TY - GEN
T1 - Multivariate Correlation Degradation Parameters Life Assessment Method of Component Based on the Cholesky Factorization
AU - Leng, Hongyan
AU - Fu, Guicui
AU - Jiang, Maogong
AU - Zhong, Ling
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/4
Y1 - 2019/1/4
N2 - With the improvement of the component reliability, the requirement of the accuracy of life assessment is increasingly rigorous. Mostly, the existing life assessment method based on degradation data exclusively considers the single sensitive parameter. But actually, several correlation parameters may degenerate simultaneously, which will make the life assessment result inaccurate. In this paper, based on the single parameter life assessment of accelerated degradation data, the Monte Carlo method is used for simple random sampling, and the Cholesky factorization method is used to identify the correlation of samples under multivariate parameters. Afterwards, according to the competition failure model, a life distribution fusion method on multivariate correlation degradation parameters is proposed. This method makes the life assessment result more accurate and exhibits excellent engineering application value.
AB - With the improvement of the component reliability, the requirement of the accuracy of life assessment is increasingly rigorous. Mostly, the existing life assessment method based on degradation data exclusively considers the single sensitive parameter. But actually, several correlation parameters may degenerate simultaneously, which will make the life assessment result inaccurate. In this paper, based on the single parameter life assessment of accelerated degradation data, the Monte Carlo method is used for simple random sampling, and the Cholesky factorization method is used to identify the correlation of samples under multivariate parameters. Afterwards, according to the competition failure model, a life distribution fusion method on multivariate correlation degradation parameters is proposed. This method makes the life assessment result more accurate and exhibits excellent engineering application value.
KW - Cholesky factorization
KW - Correlation
KW - Degradation parameters
KW - Life assessment
KW - Multivariate
UR - https://www.scopus.com/pages/publications/85061785677
U2 - 10.1109/PHM-Chongqing.2018.00085
DO - 10.1109/PHM-Chongqing.2018.00085
M3 - 会议稿件
AN - SCOPUS:85061785677
T3 - Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018
SP - 462
EP - 467
BT - Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018
A2 - Ding, Ping
A2 - Li, Chuan
A2 - Yang, Shuai
A2 - Ding, Ping
A2 - Sanchez, Rene-Vinicio
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018
Y2 - 26 October 2018 through 28 October 2018
ER -