Tao Liu

In order to extract and enhance the weak fault feature of rolling element bearings in strong noise conditions, the Empirical Wavelet Transform (EWT) is improved and a novel fault feature extraction and enhancement method is proposed by combining the Maximum Correlated Kurtosis Deconvolution (MCKD) and improved EWT method. At first, the MCKD method is conducted to de-noise the signal by eliminating the non-impact components. Then, the Fourier spectrum is segmented by local maxima or minima in the envelope of the amplitude spectrum with a pre-set threshold based on the noise level. By building up the wavelet filter banks based on the spectrum segmentation result, the signal is adaptively decomposed into several sub-signals. Finally, by choosing the most meaningful sub-signal with the maximum kurtosis, the fault feature can be extracted in the squared envelope spectrum and teager energy operator spectrum of the chosen component. Both simulations and experiments are performed to validate the effectiveness of the proposed method. It is shown that the spectrum segmentation result of improved EWT is more reasonable than the traditional EWT in strong noise conditions. Furthermore, compared with commonly used methods, such as the Fast Kurtogram (FK) and the Optimal Wavelet Packet Transform (OWPT) method, the proposed method is more effective in the fault feature extraction and enhancement of rolling element bearings.

Deployable structures are so widely employed in spacecraft, which are folded during launch to fit inside the launcher's payload fairing and deployed to be the structures on-orbit. In order to more accurately obtain vibration properties of the solar arrays with joint clearances, a set of experiment device is developed, and vibrations of the deployable structure are stimulated by means of hammer impact method. Constant-Q nonstationary Gabor frame transform and Fourier transform are described and employed to analyze vibration properties of the deployable structure. It is found that the damping becomes greater along with the vibration frequencies increasing, and the energy of vibration of the outer panel tends to distribute in more frequencies in contrast with the inner panel. Compared with the deployed state, a more serious wide-frequency phenomenon occurs in the folded situation, which indicates that the effect of the clearance is stronger in the folded situation. It is shown that the vibration analysis using Constant-Q nonstationary Gabor transform and Fourier transform is helpful to reveal dynamic performance of this type of deployable structures.

During touchdowns of active magnetic bearings (AMB), the violent collision between rotors and touchdown bearings (TDB) can cause damages to both parts. Orbit response recognition provides a way for the AMB controller to automatically switch the control algorithm to actively suppress the rotor–TDB vibration and promptly relevitate the rotor during touchdowns. A novel method based on Hilbert transform (HT) is proposed to recognize the orbit responses (pendulum vibration, combined rub and bouncing, and full rub) in touchdowns. In this method, the rotor suspension status is monitored by the AMB controller in real-time. When touchdown is detected, the rotor displacement signal during the sampling period is intercepted, and the instantaneous frequency (IF) is calculated by HT. Then, the local variance of IF during the sampling period is calculated, and it is compared with the threshold value. Combined rub and bouncing can be identified for it has the largest local variance. Finally, the mean value of IF during the sampling period is calculated and is compared with the other threshold value. Pendulum vibration can be identified for it has a lower and fixed mean value, while full rub has a larger value. The principle of the recognition method is demonstrated by the simulated results of a thermo-dynamic model. The results reveal that the method is feasible in recognizing the orbit responses and can be implemented in the AMB controller to help switch the control algorithms automatically in case of touchdowns.