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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 153656, 10 pages
Research Article

Wind Turbine Gearbox Fault Diagnosis Method Based on Riemannian Manifold

School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Received 27 February 2014; Accepted 30 March 2014; Published 16 April 2014

Academic Editor: Weichao Sun

Copyright © 2014 Shoubin Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


As multivariate time series problems widely exist in social production and life, fault diagnosis method has provided people with a lot of valuable information in the finance, hydrology, meteorology, earthquake, video surveillance, medical science, and other fields. In order to find faults in time sequence quickly and efficiently, this paper presents a multivariate time series processing method based on Riemannian manifold. This method is based on the sliding window and uses the covariance matrix as a descriptor of the time sequence. Riemannian distance is used as the similarity measure and the statistical process control diagram is applied to detect the abnormity of multivariate time series. And the visualization of the covariance matrix distribution is used to detect the abnormity of mechanical equipment, leading to realize the fault diagnosis. With wind turbine gearbox faults as the experiment object, the fault diagnosis method is verified and the results show that the method is reasonable and effective.