Application of Independent Component Analysis to the aero-engine fault diagnosis

Author

Zhonghai, Li ; Yan, Zhang ; Liying, Jiang ; Xiaoguang, Qu

Author_Institution

Shenyang Inst. of Aeronaut. Eng., Shenyang, China

fYear

2009

fDate

17-19 June 2009

Firstpage

5330

Lastpage

5333

Abstract

In view of the complexity of aero-engine system, there are massive correlated parameters, a novel method for aeroengine fault diagnosis based on independent component analysis (ICA) is proposed in this paper. ICA is already widely applied in many domains, but the aeroengine fault diagnosis domain hasn´t involved. ICA is used to detect fault by calculating I² statistics, and SVM models are constructed based on separate matrix of ICA. Applications illustrate the efficiency of the proposed approach.

Keywords

aerospace engines; fault diagnosis; independent component analysis; support vector machines; SVM models; aeroengine fault diagnosis; fault detection; independent component analysis; massive correlated parameters; separate matrix; statistics; support vector machines; Covariance matrix; Fault detection; Fault diagnosis; Independent component analysis; Matrix decomposition; Principal component analysis; Random variables; Statistics; Support vector machine classification; Support vector machines; Aeroengine fault diagnosis; Fault detection; ICA; SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5195066

Filename

5195066