Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 586316, 17 pages
Research Article

Fatigue Reliability Sensitivity Analysis of Complex Mechanical Components under Random Excitation

1School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China
2Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada N2l 3G1

Received 31 July 2010; Revised 19 December 2010; Accepted 13 January 2011

Academic Editor: Michael J. Brennan

Copyright © 2011 Hao Lu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Fatigue failure is the typical failure mode of mechanical components subjected to random load-time history. It is important to ensure that the mechanical components have an expected life with a high reliability. However, it is difficult to reduce the influence of factors that affect the fatigue reliability and thus a reliability sensitivity analysis is necessary. An approach of fatigue reliability sensitivity analysis of complex mechanical components under random excitation is presented. Firstly, load spectra are derived using a theoretical method. A design of experiment (DOE) is performed to study the stresses of dangerous points according to the change of design parameters of the mechanical component. By utilizing a Back-Propagation (BP) algorithm, the explicit function relation between stresses and design parameters is formulated and thus solves the problem of implicit limit state function. Based on the damage accumulation (DA) approach, the probability perturbation method, the fourth-moment method, the Edgeworth expansion is adopted to calculate the fatigue reliability and reliability-based sensitivity. The fatigue reliability sensitivity analysis of a train wheel is performed as an example. The results of reliability are compared with that obtained using Monte Carlo simulation. The reliability sensitivity of design parameters in the train wheel is analyzed.