Reliability-based fatigue life assessment using random road load condition and local damage criteria

• Published in: Engineering failure analysis 2023-04, Vol.146, p.107157, Article 107157
• Main Authors: Manouchehrynia, R., Abdullah, S., Singh, S.S.K., Correia, J.A.F.O.
• Format: Article
• Language: English
• Subjects: Coil spring; Editing data; Fatigue life; Random load; Reliability assessment
• ISSN: 1350-6307; 1873-1961
• DOI: 10.1016/j.engfailanal.2023.107157

•Strain-time history signals of coil spring were measured through road tests.•Fatigue life data was conducted based on 90%, 95% and 100% retained damage.•Durability analysis was performed based on Coffin-Manson, Morrow and SWT life models.•Reliability assessment using the probability Gumbel distribution model.•Hazard rate was obtained for risk assessments based on the fatigue life predictions. This study presents a fatigue reliability assessment of a vehicle coil spring based on random road load conditions for fatigue life characterisation. Fatigue life data characterisation was carried out to accelerate the durability analysis by retaining the higher amplitude cycles in the original strain signals and thus indicate the fatigue damage. To collect experimental data, road testing was conducted using various road profiles, which contributed significantly to the fatigue failure performance of the vehicle coil spring. Fatigue reliability analysis was performed to assess the failure behaviour of the coil spring utilising the probabilistic Gumbel distribution model to forecast the probability distribution of the fatigue life data. Furthermore, the highest and lowest mean-cycles-to-failure (McTF) of 5.44 × 107 and 2.46 × 105 blocks were estimated for the Coffin-Manson and Smith-Watson-Topper models from the highway and rural road profiles. The findings demonstrate that the lowest hazard rate corresponded to the highest McTF, making this an acceptable model to be implemented in reliability assessments of road profiles. Hence, the fatigue reliability assessment provided a hazard rate based on the fatigue life predictions for risk assessments when characterising the fatigue life data.