Fatigue reliability and hazard assessment of road load strain data for determining the fatigue life characteristics. (May 2021)

• Record Type: Journal Article
• Authors: Abdullah, L.; Singh, S.S.K.; Abdullah, S.; Azman, A.H.; Ariffin, A.K.
• Is Part Of: Engineering failure analysis. Volume 123(2021)
• Publication Date: 2021-05
• Subjects: Fatigue reliability -- Mean stress -- Durability -- Variable amplitude loading -- Strain data; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2021.105314
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: Fatigue reliability assessment is proposed based on experimentally measured random road load strain data. The capture strain signal is modelled to predict the fatigue life to assess the durability of the component. The data is modelled to predict the fatigue life, hazard rate, reliability and mean cycle to failure. The proposed reliability, cycle to failure and hazard rate distribution is for characterising fatigue life [1–52] . Abstract: This paper aims to assess the fatigue reliability associated for determining the fatigue life characteristics under random strain loads from various road load conditions. Fatigue failure for automotive components is mainly due to the random loads during the operating condition. However, there are still limited studies to associate fatigue reliability from fatigue life data for random loads, especially in the automotive industry. Experimentally measured random road load strain data at a sampling rate of 500 Hz in 60 s were captured from three different road conditions. The time history of the road load strain data illustrated low amplitude and high-frequency events on uneven surface roads. Fatigue life is assessed using the Coffin–Manson, Morrow and Smith–Watson–Topper models based on the Rainflow cycle counting technique. The fatigue life was estimated to be within a range of 3.21 × 10 2 to 1.08 × 10 5 cycles/block with a mean cycle to failure of 3.36 × 10 4 to 1.20 × 10 5 cycles/block. The Gumbel distribution is identified as the suitable distribution for the predicted fatigue lives data to model the reliability, hazard rate and mean cycle to failure. Hence, the distribution of reliability, cycle to failure and hazard rate is modelled and proposed for determining fatigue life characteristics under random road load strain data.