Title :
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
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;
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
DOI :
10.1109/CCDC.2009.5195066
