Reliability modeling methods for load-sharing k-out-of-n system subject to discrete external load

• Published in: Reliability engineering & system safety Vol. 193; p. 106603
• Main Authors: Zhang, Jianchun, Zhao, Yu, Ma, Xiaobing
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.01.2020; Elsevier BV
• Subjects: Component reliability; Data acquisition; Distribution variation; Failure; Failure rates; Load distribution; Load distribution (forces); Load-sharing system; Load-strength model; Modelling; Reliability analysis; Reliability engineering; Reliability model; Strength damage; Stress concentration; Distribution variation; Reliability model; Strength damage; Load-sharing system; Load-strength model
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2019.106603

•The load distribution variation is used to reflect the load-sharing effect.•The physical and statistical dependence between load and strength are considered.•The common-cause failure is integrated into the model.•the failure-rate-based reliability modeling method is improved.•The proposed method extends the application of load-strength model. Most reliability modeling methods for the load-sharing k-out-of-n system are based on the assumed lifetime distribution and the relation function between the component failure rate and component load. However, the relation function is difficult to determine since the failure rate data have to be acquired. Therefore, this paper aims to develop a more direct reliability model for the load-sharing system based on the generalized load-strength model. In the presence of discrete external load, the proposed method utilizes the load distribution variation and strength damage after component failures to directly reflect the load-sharing effect, which can avoid measuring the failure rate. Further, the existing failure-rate-based reliability modeling method is also improved since the direct relation function between the component failure rate and component load is deduced. Two methods are both illustrated through the reliability analysis of a load-sharing redundant micro-engine system.