Fault Diagnosis Based on PCA Model and Fault Reconstruction

被引：0

作者：

Chen, Chengguo ^{[1
]}

Xiao, Yingwang ^{[2
]}

Huang, Yean ^{[1
]}

Yang, Jun ^{[2
]}

机构：

[1] S China Normal Univ, Sch Comp, Guangzhou 510631, Guangdong, Peoples R China

[2] S China Normal Univ, Sch Software, Fushan 528225, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON ELECTRICAL AND CONTROL ENGINEERING (ICECE 2015) | 2015年

关键词：

Fault identification; Fault reconstruction; Double-effect evaporator process; PRINCIPAL COMPONENT ANALYSIS;

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：

Nevertheless, the most significant advantage of principal component analysis (PCA) is that no precise process model is needed, the development of capacity for fault diagnosis based on PCA is restricted to some extent. Based on the fault reconstruction technology, the fault diagnosis issue was explored by using T2 index. The fault identification index and diagnosis arithmetic were presented. Through the simulation monitoring of double-effect evaporator process, these results show that the acquired theoretical results can effectively identify fault (sensor and process fault) and are effective.

引用

页码：685 / 690

页数：6

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