@inproceedings{f6becf376f7d48d381a84d8c2d7f95a7,
title = "Fault Assessment of Hydraulic System Based on Gaussian Mixture Model",
abstract = "Based on the civil aircraft hydraulic system, the typical slow-change fault injection is carried out in hydraulic system MWorks model, and the fault state assessment technology based on Gaussian mixture model is studied. The results show that the health curve of the Gaussian mixture model can truly reflect the system pressure abnormal deviation process, and the health confidence value obtained by the inverse tangent function normalization is more sensitive to the early failure process of the fault, which can better support the predictive maintenance.",
keywords = "fault assessment, gaussian mixture model, normalization",
author = "Zhaobing Wang and Jian Tang and Xin Jiang and Yi Wang and Jian Ma and Yu Chen",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020 ; Conference date: 16-10-2020 Through 18-10-2020",
year = "2020",
month = oct,
day = "16",
doi = "10.1109/PHM-Shanghai49105.2020.9280952",
language = "英语",
series = "2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Wei Guo and Steven Li and Qiang Miao",
booktitle = "2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020",
address = "美国",
}