Adaptively Detecting the Transient Feature of Faulty Wind Turbine Planetary Gearboxes by the Improved Kurtosis and Iterative Thresholding Algorithm

It is significant for diagnosing the early faults of wind turbine planetary gearboxes. However, the weak transient feature generated by the early gear failure is often submerged in other vibration signals and noise, thus this paper discusses a new automatic sparse representation method for detecting...

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Published in:	IEEE access Vol. 6; pp. 14602 - 14612
Main Authors:	Qin, Yi, Zou, Jingqiang, Cao, Folin
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.01.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	adaptive feature extraction Algorithms Dictionaries early fault detection Fault diagnosis Feature extraction Gearboxes Gears improved kurtosis index Iterative algorithms Kurtosis Morlet wavelet Morlet wavelet transform sparse optimization Transient analysis Vibrations Wavelet transforms Wind turbines
ISSN:	2169-3536, 2169-3536
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Abstract	It is significant for diagnosing the early faults of wind turbine planetary gearboxes. However, the weak transient feature generated by the early gear failure is often submerged in other vibration signals and noise, thus this paper discusses a new automatic sparse representation method for detecting weak transients. An improved Morlet wavelet which strictly satisfies the admissibility condition is constructed, and it is highly beneficial to sparsely separating signal component. By the use of the improved Morlet wavelet dictionary and Fourier dictionary, the transient component can be extracted by solving a sparse problem. Aiming at the drawback of the kurtosis and squared envelope spectrum (SES) negentropy in evaluating the similarity between the extracted transient and the original transient, an improved kurtosis index is designed, which can be used to search the optimal sparse parameters. Then, by the use of the improved kurtosis index and iterative thresholding method, an adaptively iterative thresholding shrinkage algorithm is proposed to detect the repetitive transients from the planetary gearbox signal. The comparative results in simulation and experiments show that the proposed method can more effectively and accurately perform the fault diagnosis of wind turbine planetary gearboxes than the infogram method and the resonance-based signal decomposition method.
AbstractList	It is significant for diagnosing the early faults of wind turbine planetary gearboxes. However, the weak transient feature generated by the early gear failure is often submerged in other vibration signals and noise, thus this paper discusses a new automatic sparse representation method for detecting weak transients. An improved Morlet wavelet which strictly satisfies the admissibility condition is constructed, and it is highly beneficial to sparsely separating signal component. By the use of the improved Morlet wavelet dictionary and Fourier dictionary, the transient component can be extracted by solving a sparse problem. Aiming at the drawback of the kurtosis and squared envelope spectrum (SES) negentropy in evaluating the similarity between the extracted transient and the original transient, an improved kurtosis index is designed, which can be used to search the optimal sparse parameters. Then, by the use of the improved kurtosis index and iterative thresholding method, an adaptively iterative thresholding shrinkage algorithm is proposed to detect the repetitive transients from the planetary gearbox signal. The comparative results in simulation and experiments show that the proposed method can more effectively and accurately perform the fault diagnosis of wind turbine planetary gearboxes than the infogram method and the resonance-based signal decomposition method.
Author	Yi Qin Jingqiang Zou Folin Cao
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SubjectTerms	adaptive feature extraction Algorithms Dictionaries early fault detection Fault diagnosis Feature extraction Gearboxes Gears improved kurtosis index Iterative algorithms Kurtosis Morlet wavelet Morlet wavelet transform sparse optimization Transient analysis Vibrations Wavelet transforms Wind turbines
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Title	Adaptively Detecting the Transient Feature of Faulty Wind Turbine Planetary Gearboxes by the Improved Kurtosis and Iterative Thresholding Algorithm
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