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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 724-725Research on Fault Diagnosis Method of Wind Turbine...

Research on Fault Diagnosis Method of Wind Turbine Based on Wavelet Analysis and LS-SVM

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Abstract:

Aiming at the fault characteristics of high-speed gearbox fault diagnosis of wind turbine, a fault diagnosis method of combining wavelet analysis with least square-support vector machine (LS-SVM) is proposed. According to the method, the energy of frequency bands generated by wavelet decomposition and reconstruction of the high-speed gearbox's vibration signals in different fault states is normalized as eigenvectors, forming training and testing samples of LS-SVM fault classifier. Train the LS-SVM fault diagnosis model with the training samples and test the accuracy with the testing samples. The result of research shows that the fault diagnosis method based on the wavelet analysis and LS-SVM has good diagnostics effect.

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Applied Energy Technology

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Periodical:

Advanced Materials Research (Volumes 724-725)

Pages:

593-597

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.724-725.593

Citation:

Cite this paper

Online since:

August 2013

Authors:

Chang Liang Liu, Wei Xue Qi

Keywords:

Fault Diagnosis, High-Speed Gearbox, Support Vector Machine (SVM), Wavelet Analysis

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