Nowadays, S-transform-based (ST-based) editing method is utilized in fatigue durability analysis of automotive components. Nevertheless, single threshold setting in this method leads to poor effect on editing of load spectrum. This work optimizes threshold setting and proposes a S-transform dual-threshold-based (STDT-based) spectral editing method. The proposed method first performs S-transform on equivalent strain signal to obtain maximum amplitude spectrum. Then, dual-threshold is setting to identify and retain amplitude spectrum, based on which corresponding load spectrums are retained and stitched together to form accelerated load spectrums. The effectiveness of load spectrum via STDT-based editing is verified by taking multi-axis load spectrums of automobile steering knuckle as an example. The results show that, STDT-based editing method can obviously compress original load time, and the compression efficiency is higher than that of ST-based editing method. Moreover, it verifies that load effect of edited spectrum matches well with that of original in combination with fatigue simulation analysis. Thus, this proposed method is suitable for research of accelerated editing of load spectra of vehicle components.
GengSLiuXYangX, et al. Load spectrum for automotive wheels hub based on mixed probability distribution model. Proc IMechE, Part D: J Automobile Engineering2019; 233(14): 3707–3720.
2.
LiuXWangHWuQ, et al. Uncertainty-based analysis of random load signal and fatigue life for mechanical structures. Arch Comput Methods Eng2022; 29(1): 375–395.
3.
YangXLiuXWangY. Random fatigue life prediction of automobile lower arm via modified Corten–Dolan model. Fatigue Fract Eng Mater Struct2022; 45(12): 3500–3513.
4.
SunderR. Cycle sequence sensitivity of near threshold fatigue under programmed loading – a fractographic study. Int J Fatigue2020; 135: 105537.
5.
ParaforosDSGriepentrogHWVougioukasSG. Methodology for designing accelerated structural durability tests on agricultural machinery. Biosyst Eng2016; 149: 24–37.
6.
YuJZhengSFengJ, et al. New methodology for determination of load spectra for the vehicle accelerated durability testing associated with the time correlated fatigue damage analysis method. Int J Automot Technol2017; 18(3): 547–560.
7.
HeXLiTLiY, et al. Developing an accelerated flight load spectrum based on the nz-N curves of a fleet. Int J Fatigue2018; 117: 246–256.
8.
LuYZhengHZengJ, et al. Fatigue life reliability evaluation in a high-speed train bogie frame using accelerated life and numerical test. Reliab Eng Syst Saf2019; 188: 221–232.
9.
WanASXuYGXueLH, et al. Finite element modeling and fatigue life prediction of helicopter composite tail structure under multipoint coordinated loading spectrum. Compos Struct2021; 255: 112900.
10.
MeiGLuoQQiaoW, et al. Study of load spectrum compilation method for the pantograph upper frame based on multi-body dynamics. Eng Fail Anal2022; 135: 106099.
11.
KadhimNAAbdullahSAriffinAK. Effect of the fatigue data editing technique associated with finite element analysis on the component fatigue design period. Mater Des2011; 32(2): 1020–1030.
12.
MattettiMMolariGVertuaA. New methodology for accelerating the four-post testing of tractors using wheel hub displacements. Biosyst Eng2015; 129: 307–314.
13.
YuJZhaoLMaJ, et al. Load spectrum compilation for vehicle road simulation test by applying a new time domain threshold editing method. Proc IMechE, Part D: J Automobile Engineering2024; 238(1): 277–290.
14.
LiuZPengCYangX. Research and analysis of the wheeled vehicle load spectrum editing method based on short-time Fourier transform. Proc IMechE, Part D: J Automobile Engineering2019; 233(14): 3671–3683.
15.
WenCXieBLiZ, et al. Power density based fatigue load spectrum editing for accelerated durability testing for tractor front axles. Biosyst Eng2020; 200: 73–88.
16.
PutraTEAbdullahSSchrammD, et al. Generating strain signals under consideration of road surface profiles. Mech Syst Signal Process2015; 60: 485–497.
17.
PratumnopharatPLeungPSCourtRS. Wavelet transform-based stress-time history editing of horizontal axis wind turbine blades. Renew Energy2014; 63: 558–575.
18.
PutraTEAbdullahSSchrammD, et al. Reducing cyclic testing time for components of automotive suspension system utilising the wavelet transform and the Fuzzy C-Means. Mech Syst Signal Process2017; 90: 1–14.
19.
PutraTEAbdullahSSchrammD, et al. The need to generate realistic strain signals at an automotive coil spring for durability simulation leading to fatigue life assessment. Mech Syst Signal Process2017; 94: 432–447.
20.
RaiHMChatterjeeK. Hybrid adaptive algorithm based on wavelet transform and independent component analysis for denoising of MRI images. Measurement2019; 144: 72–82.
21.
PutraTEAbdullahSSchrammD. Effect of cycle amplitude removal of fatigue strain loadings associated to signal energy characteristics. Eng Fail Anal2020; 116: 104723.
22.
RahimAAAAbdullahSSinghSSK, et al. Fatigue strain signal reconstruction technique based on selected wavelet decomposition levels of an automobile coil spring. Eng Fail Anal2021; 125: 105434.
23.
MohseniMSanthanamSWilliamsJ, et al. Systematic fatigue spectrum editing by fast wavelet transform and genetic algorithm. Fatigue Fract Eng Mater Struct2022; 45(1): 69–83.
24.
GuofengZWenbinSPengfeiHAN, et al. Study of load spectrum edition method based on the wavelet transform to the accelerated durability test of the vehicle component. J Mech Eng2017; 53(8): 124–131.
25.
ShangguanWBZhengGFRakhejaS, et al. A method for editing multi-axis load spectrums based on the wavelet transforms. Measurement2020; 162: 107903.
26.
ZhengGPanHChenB, et al. Methods for editing random load spectra based on multi-parameter index preservation for accelerated durability testing. Proc IMechE, Part C: J Mechanical Engineering Science2022; 236(14): 7657–7673.
27.
LiuXZhaoXLiuXA, et al. A load spectrum editing method of time-frequency for rubber isolators based on the continuous wavelet transform. Measurement2022; 198: 111374.
28.
KumarRNigamRSinghSK. Selection of suitable mother wavelet along with vanishing moment for the effective detection of crack in a beam. Mech Syst Signal Process2022; 163: 108136.
29.
YaoJLinYLinX, et al. Fatigue loads compressed editing by discrete wavelet transform and optimal wavelet parameters selection algorithm. Eng Fract Mech2024; 303: 110128.
30.
JinJZhangJZhouW, et al. Edition of vehicle durability load spectrum based on Hilbert-Huang transform. J Highw Transp Res Dev2022; 39(2): 140–149.
31.
YangYZhangZPengL, et al. Accelerated editing method for vehicle durability fatigue load spectrum based on Wigner-Ville transform. Sensors2023; 23(14): 6435.
32.
WuLCastagnaJ. S-transform and Fourier transform frequency spectra of broadband seismic signals. Geophysics2017; 82(5): O71–O81.
33.
LiHFWangJWeiZR, et al. High-frequency compensation for seismic data based on adaptive generalized S transform. Appl Geophy2020; 17(5): 747–755.
34.
SerdyukovASAzarovAVYablokovAV, et al. Research note: reconstruction of seismic signals using S-transform ridges. Geophys Prospect2021; 69(4): 891–900.
35.
JiangLShangWJiaoY, et al. An adaptive generalized S-transform algorithm for seismic signal analysis. IEEE Access2022; 10: 127863–127870.
36.
KumarMAgrawalS. Color image encoding in DOST domain using DWT and SVD. Opt Laser Technol2015; 75: 138–145.
37.
KumarMVaishA. Encryption of color images using MSVD in DCST domain. Opt Laser Eng2017; 88: 51–59.
38.
RajkumarRRoySSinghKM. S-transform-based efficient copy-move forgery detection technique in digital images. Int J Intell Enterp2020; 7(1–3): 107–121.
39.
SharmaVGidwaniL. Recognition of disturbances in hybrid power system interfaced with battery energy storage system using combined features of Stockwell transform and Hilbert transform. AIMS Energy2019; 7(5): 671–687.
40.
KulshresthaAMahelaOPGuptaMK, et al. A hybrid fault recognition algorithm using Stockwell transform and Wigner distribution function for power system network with solar energy penetration. Energies2020; 13(14): 3519.
41.
Minh KhoaNVan DaiL. Detection and classification of power quality disturbances in power system using modified-combination between the Stockwell transform and decision tree methods. Energies2020; 13(14): 3623.
42.
MahelaOPGuptaMKKulshresthaA, et al. Hybrid protection algorithm for power system with renewable energy generation using Stockwell transform and Wigner distribution function. J Eng2022; 2022(8): 832–846.
43.
OrtizMRodríguez-UgarteMIáñezE, et al. Application of the Stockwell transform to electroencephalographic signal analysis during gait cycle. Front Neurosci2017; 11: 660.
44.
Pérez-VidalAFGarcia-BeltranCDMartínez-SibajaA, et al. Use of the Stockwell transform in the detection of P300 evoked potentials with low-cost brain sensors. Sensors2018; 18(5): 1483.
45.
SubohMZJaafarRNayanNA, et al. Shannon energy application for detection of ECG R-peak using bandpass filter and Stockwell transform methods. Adv Electr Comput Eng2020; 20(3): 41–48.
46.
AbdullahSNizwanCKEYunohMFM, et al. Fatigue features extraction of road load time data using the S-transform. Int J Automot Technol2013; 14: 805–815.
47.
DongGHanJZhangY, et al. Research on the S-transform based fatigue load spectrum editing method for automotive components. China J Highw Transp2021; 34(5): 204–214.
48.
LiuXTanJLongS. Multi-axis fatigue load spectrum editing for automotive components using generalized S-transform. Int J Fatigue2024; 188: 108503.
49.
ShahFATantaryAY. Linear canonical Stockwell transform. J Math Anal Appl2020; 484(1): 123673.
50.
BenasciuttiDSherrattFCristoforiA. Recent developments in frequency domain multi-axial fatigue analysis. Int J Fatigue2016; 91: 397–413.
51.
MoonyoungYKyeonghoKKwangsuckB, et al. Fatigue life prediction with equivalent von mises stress considering the phase difference between multi-axial stress components. J Korean Soc Precis Eng2018; 35(5): 515–520.
52.
ObremenitevP. A modified method of Von Mises stress-based MWCM for fatigue-life prediction under fully-reversed axial-torsion proportional loads. Mater Tehnol2019; 53(1): 115–121.
53.
LiuBYanX. A multi-axial fatigue limit prediction equation for metallic materials. J Press Vessel Technol2020; 142(3): 034501.
54.
PengMLiuMGuS, et al. Multiaxial fatigue analysis of jacket-type offshore wind turbine based on multi-scale finite element model. Materials2023; 16(12): 4383.
