@article{ref1,
title="Mechanism reliability and sensitivity analysis method using truncated and correlated normal variables",
journal="Safety science",
year="2020",
author="Zhang, Feng and Xu, Xiayu and Cheng, Lei and Tan, Shiwang and Wang, Weihu and Wu, Mingying",
volume="125",
number="",
pages="e104615-e104615",
abstract="This paper presents a method for the reliability and sensitivity analysis of mechanical systems using truncated and correlated normal variables. First, a model for estimating the reliability of such systems is established. Second, the failure probability and reliability sensitivity are calculated using the Monte Carlo method, and the influence of the normal input variables on the failure probability and reliability sensitivity is analyzed. The proposed method is then applied to four-bar linkage and squaring machine examples to demonstrate the applicability of the proposed analysis model. Finally, it is shown from the analysis results that it is critical that the failure probability and reliability sensitivity be estimated with consideration of the correlated and truncated distributions of mechanisms with normal input variables. This paper focuses on precision reliability and reliability sensitivity analysis of mechanism movements to demonstrate how the proposed analysis process can be best implemented.<p /> <p>Language: en</p>",
language="en",
issn="0925-7535",
doi="10.1016/j.ssci.2020.104615",
url="http://dx.doi.org/10.1016/j.ssci.2020.104615"
}