Subspace Aided Data-Driven Fault Detection for LTI Systems

被引：0
|
作者：
Chen Jiao [1 ]
Fang Huajing [1 ]
Liu Xiaoyong [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China
来源：
2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2015年
关键词：
Determination of System Order; Fault Detection; Subspace Identification Methods; Akaike Information Criterion; IDENTIFICATION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper mainly solves the issue of subspace aided data-driven fault detection for systems, identifying the residual generator without the specific model. By the input and output data. Akaike information criterion and singular value decomposition are used to determined the system order firstly and a comparison between them is made. Then based on a certain algorithm, we can get some useful subspace to construct a residual generator for fault detection effectively. Finally,we apply the theoretical method into simulation studies to show its feasibility and effectiveness.
引用
收藏
页码：2758 / 2761
页数：4
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