Title :
Bearing fault detection based on instantaneous energy spectrum
Author_Institution :
Dept. of Electromech. Eng., Shijiazhuang Inst. of Railway Technol., Shijiazhuang, China
Abstract :
A novel method for detection and diagnosis the bearing fault according to instantaneous energy spectrum (IES) based on empirical mode decomposition (EMD) method is presented. EMD can adaptively decompose the vibration signal into a series of zero mean oscillatory functions called intrinsic mode functions (IMFs). Hilbert transform can track the instantaneous amplitude and instantaneous frequency of the intrinsic mode functions at any instant. Then the instantaneous energy spectrum can be calculated based on the intrinsic mode functions. The instantaneous energy is thus associated with the deterioration in bearing condition and can be utilized for bearing fault detection. The experimental results show that instantaneous energy spectrum is a sensitive indicator of the existence of damage in the gearbox.
Keywords :
Hilbert transforms; acoustic signal processing; condition monitoring; fault diagnosis; gears; machine bearings; vibrations; EMD method; Hilbert transform; bearings; deterioration; empirical mode decomposition; fault detection; fault diagnosis; gearbox; instantaneous amplitude; instantaneous energy spectrum; instantaneous frequency; intrinsic mode functions; vibration signal; zero mean oscillatory functions; Fault detection; Fault diagnosis; Time frequency analysis; Transforms; Transient analysis; Vibrations; Wavelet analysis; bearing; empirical mode decomposition; fault detection; instantaneous energy spectrum; vibration;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569849