Approach to fault diagnosis for non-linear system based on fuzzy cluster analysis

Yiping Liu; Yi Shen; Zhiyan Liu

Approach to fault diagnosis for non-linear system based on fuzzy cluster analysis

Yiping Liu^*
, Yi Shen
, Zhiyan Liu

^*Corresponding author for this work

School of Astronautics

Harbin Institute of Technology

Research output: Contribution to conference › Paper › peer-review

8 Scopus citations

Abstract

An approach to fault diagnosis based on fuzzy clustering is proposed in this paper. First, the fuzzy model representing each state of system is built by extracting fuzzy rules from the sample data using fuzzy clustering algorithm. Then, the modified fuzzy models for fault diagnosis are obtained based on the original fuzzy models and constitute a whole rule-base. Furthermore, a strategy for fault diagnosis based on fuzzy clustering is presented to detect and locate faults in system. Finally, some experimental results are shown to illustrate the effectiveness of the proposed approach.

Original language	English
Pages	1469-1473
Number of pages	5
State	Published - 2000
Event	IMTC/2000 - 17th IEEE Instrumentation and Measurement Technology Conference 'Smart Connectivity: Integrating Measurement and Control' - Baltimore, MD, USA Duration: 1 May 2000 → 4 May 2000

Conference

Conference	IMTC/2000 - 17th IEEE Instrumentation and Measurement Technology Conference 'Smart Connectivity: Integrating Measurement and Control'
City	Baltimore, MD, USA
Period	1/05/00 → 4/05/00

Cite this

@conference{5da3a5d8718e41a1a494479b468e8f15,

title = "Approach to fault diagnosis for non-linear system based on fuzzy cluster analysis",

abstract = "An approach to fault diagnosis based on fuzzy clustering is proposed in this paper. First, the fuzzy model representing each state of system is built by extracting fuzzy rules from the sample data using fuzzy clustering algorithm. Then, the modified fuzzy models for fault diagnosis are obtained based on the original fuzzy models and constitute a whole rule-base. Furthermore, a strategy for fault diagnosis based on fuzzy clustering is presented to detect and locate faults in system. Finally, some experimental results are shown to illustrate the effectiveness of the proposed approach.",

author = "Yiping Liu and Yi Shen and Zhiyan Liu",

year = "2000",

language = "英语",

pages = "1469--1473",

note = "IMTC/2000 - 17th IEEE Instrumentation and Measurement Technology Conference 'Smart Connectivity: Integrating Measurement and Control' ; Conference date: 01-05-2000 Through 04-05-2000",

}

Approach to fault diagnosis for non-linear system based on fuzzy cluster analysis. / Liu, Yiping; Shen, Yi; Liu, Zhiyan.
2000. 1469-1473 Paper presented at IMTC/2000 - 17th IEEE Instrumentation and Measurement Technology Conference 'Smart Connectivity: Integrating Measurement and Control', Baltimore, MD, USA.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Approach to fault diagnosis for non-linear system based on fuzzy cluster analysis

AU - Liu, Yiping

AU - Shen, Yi

AU - Liu, Zhiyan

PY - 2000

Y1 - 2000

N2 - An approach to fault diagnosis based on fuzzy clustering is proposed in this paper. First, the fuzzy model representing each state of system is built by extracting fuzzy rules from the sample data using fuzzy clustering algorithm. Then, the modified fuzzy models for fault diagnosis are obtained based on the original fuzzy models and constitute a whole rule-base. Furthermore, a strategy for fault diagnosis based on fuzzy clustering is presented to detect and locate faults in system. Finally, some experimental results are shown to illustrate the effectiveness of the proposed approach.

AB - An approach to fault diagnosis based on fuzzy clustering is proposed in this paper. First, the fuzzy model representing each state of system is built by extracting fuzzy rules from the sample data using fuzzy clustering algorithm. Then, the modified fuzzy models for fault diagnosis are obtained based on the original fuzzy models and constitute a whole rule-base. Furthermore, a strategy for fault diagnosis based on fuzzy clustering is presented to detect and locate faults in system. Finally, some experimental results are shown to illustrate the effectiveness of the proposed approach.

UR - https://www.scopus.com/pages/publications/0033713766

M3 - 论文

AN - SCOPUS:0033713766

SP - 1469

EP - 1473

T2 - IMTC/2000 - 17th IEEE Instrumentation and Measurement Technology Conference 'Smart Connectivity: Integrating Measurement and Control'

Y2 - 1 May 2000 through 4 May 2000

ER -

Approach to fault diagnosis for non-linear system based on fuzzy cluster analysis

Abstract

Conference

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