Bearing fault diagnosis using wavelet domain operator-based signal separation
- Resource Type
- Conference
- Authors
- Hou, Borui; Yan, Ruqiang; Chen, Xuefeng; Liu, Yanmeng
- Source
- 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Instrumentation and Measurement Technology Conference (I2MTC), 2017 IEEE International. :1-5 May, 2017
- Subject
- Bioengineering
Engineering Profession
General Topics for Engineers
Signal Processing and Analysis
Fault diagnosis
Vibrations
Null space
Continuous wavelet transforms
Wind turbines
fault diagnosis
continuous wavelet transform
null space pursuit
- Language
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.