Method of Fault Character Extraction for Diesel Engine Based on Multivariate Time Series

Yan Liu; Wen Yuan; Xi Bing Li

doi:10.4028/www.scientific.net/AMM.151.661

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 151Method of Fault Character Extraction for Diesel...

Method of Fault Character Extraction for Diesel Engine Based on Multivariate Time Series

Abstract:

On the premise of data pre-processing by principal component analysis, in this paper, the largest Lyapunov exponent and generalized correlation dimension of multivariate time series are extracted based on the multivariate reconstruction presented. Though simulation analysis of coupling Rossler system, The results indicated that the method can identified and diagnosis fault accurately for complex system dynamics. The method has been used to fault character extraction for diesel engine with satisfactory results.

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Periodical:

Applied Mechanics and Materials (Volume 151)

Pages:

661-664

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.151.661

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Online since:

January 2012

Authors:

Yan Liu, Wen Yuan, Xi Bing Li

Keywords:

Diesel Engine, Fault Diagnosis, Multivariate Time Series, Principal Component Analysis (PCA)

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