Information theoretic fault detection

Alok Joshi; Paul Deignan; Peter Meckl; Galen King; Kristofer Jennings

doi:10.1109/ACC.2005.1470203

Information theoretic fault detection

Alok Joshi
, Paul Deignan
, Peter Meckl
, Galen King
, Kristofer Jennings

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

In this paper we propose a novel method of fault detection based on a clustering algorithm developed in the information theoretic framework. A mathematical formulation for a multi-input multi-output (MIMO) system is developed to identify the most informative signals for the fault detection using mutual information (MI) as the measure of correlation among various measurements on the system. This is a model-independent approach for the fault detection. The effectiveness of the proposed method is successfully demonstrated by employing MI-based algorithm to isolate various faults in 16-cylinder diesel engine in the form of distinct clusters.

Original language	English (US)
Title of host publication	Proceedings of the 2005 American Control Conference, ACC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1642-1647
Number of pages	6
ISBN (Print)	0780390989
DOIs	https://doi.org/10.1109/ACC.2005.1470203
State	Published - 2005
Externally published	Yes
Event	2005 American Control Conference, ACC 2005 - Portland, OR, United States Duration: Jun 8 2005 → Jun 10 2005

Publication series

Name	Proceedings of the American Control Conference
Volume	3
ISSN (Print)	0743-1619

Conference

Conference	2005 American Control Conference, ACC 2005
Country/Territory	United States
City	Portland, OR
Period	6/8/05 → 6/10/05

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2005.1470203

Cite this

Information theoretic fault detection. / Joshi, Alok; Deignan, Paul; Meckl, Peter et al.
Proceedings of the 2005 American Control Conference, ACC. Institute of Electrical and Electronics Engineers Inc., 2005. p. 1642-1647 WeC15.2 (Proceedings of the American Control Conference; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Joshi, A, Deignan, P, Meckl, P, King, G & Jennings, K 2005, Information theoretic fault detection. in Proceedings of the 2005 American Control Conference, ACC., WeC15.2, Proceedings of the American Control Conference, vol. 3, Institute of Electrical and Electronics Engineers Inc., pp. 1642-1647, 2005 American Control Conference, ACC 2005, Portland, OR, United States, 6/8/05. https://doi.org/10.1109/ACC.2005.1470203

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author = "Alok Joshi and Paul Deignan and Peter Meckl and Galen King and Kristofer Jennings",

year = "2005",

doi = "10.1109/ACC.2005.1470203",

language = "English (US)",

isbn = "0780390989",

series = "Proceedings of the American Control Conference",

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note = "2005 American Control Conference, ACC 2005 ; Conference date: 08-06-2005 Through 10-06-2005",

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AU - Meckl, Peter

AU - King, Galen

AU - Jennings, Kristofer

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N2 - In this paper we propose a novel method of fault detection based on a clustering algorithm developed in the information theoretic framework. A mathematical formulation for a multi-input multi-output (MIMO) system is developed to identify the most informative signals for the fault detection using mutual information (MI) as the measure of correlation among various measurements on the system. This is a model-independent approach for the fault detection. The effectiveness of the proposed method is successfully demonstrated by employing MI-based algorithm to isolate various faults in 16-cylinder diesel engine in the form of distinct clusters.

AB - In this paper we propose a novel method of fault detection based on a clustering algorithm developed in the information theoretic framework. A mathematical formulation for a multi-input multi-output (MIMO) system is developed to identify the most informative signals for the fault detection using mutual information (MI) as the measure of correlation among various measurements on the system. This is a model-independent approach for the fault detection. The effectiveness of the proposed method is successfully demonstrated by employing MI-based algorithm to isolate various faults in 16-cylinder diesel engine in the form of distinct clusters.

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M3 - Conference contribution

AN - SCOPUS:23944502367

SN - 0780390989

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BT - Proceedings of the 2005 American Control Conference, ACC

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ER -

Information theoretic fault detection

Abstract

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Conference

ASJC Scopus subject areas

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