fatigue coupling factor corresponding to the current cycle to correct the synergistic damage effect.

[0113] As a preferred embodiment of the above, based on the local strain energy density obtained in the above steps, the strain components of the casting wheel in different directions (radial, tangential, and axial) are calculated respectively. The fatigue damage potential in each direction can be obtained through the energy density of these strain components. The component analysis method is used, for example, based on the uniaxial fatigue model (such as the SN curve method) or fracture mechanics theory, to calculate the damage degree in each direction respectively. The higher the damage degree, the greater the contribution of the strain in this direction to the overall fatigue damage. Based on these separately calculated damage degrees, the independent influence weights of the radial, tangential, and axial strain components on the total damage are quantified. These weights reflect the independent contribution of different strain directions to the fatigue damage of the casting wheel, such as based on The strain energy density in each direction is compared, and the proportion of energy in each direction to the total energy is calculated by integration, so as to obtain the weight of different directions. Since the strains in each direction of the casting wheel are not independent under multi-axial stress, but there is interaction or synergistic damage effect. In order to quantify this synergistic effect, it is necessary to calibrate the mutual influence of damage under different direction combinations through experiments. Fatigue tests under different loading modes (such as radial loading and tangential loading at the same time, or axial and radial loading) are carried out using a fatigue test bench or finite element analysis (FEA). The strain data under each loading mode is recorded, and the corresponding fatigue damage increment is calculated. The fatigue damage increment is calculated by fitting the experimental data or based on the multi-axial fatigue damage theory ( Such as Manson-Coffin model, Fatemi-Socie criterion, etc.), to obtain the synergistic damage effect under each direction combination. The synergistic effect data can include stress and strain coupling coefficients of different direction combinations, as well as the comprehensive influence of these combinations on the damage increment; According to the independent influence weights and synergistic effect data, a multi-axial fatigue coupling model can be constructed. The model describes how the strain components in different directions couple with each other and affect the overall fatigue damage. The multi-axial fatigue coupling model is based on the damage coupling relationship in each direction. Through the weighted average method, tensor model or other appropriate mathematical models, the fatigue damage in each direction is comprehensively considered. In this model, a multi-axial fatigue coupling is defined. A factor is dynamically adjusted with different strain direction combinations and phase differences (i.e., the relative time lag between strain waveforms in different directions). Specifically, changes in loading direction and phase difference will affect the coupling effect of fatigue damage, thereby affecting the final fatigue life prediction. For example, when radial loading and tangential loading act simultaneously, the rate of local damage generation may be accelerated due to the coupling effect of stress directions, so the value of the coupling factor will be appropriately increased. The calculated multiaxial fatigue coupling factor is embedded in the cumulative calculation process of the equivalent damage increment in real time. This process is dynamically calculated according to the current loading conditions in each loading cycle, including the equivalent damage increment calculated from the strain component in each loading cycle.The equivalent damage increment of each loading cycle is multiplied by the multiaxial fatigue coupling factor corresponding to the current cycle. This method can correct the impact of the multiaxial strain synergistic damage effect on the overall fatigue damage and improve the calculation accuracy of the equivalent damage increment. The damage increment and coupling factor of each cycle are updated as the loading state and direction change, ensuring the real-time and accurate calculation of the damage increment.

[0114] Further, if Figure 4 As shown, the dynamic strain response of the target casting wheel surface and interior is monitored in real time based on the distributed sensing array, including:

[0115] A sensor array is embedded in the stress concentration area on the surface of the target casting wheel to generate a distributed sensor array;

[0116] Collect the original signal of the distributed sensor array and compensate for temperature drift, and extract the damage characteristic frequency band;

[0117] Perform time domain alignment and spatial registration on the original signal to establish the coordinate mapping relationship between the sensor position and the three-dimensional model of the target casting wheel;

[0118] Correlate the coordinate mapping relationship with the damage characteristic frequency band to generate dynamic strain response and mark potential damage hotspots;

[0119] The dynamic strain response is transmitted to the damage accumulation calculation model in real time and the timestamp is recorded to match the current loading parameters.

[0120] As a preferred embodiment of the above, multiple strain sensor arrays are embedded in the surface stress concentration areas of the high fatigue resistance cast wheel (such as the areas prone to fatigue damage such as the rim, the contact areas between the spokes and the axle). The sensor array can choose fiber optic Bragg grating sensors (FOGs), strain gauges, piezoelectric sensors, etc., and the appropriate sensor type is selected according to the actual use environment. The sensor array layout should ensure that it can cover the key parts of the surface and interior of the cast wheel and can capture the strain response of the cast wheel under working conditions. These sensors should have real-time data acquisition capabilities and be able to resist environmental influences such as temperature fluctuations to ensure data reliability. For the interior of the cast wheel, it is possible to consider using embedded sensors or non-contact monitoring through advanced sensor fusion technology. Measurement (such as using acoustic emission sensors to monitor crack propagation, etc.); the sensor array collects dynamic strain signals on the surface and inside of the target casting wheel in real time. The original signal needs to be collected by the signal processing circuit and preliminary data cleaning is performed to remove noise. Since the strain sensor may experience temperature drift in a high temperature environment, it is necessary to use a temperature sensor to monitor the ambient temperature in real time or the temperature compensation function of the sensor itself to correct the strain signal to eliminate the error caused by temperature. The spectrum analysis of the collected original signal is performed to extract the damage characteristic frequency bands related to fatigue damage. These frequency bands usually include the frequency components related to strain fluctuations and material fatigue damage during the working process of the casting wheel. Wavelet transform, Fourier transform (FFT) and other technologies are used to perform the spectrum analysis. Perform signal decomposition to find the main frequency band of damage evolution; since different positions on the casting wheel surface may have different dynamic responses, it is necessary to align the signals collected by all sensors in the time domain. Through time domain alignment, the errors caused by signal propagation delay of different sensors can be eliminated, ensuring that the data of multiple sensors are consistent at the same time. According to the three-dimensional geometric model of the casting wheel, a coordinate mapping relationship is established for each sensor. This mapping relationship can be obtained through CAD model or based on three-dimensional scanning technology. Using this coordinate mapping relationship, the sensor data can be matched one by one with the actual physical position of the casting wheel. Using three-dimensional space reconstruction technology (such as alignment based on point cloud data), the signal position of the sensor array is accurately mapped to the casting wheel. In the three-dimensional wheel model, the accurate correspondence of spatial information is ensured. The mapped coordinate relationship is associated with the extracted damage characteristic frequency band to generate a dynamic strain response diagram based on time and space. This diagram reflects the strain conditions of sensors at different locations in a specific frequency band. Based on the dynamic strain response diagram, the strain fluctuations in each area are further analyzed to identify potential damage hotspots. These hotspots usually correspond to areas of stress concentration on the surface or inside the cast wheel, such as the rim and spoke joints. They may be the source of cracks, fatigue damage, or other structural problems. Using threshold detection technology, a damage threshold is set (obtained through experimental calibration). When the dynamic strain response of a certain area exceeds the threshold, the system automatically marks the area as a potential damage hotspot.The dynamic strain response (including strain fluctuations, damage hotspot locations, and other data) is transmitted in real time to the damage accumulation calculation model. This model updates the damage status of the cast wheel based on the actual loading conditions and real-time data. Each acquired data point is time-stamped to ensure timing matching with the current loading parameters (such as loading frequency and amplitude). This allows for real-time tracking of cast wheel fatigue damage and timely identification of potential structural problems.

[0121] Embodiment 2:

[0122] Based on the same inventive concept as the fatigue acceleration detection method of a high fatigue resistance cast wheel in the aforementioned embodiment, the present invention also provides a fatigue acceleration detection system for a high fatigue resistance cast wheel, the system comprising:

[0123] The load analysis module generates a dynamic load spectrum including multi-axial composite loads based on the actual operating conditions of the target cast wheel;

[0124] The strain monitoring module applies a dynamic load spectrum to the target casting wheel for accelerated testing, and monitors the dynamic strain response of the target casting wheel surface and interior in real time based on a distributed sensing array;

[0125] The damage calculation module establishes a damage accumulation calculation model using the loading parameters of the dynamic load spectrum as additional correlation conditions, and calculates the equivalent fatigue damage accumulation value based on the dynamic strain response;

[0126] The fatigue judgment module determines that the target cast wheel has reached the end of its fatigue life when the equivalent fatigue damage accumulation value reaches the preset damage threshold. The damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating conditions.

[0127] The above-mentioned adjustment system in the present invention can be effectively implemented, and the technical effects that can be achieved are as described in the above-mentioned embodiments, which will not be repeated here.

[0128] Furthermore, the load analysis module includes:

[0129] The data acquisition unit acquires the radial, tangential and axial multi-axis vibration signals and material stress concentration coefficient of the target casting wheel during actual operation;

[0130] Feature analysis unit, which performs load feature analysis on multi-axis vibration signals and extracts multiple three-dimensional load segments;

[0131] Equivalent conversion unit, combined with the material stress concentration factor, converts the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load;

[0132] The spectrum generation unit calculates the damage contribution rate of each three-dimensional load segment, optimizes the loading sequence and cycle number distribution of the equivalent symmetrical cyclic load according to the damage contribution rate, and generates a dynamic load spectrum.

[0133] Similarly, the above-mentioned optimization schemes for the system can also respectively achieve the corresponding optimization effects of the method in Example 1, which will not be repeated here.

[0134] Although the present application has been described with reference to specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and drawings are merely illustrative of the present application as defined herein and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, the present application is intended to include such modifications and variations as fall within the scope of the present application and its equivalents.

Claims

1. A fatigue acceleration detection method for a high fatigue resistance cast wheel, characterized in that: The method comprises: Generate a dynamic load spectrum including multi-axial composite loads according to the actual operating conditions of the target cast wheel; Applying the dynamic load spectrum to the target casting wheel to perform an accelerated test, and monitoring the dynamic strain response of the surface and interior of the target casting wheel in real time based on a distributed sensing array; Establishing a damage accumulation calculation model using the loading parameters of the dynamic load spectrum as additional correlation conditions, and calculating an equivalent fatigue damage accumulation value based on the dynamic strain response; When the equivalent fatigue damage accumulation value reaches a preset damage threshold, it is determined that the target cast wheel has reached the end of fatigue life, wherein the damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating condition; Calculating an equivalent fatigue damage accumulation value based on the dynamic strain response, including: Extracting an effective frequency band from the dynamic strain signal collected by the distributed sensing array to generate a strain fluctuation component; Obtaining the local strain energy density distributed at key parts of the target casting wheel according to the strain fluctuation component; Inputting the local strain energy density into the damage accumulation calculation model, and calculating the equivalent damage increment of a single cycle in combination with the stress state correction coefficient under the current loading parameters; Accumulating the equivalent damage increments of all loading cycles to generate the equivalent fatigue damage accumulation value updated in real time, wherein the accumulation process introduces a multiaxial fatigue coupling factor to correct the synergistic damage effect of strains in different directions; Obtaining the local strain energy density distributed at key locations of the target casting wheel includes: Performing multi-band signal decomposition on the strain fluctuation component, extracting the main frequency band signal associated with fatigue damage evolution, and generating a transient strain amplitude; According to the nonlinear relationship between stress and strain of the material of the target casting wheel, the transient strain amplitude is converted into local stress fluctuation data; Calculating the strain energy density of a single cycle based on the local stress fluctuation data; reconstructing the strain energy density of uncovered areas by interpolation based on the spatial position information of the distributed sensing array; Identifying and marking the area where the strain energy density peak exceeds the preset damage threshold as a key part, and generating the local strain energy density; The multiaxial fatigue coupling factor includes: Based on the local strain energy density, the independent influence weights of radial, tangential and axial strain components on the total damage are quantified respectively; Calibrate the synergistic damage effect under the combination of radial, tangential and axial strain directions to obtain synergistic effect data; Constructing a multi-axis coupling model based on the independent influence weights and the synergistic effect data and calculating and outputting a multi-axis fatigue coupling factor, wherein the multi-axis fatigue coupling factor value is dynamically adjusted according to the strain direction combination and the phase difference; The multiaxial fatigue coupling factor is embedded in the cumulative calculation process of the equivalent damage increment in real time, specifically, the equivalent damage increment of each loading cycle is multiplied by the multiaxial fatigue coupling factor corresponding to the current cycle, so as to correct the synergistic damage effect.

2. The fatigue acceleration detection method for a high fatigue resistance cast wheel according to claim 1, characterized in that: Generate dynamic load spectra with combined multiaxial loading, including: Obtaining radial, tangential and axial multi-axis vibration signals and material stress concentration coefficients of the target casting wheel during actual operation; performing load characteristic analysis on the multi-axis vibration signal to extract a plurality of three-dimensional load segments; In combination with the material stress concentration factor, converting the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load; The damage contribution rate of each of the three-dimensional load segments is calculated, and the loading sequence and the number of cycles of the equivalent symmetrical cyclic load are optimized according to the damage contribution rate to generate the dynamic load spectrum.

3. The fatigue acceleration detection method for a high fatigue resistance cast wheel according to claim 2, characterized in that: Converting the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load includes: Based on the material stress concentration factor, correcting the local stress amplitude of the asymmetric cyclic load in the three-dimensional load segment; Establishing a stress-life correlation relationship, and converting the corrected local stress amplitude into the local stress amplitude of the equivalent symmetrical cyclic load; Perform multi-axis synchronization calibration on the equivalent symmetrical cyclic load to confirm that the loading phases of the radial, tangential, and axial loads are consistent with the timing relationship in the actual working conditions; According to a preset fatigue damage screening threshold, the three-dimensional load segments in the equivalent symmetric cyclic load whose local stress amplitude is lower than the fatigue damage screening threshold are screened to generate the equivalent symmetric cyclic load that only retains high damage contribution loads.

4. The fatigue acceleration detection method for a high fatigue resistance cast wheel according to claim 2, characterized in that: Calculating the damage contribution rate of each of the three-dimensional load segments, including: Determining, based on the material fatigue performance parameters of the target casting wheel, the influence weight coefficient of the local stress amplitude and the number of cycles in each of the three-dimensional load segments on the fatigue life; Correcting the local stress amplitude of each three-dimensional load segment according to the material stress concentration factor, and calculating a corrected single-cycle equivalent damage value; Counting the number of cycles of each three-dimensional load segment within the total test time, and multiplying the single-cycle equivalent damage value by the number of cycles to obtain a cumulative damage value of each three-dimensional load segment; The cumulative damage value of each of the three-dimensional load segments is divided by the sum of the cumulative damage values of all the three-dimensional load segments to obtain the damage contribution rate of each load segment.

5. The fatigue acceleration detection method for a high fatigue resistance cast wheel according to claim 1, characterized in that: The method includes real-time monitoring of the dynamic strain response of the surface and interior of the target casting wheel based on a distributed sensing array, including: Pre-embedding a sensor array in a stress concentration area on the surface of the target casting wheel to generate the distributed sensor array; Collecting the original signal of the distributed sensing array and performing temperature drift compensation to extract the damage characteristic frequency band; Performing time domain alignment and spatial registration on the original signal to establish a coordinate mapping relationship between the sensor position and the three-dimensional model of the target casting wheel; Associating the coordinate mapping relationship with the damage characteristic frequency band to generate the dynamic strain response and mark potential damage hotspots; The dynamic strain response is transmitted to the damage accumulation calculation model in real time, and a timestamp is recorded to match the current loading parameters.

6. A fatigue acceleration detection system for high fatigue resistance cast wheels, characterized in that: The fatigue acceleration detection method for a high fatigue resistance cast wheel according to claim 1 is adopted, wherein the system comprises: The load analysis module generates a dynamic load spectrum including multi-axial composite loads based on the actual operating conditions of the target cast wheel; The strain monitoring module applies a dynamic load spectrum to the target casting wheel for accelerated testing, and monitors the dynamic strain response of the target casting wheel surface and interior in real time based on a distributed sensing array; The damage calculation module establishes a damage accumulation calculation model using the loading parameters of the dynamic load spectrum as additional correlation conditions, and calculates the equivalent fatigue damage accumulation value based on the dynamic strain response; The fatigue judgment module determines that the target cast wheel has reached the end of its fatigue life when the equivalent fatigue damage accumulation value reaches the preset damage threshold. The damage evolution law in the accelerated test is kept consistent with the damage mechanism of the actual operating conditions.

7. The fatigue acceleration detection system for high fatigue resistance cast wheel according to claim 6, characterized in that: The load analysis module includes: The data acquisition unit acquires the radial, tangential and axial multi-axis vibration signals and material stress concentration coefficient of the target casting wheel during actual operation; Feature analysis unit, which performs load feature analysis on multi-axis vibration signals and extracts multiple three-dimensional load segments; Equivalent conversion unit, combined with the material stress concentration factor, converts the asymmetric cyclic load in the three-dimensional load segment into an equivalent symmetric cyclic load; The spectrum generation unit calculates the damage contribution rate of each three-dimensional load segment, optimizes the loading sequence and cycle number distribution of the equivalent symmetrical cyclic load according to the damage contribution rate, and generates a dynamic load spectrum.

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