@inproceedings{47dbfd789a89413cbf64cfe3468c9c16,
title = "Gearbox fault feature detection based on adaptive parameter identification with Morlet wavelet",
abstract = "Localized defects in rotary machinery parts tend to result in impulse response in vibration signal, whose parameters provide a potential approach for localized fault diagnosis. A method combining the Morlet wavelet and Correlation Filtering, named Cyclic Morlet Wavelet Correlation Filtering (CMWCF), is proposed for identifying both the impulse response parameters and the cyclic period. Simulation study on cyclic impulse response signal with different SNR showed that CMWCF is effective in identifying the impulse response parameters and the cyclic period. Applications in gearbox vibration parameter identification for localized fault diagnosis showed that CMWCF is effective in identifying the parameters, and thus provides a feature detection method for gearbox fault diagnosis.",
keywords = "Correlation filtering, Fault diagnosis, Gearbox, Impulse response, Morlet wavelet",
author = "Wang, \{Shi Bin\} and Zhu, \{Zhong Kui\} and Wang, \{An Zhu\}",
year = "2010",
doi = "10.1109/ICWAPR.2010.5576410",
language = "英语",
isbn = "9781424465309",
series = "2010 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2010",
pages = "409--414",
booktitle = "2010 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2010",
note = "2010 8th International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2010 ; Conference date: 11-07-2010 Through 14-07-2010",
}