Fault subspace decomposition and reconstruction theory based online fault prognosis

被引：5
|
作者：
Han, Min [1 ]
Li, Jinbing [1 ]
Han, Bing [2 ]
Zhong, Kai [1 ]
机构：
[1] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116024, Peoples R China
[2] Shanghai Ship & Shipping Res Inst, State Key Lab Nav & Safety Technol, Shanghai 200135, Peoples R China
来源：
CONTROL ENGINEERING PRACTICE | 2019年 / 85卷
基金：
中国国家自然科学基金;
关键词：
PCA; Fault subspace decomposition; Fault reconstruction; Prognosis; Vector autoregression; IDENTIFICATION; PCA;
D O I：
10.1016/j.conengprac.2019.01.013
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a monitoring-statistic-based fault subspace decomposition and double decomposition (DD) reconstruction method is presented to deal with multivariable continuous slow-varying process fault prognosis. The new method assumed that fault is known and can be completely reconstructed. Then, the fault directions are determined by the monitoring-statistic-based fault subspace decomposition method. Finally, the DD reconstruction method and the vector autoregression (VAR) method are used to calculate and predict the magnitude degeneration process of corresponding fault directions. After that, online fault prognosis is realized. The experiments show the effectiveness of the developed method.
引用
收藏
页码：121 / 131
页数：11
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