Probabilistic-based analysis for damaging features of fatigue strain loadings
This paper presents the behaviour of fatigue damage extraction in fatigue strain histories of automotive components using the probabilistic approach. This is a consideration for the evaluation of fatigue damage extraction in automotive components under service loading that is vital in a reliability...
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Gruppo Italiano Frattura
2018-10-01
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Series: | Frattura ed Integrità Strutturale |
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Online Access: | http://www.gruppofrattura.it/pdf/rivista/numero46/numero_46_art_9.pdf |
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doaj-04238d5bb5a4403ea4ebc2f1a3dcb95d2020-11-24T23:55:32ZengGruppo Italiano FratturaFrattura ed Integrità Strutturale1971-89932018-10-011246849310.3221/IGF-ESIS.46.0910.3221/IGF-ESIS.46.09Probabilistic-based analysis for damaging features of fatigue strain loadingsM. F. Mod YunohS. AbdullahM. H. M. SaadZ. M. NopiahM. Z. NuawiS. S. K. SinghThis paper presents the behaviour of fatigue damage extraction in fatigue strain histories of automotive components using the probabilistic approach. This is a consideration for the evaluation of fatigue damage extraction in automotive components under service loading that is vital in a reliability analysis. For the purpose of research work, two strain signals data are collected from a car coil spring during a road test. The fatigue strain signals are then extracted using the wavelet transform in order to extract the high amplitude segments that contribute to the fatigue damage. At this stage, the low amplitude segments are removed because of their minimal contribution to the fatigue damage. The fatigue damage based on all extracted segments is calculated using some significant strain-life models. Subsequently, the statistics-based Weibull distribution is applied to evaluate the fatigue damage extraction. It has been found that about 70% of the probability of failure occurs in the 1.0 x 10-5 to 1.0 x 10-4 damage range for both signals, while 90% of the probability of failure occurs in the 1.0 x 10-4 to 1.0 x 10-3 damage range. Lastly, it is suggested that the fatigue damage can be determined by the Weibull distribution analysishttp://www.gruppofrattura.it/pdf/rivista/numero46/numero_46_art_9.pdfFatigue damage Features extraction Probabilistic Wavelet Weibull distribution |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. F. Mod Yunoh S. Abdullah M. H. M. Saad Z. M. Nopiah M. Z. Nuawi S. S. K. Singh |
spellingShingle |
M. F. Mod Yunoh S. Abdullah M. H. M. Saad Z. M. Nopiah M. Z. Nuawi S. S. K. Singh Probabilistic-based analysis for damaging features of fatigue strain loadings Frattura ed Integrità Strutturale Fatigue damage Features extraction Probabilistic Wavelet Weibull distribution |
author_facet |
M. F. Mod Yunoh S. Abdullah M. H. M. Saad Z. M. Nopiah M. Z. Nuawi S. S. K. Singh |
author_sort |
M. F. Mod Yunoh |
title |
Probabilistic-based analysis for damaging features of fatigue strain loadings |
title_short |
Probabilistic-based analysis for damaging features of fatigue strain loadings |
title_full |
Probabilistic-based analysis for damaging features of fatigue strain loadings |
title_fullStr |
Probabilistic-based analysis for damaging features of fatigue strain loadings |
title_full_unstemmed |
Probabilistic-based analysis for damaging features of fatigue strain loadings |
title_sort |
probabilistic-based analysis for damaging features of fatigue strain loadings |
publisher |
Gruppo Italiano Frattura |
series |
Frattura ed Integrità Strutturale |
issn |
1971-8993 |
publishDate |
2018-10-01 |
description |
This paper presents the behaviour of fatigue damage extraction in fatigue strain histories of automotive components using the probabilistic approach. This is a consideration for the evaluation of fatigue damage extraction in automotive components under service loading that is vital in a reliability analysis. For the purpose of research work, two strain signals data are collected from a car coil spring during a road test. The fatigue strain signals are then extracted using the wavelet transform in order to extract the high amplitude segments that contribute to the fatigue damage. At this stage, the low amplitude segments are removed because of their minimal contribution to the fatigue damage. The fatigue damage based on all extracted segments is calculated using some significant strain-life models. Subsequently, the statistics-based Weibull distribution is applied to evaluate the fatigue damage extraction. It has been found that about 70% of the probability of failure occurs in the 1.0 x 10-5 to 1.0 x 10-4 damage range for both signals, while 90% of the probability of failure occurs in the 1.0 x 10-4 to 1.0 x 10-3 damage range. Lastly, it is suggested that the fatigue damage can be determined by the Weibull distribution analysis |
topic |
Fatigue damage Features extraction Probabilistic Wavelet Weibull distribution |
url |
http://www.gruppofrattura.it/pdf/rivista/numero46/numero_46_art_9.pdf |
work_keys_str_mv |
AT mfmodyunoh probabilisticbasedanalysisfordamagingfeaturesoffatiguestrainloadings AT sabdullah probabilisticbasedanalysisfordamagingfeaturesoffatiguestrainloadings AT mhmsaad probabilisticbasedanalysisfordamagingfeaturesoffatiguestrainloadings AT zmnopiah probabilisticbasedanalysisfordamagingfeaturesoffatiguestrainloadings AT mznuawi probabilisticbasedanalysisfordamagingfeaturesoffatiguestrainloadings AT ssksingh probabilisticbasedanalysisfordamagingfeaturesoffatiguestrainloadings |
_version_ |
1725462016578027520 |