| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 560702 | Mechanical Systems and Signal Processing | 2012 | 9 Pages |
This paper addresses an application of recently developed Hilbert–Huang transform (HHT) signal processing technique on AE feature extraction of natural fatigue cracks in rotating shafts providing an energy–frequency–time distribution with adaptable precision. A special purpose built test rig was employed for generating natural rotating fatigue crack on a shaft. Acoustic emission signals are non-stationary and nonlinear transients, whose waveforms and arrival times are unknown. A common problem in AE signal processing is to extract physical parameters of interest when these involve joint variations of time and frequency. It has been found that HHT appears to be a better tool compared to fast Fourier transform and continuous wavelet transform for natural fatigue crack characterization in a rotating rotor in all experiment cases. It was concluded that HHT-based AE technology successfully extracted the features of natural fatigue cracks induced on rotating shafts.
▶ A special device was employed for generating natural rotating shaft fatigue cracks. ▶ HHT analysis can effectively show the fatigue crack AE features. ▶ HHT appears to be a better tool compared to FFT and Wavelet in the experiment cases.
