Design of intelligent diagnosis system based on CBR for jet engine

Bo Xu; Xingshan Li; Jinsong Yu

doi:10.1117/12.522341

Design of intelligent diagnosis system based on CBR for jet engine

Bo Xu^*
, Xingshan Li
, Jinsong Yu

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Beihang University

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Condition monitoring and fault diagnosis are crucial for insuring flight safety. According to characteristics of complex systems, this paper proposes an intelligent system for off-line fault detection and diagnosis for gas path components in jet engine. Based on a machine learning methodology named Case-based Reasoning (CBR), this system consists of two types of case-bases, static case-base and dynamic case-base. Dynamic time warping (DTW) is used to retrieve dynamic cases by assessing the similarity between two dynamic sequence samples.

Original language	English
Pages (from-to)	1006-1009
Number of pages	4
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5253
DOIs	https://doi.org/10.1117/12.522341
State	Published - 2003
Event	Fifth International Symposium on Instrumentation and Control Technology - Beijing, China Duration: 24 Oct 2003 → 27 Oct 2003

Keywords

Artificial intelligent
Case-based reasoning
Dynamic time warping
Fault diagnosis
Jet engine

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10.1117/12.522341

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title = "Design of intelligent diagnosis system based on CBR for jet engine",

abstract = "Condition monitoring and fault diagnosis are crucial for insuring flight safety. According to characteristics of complex systems, this paper proposes an intelligent system for off-line fault detection and diagnosis for gas path components in jet engine. Based on a machine learning methodology named Case-based Reasoning (CBR), this system consists of two types of case-bases, static case-base and dynamic case-base. Dynamic time warping (DTW) is used to retrieve dynamic cases by assessing the similarity between two dynamic sequence samples.",

keywords = "Artificial intelligent, Case-based reasoning, Dynamic time warping, Fault diagnosis, Jet engine",

author = "Bo Xu and Xingshan Li and Jinsong Yu",

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journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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note = "Fifth International Symposium on Instrumentation and Control Technology ; Conference date: 24-10-2003 Through 27-10-2003",

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AU - Li, Xingshan

AU - Yu, Jinsong

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AB - Condition monitoring and fault diagnosis are crucial for insuring flight safety. According to characteristics of complex systems, this paper proposes an intelligent system for off-line fault detection and diagnosis for gas path components in jet engine. Based on a machine learning methodology named Case-based Reasoning (CBR), this system consists of two types of case-bases, static case-base and dynamic case-base. Dynamic time warping (DTW) is used to retrieve dynamic cases by assessing the similarity between two dynamic sequence samples.

KW - Artificial intelligent

KW - Case-based reasoning

KW - Dynamic time warping

KW - Fault diagnosis

KW - Jet engine

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DO - 10.1117/12.522341

M3 - 会议文章

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SN - 0277-786X

VL - 5253

SP - 1006

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JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Fifth International Symposium on Instrumentation and Control Technology

Y2 - 24 October 2003 through 27 October 2003

ER -

Design of intelligent diagnosis system based on CBR for jet engine

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Keywords

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