Prediction and evaluation of fatigue life for mechanical components considering anelasticity‐based load spectrum

Abstract

To accurately predict the degraded fatigue life of components under random loads, anelasticity effect of metal on life estimation needs to be explored. Weighting coefficient and dynamic elastic modulus are introduced to modify the calculation process of the model. By establishing an equal-amplitude fatigue median surface and applying Miner linear fatigue cumulative damage theory, a fatigue life prediction model of the component under random loads is proposed. The model can be used to calculate the degraded fatigue life of components, which provides a theoretical basis for life estimation under random load spectrum. The two-dimensional load spectrum is compared with the unprocessed two-dimensional load spectrum and the one-dimensional program spectrum in life prediction results. With the comparison of the target life and simulation life and the data calculated by the model of the automobile front stabilizer bar, it is concluded that the data obtained by the modified model are more reasonable and accurate.

Numerical Method for Fatigue Life Prediction of Liquid‐Storage Tank via Crack Length and Depth

“…e Paris law is widely used in engineering to describe the fatigue crack growth characteristics of materials [14,15]. e fatigue life of mechanical components has been evaluated, which is considered an elasticity-based load spectrum [16]. And a modified quality loss model of service life prediction has been established [17,18].…”

An improved nonlinear cumulative damage model for strength degradation considering loading sequence

“…Fatigue failure of mechanical structures in engineering is one of the main failure modes (Wang et al, 2020). So, it is very important to predict the fatigue life of components (Zhu et al, 2018).…”

Tolerance analysis for automobile transmission shaft based on minimum cost and reliability target

“…where d is the deviation from target radius r o . According to T = 3.522 mm, T = 3.750 mm and equation (18), if the quality loss coefficient k is known, the expected quality loss can also be calculated and compared. This section is not discussed in detail in this paper.…”