@inproceedings{6947d7cc6fe54d399ff4dc7f53e0a7af,
title = "Bearing fault diagnosis using wavelet domain operator-based signal separation",
abstract = "This paper presents a new bearing fault diagnosis approach using wavelet domain operator-based signal separation. The measured vibration signal is first preprocessed using the continuous wavelet transform (CWT) to filter unwanted noise. Then an operator-based signal separation approach, called null space pursuit (NSP), is applied to decomposing the signal into a series of subcomponents and residues in accordance with their characteristics. Subsequently, the selected subcomponent with the maximum Kurtosis value is analyzed by the envelop spectrum to identify potential fault-related characteristic frequency components. Experimental studies from a real wind turbine gearbox have verified the effectiveness of the presented approach for bearing fault diagnosis.",
keywords = "Continuous wavelet transform, Fault diagnosis, Null space pursuit",
author = "Borui Hou and Ruqiang Yan and Xuefeng Chen and Yanmeng Liu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2017 ; Conference date: 22-05-2017 Through 25-05-2017",
year = "2017",
month = jul,
day = "5",
doi = "10.1109/I2MTC.2017.7969989",
language = "英语",
series = "I2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "I2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings",
}