@inproceedings{0c656caa567c4d50b0664a9bf7f1cfa1,
title = "A Research on Fault Detection of Multi-State System Based on Hidden Markov Model",
abstract = "Different tasks and requirements make the system more and more modular and integrated. Its structures and levels are more and more complex, and more functions can be realized. Reliable operation and health management of systems have been an important elements for the success of the mission of systems. Then, the higher demands are presented for fault detection. In fact, there are various working states, and working state changed will bring the couplings in faults. Therefore, it is extremely significant for the multi-working states to identify working states. In this paper, combining multi-working states and the structure of hidden Markov model, based on the structure of hidden Markov model to deal with the three kinds of problems, the research identifying working states has been completed.",
keywords = "Fault Detection, Health management, Hidden Markov Model, Multi state System",
author = "Junyou Shi and Nanpo Niu and Xianjie Zhu and Chuxuan Fan",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018 ; Conference date: 26-10-2018 Through 28-10-2018",
year = "2019",
month = jan,
day = "4",
doi = "10.1109/PHM-Chongqing.2018.00129",
language = "英语",
series = "Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "723--728",
editor = "Ping Ding and Chuan Li and Shuai Yang and Ping Ding and Rene-Vinicio Sanchez",
booktitle = "Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018",
address = "美国",
}