Fault Diagnosis of Wind Turbine Based on ELMD and FCM
Xianjin Luo*, Xiumei Huang*
Identifiers and Pagination:Year: 2014
First Page: 716
Last Page: 720
Publisher Id: TOMEJ-8-716
Article History:Received Date: 19/11/2014
Revision Received Date: 06/12/2014
Acceptance Date: 06/12/2014
Electronic publication date: 31/12/2014
Collection year: 2014
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In view of failure characteristics of wind turbine gear box, this paper put forward a method for fault diagnosis based on the ensemble local means decomposition (ELMD) and fuzzy C-means clustering (FCM) method. By resolving the vibration signal of different fault state of high speed gear box by ELMD, the PF component was obtained with its singular value, which was composed of known sample followed by a test sample as the feature vector. The known sample was clustered by using the FCM clustering, and the test sample was recognized and classified . The experimental results show that the method for fault diagnosis based on ELMD and FCM clustering has good diagnosis results.