Wind Turbine Gearbox Fault Detection Based on Multifractal Analysis

Chang Zheng Chen; Ping Ping Pan; Qiang Meng; Yan Ling Gu

doi:10.4028/www.scientific.net/AMR.644.312

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 644Wind Turbine Gearbox Fault Detection Based on...

Wind Turbine Gearbox Fault Detection Based on Multifractal Analysis

Abstract:

The presence of irregularity in periodical vibration signals usually indicates the occurrence of wind turbine gearbox faults. Unfortunately, detecting the incipient faults is a difficult job because they are rather weak and often interfered by heavy noise and higher level macro-structural vibrations. Therefore, a proper signal processing method is necessary. We used the wavelet-based multifractal method to extract the impulsive features buried in noisy vibration signals. We first calculated the wavelet transform modulo maxima lines from the real vibration signals, then, obtained the singularity spectrum from the lines. The analysis results of the real signals showed that the proposed method can effectively extract weak fault features.

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Periodical:

Advanced Materials Research (Volume 644)

Pages:

312-316

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.644.312

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Online since:

January 2013

Authors:

Chang Zheng Chen, Ping Ping Pan, Qiang Meng, Yan Ling Gu

Keywords:

Feature Extraction, Incipient Fault, Singularity Spectrum, Wind Turbine Gearbox

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