Fatigue crack fault diagnosis and prognosis based on hidden semi-Markov model

被引:13
作者
Fan, Lei [1 ,2 ]
Wang, Shaoping [1 ,3 ]
Duan, Haibin [1 ]
Ran, Hongliang [4 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China
[2] Peoples Liberat Army Troop 61267, Detachment 41, Beijing, Peoples R China
[3] Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China
[4] Logist Univ PAP, Dept Equipment Support, Tianjin, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 13期
基金
中国国家自然科学基金;
关键词
D O I
10.1049/joe.2018.8960
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Aiming at the fault diagnosis and remaining useful life (RUL) prediction of fatigue cracks of a helicopter main gearbox planet carrier, this article proposes a hidden semi-Markov model (HSMM) methodology, which introduces the explicit state durational distribution parameters into the traditional hidden Markov model (HMM), thus overcoming the limitation of exponential distribution in HMM, retaining strong pattern recognition and classification ability, and improving the diagnostic and prognostic accuracy, and the effectiveness of the method was verified through experiments.
引用
收藏
页码:406 / 410
页数:5
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