Vibration signal analysis has been widely used in the fault detection and condition monitoring of rotation machinery. But the practical signals are easily polluted by noises in their transmission process. The raw signals should be processed to reduce noise and improve the quality before further analyzing. In this paper an improved wavelet threshold denosing method for vibration signal processing is proposed. Firstly, a new threshold is developed based on the VisuShrink threshold. The effect of noise standard deviation and wavelet coefficient is retained, and the correlation of wavelet decomposition scale is considered. Then, a new threshold function is defined. The new algorithm is able to overcome the discontinuity in hard threshold denoising method and reduce the distortion caused by permanent bias of wavelet coefficient in soft threshold denoising method. At last five kinds of threshold principles and three kinds of threshold functions are compared in processing the same signal, which is simulated as the mechanical vibration signal added white noises. The results show that the improved threshold is superior to the traditional threshold principles and the new threshold function is more effective than soft and hard threshold function in improving SNR and decreasing RMSE.

As the vibration signal of helical gears is nonlinear and nonstationary, it is very difficult to diagnose their faults based on the vibration signal analysis and processing, particularly when the gears rotate at low speed. In this paper, an applicable fault diagnosis approach is proposed based on Hilbert demodulation and EMD (empirical mode decomposition). Firstly, the modulated signals are extracted through Hilbert envelope demodulationand low pass filter. Furthermore, EMD is used to decompose the multi-component demodulated signal into a series of intrinsic mode functions (IMFs) whose instantaneous frequencies have a physically meaningful characterization of the original signal. Finally, the fault features of low-speed helical gear are obtained by the spectrum analysis to each IMF. The experiments of tooth broken fault diagnosis show that this method is more effective than traditional Hilbert demodulation analysis.

In order to investigate the life of bearings lubricated by solid lubricant (BLSL), which are installed in the rotational parts of spacecraft, a test platform has been developed. The platform can test the life of BLSL working under the vacuum environment with high-low temperature cycle conditions. The test platform consists of three systems of loading, measurement, and power and speed control. A corresponding computer program was also developed to measure, monitor and record test data. The working life of deep groove ball bearings lubricated by MoS2 solid lubricant was tested in 5×10-4Pa vacuum. The surface observation and analysis for the damage condition of the failed bearings were also conducted.