TY - GEN
T1 - A stochastic approach for evaluating the reliability of multi-stated phased-mission systems with imperfect fault coverage
AU - Song, Xiaogang
AU - Zhai, Zhengjun
AU - Zhu, Peican
AU - Guo, Yangming
AU - Zhang, Yunpeng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/20
Y1 - 2017/10/20
N2 - A phased-mission system (PMS) is usually consisting of a number of non-overlapping phases, and the phases should be completed sequentially to achieve a successful mission. In practice, imperfect fault coverage (IPC) plays an important effect on the system reliability. In this paper, stochastic multi-value (SMV) models are proposed to predict the system reliability of a multi-stated PMS consisting of non-repairable components; during the evaluating process, three different imperfect fault coverage conditions (listed as Element Level Coverage, Fault Level Coverage, and Performance dependent Coverage) are incorporated. In the stochastic analysis, performance values and their corresponding probabilities of elements are simultaneously encoded in random sequences consisting of permutation of fixed numbers of multi-value numbers. Thus, the types of components' failure distributions are not limited for the proposed approach. By feeding the obtained stochastic sequences into the proposed system structure, reliability of a PMS can be efficiently determined which avoids cumbersome analyzing process. The efficiency of the SMV approach is verified by several case studies compared to universal generating function (UGF).
AB - A phased-mission system (PMS) is usually consisting of a number of non-overlapping phases, and the phases should be completed sequentially to achieve a successful mission. In practice, imperfect fault coverage (IPC) plays an important effect on the system reliability. In this paper, stochastic multi-value (SMV) models are proposed to predict the system reliability of a multi-stated PMS consisting of non-repairable components; during the evaluating process, three different imperfect fault coverage conditions (listed as Element Level Coverage, Fault Level Coverage, and Performance dependent Coverage) are incorporated. In the stochastic analysis, performance values and their corresponding probabilities of elements are simultaneously encoded in random sequences consisting of permutation of fixed numbers of multi-value numbers. Thus, the types of components' failure distributions are not limited for the proposed approach. By feeding the obtained stochastic sequences into the proposed system structure, reliability of a PMS can be efficiently determined which avoids cumbersome analyzing process. The efficiency of the SMV approach is verified by several case studies compared to universal generating function (UGF).
KW - imperfect fault coverage
KW - phased-mission system
KW - reliability analysis
KW - stochastic multi-value model
UR - http://www.scopus.com/inward/record.url?scp=85039962848&partnerID=8YFLogxK
U2 - 10.1109/PHM.2017.8079163
DO - 10.1109/PHM.2017.8079163
M3 - 会议稿件
AN - SCOPUS:85039962848
T3 - 2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings
BT - 2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings
A2 - Zhang, Bin
A2 - Peng, Yu
A2 - Liao, Haitao
A2 - Liu, Datong
A2 - Wang, Shaojun
A2 - Miao, Qiang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE Prognostics and System Health Management Conference, PHM-Harbin 2017
Y2 - 9 July 2017 through 12 July 2017
ER -