As diesel engine vibration signal characteristic frequency band and noise frequency band exist overlap phenomenon, so it was diffcult to choose suitable wavelet threshold for wavelet threshold denoising in vibration signal processing. In order to extract fault features from engine vibration signal, a new method using LMS Adaptive Filtering Denoising based on wavelet transform for diesel engine vibration signals was proposed. Reconstruct signal that removed wavelet detail parts including noise of the multi-scale decomposition of wavelet transforms was used as input signal for LMS adaptive filter firstly. the first layer wavelet detail parts of the multi-scale decomposition of wavelet transform was used as reference input signal secondly, and Then the optimal filter for signal-noise decomposition was realized. Using the adaptive filter based on the wavelet transform to remove noise from diesel engine vibration signals, the filter has excellent filtering capability. Application example demonstrates that this method is excellent to realize the optimal estimate for the valuable signal and noise of the diesel engine vibration signal, it don’t need to choose suitable wavelet threshold for wavelet threshold denoising in vibration signal processing, its set parameter is few and easy to control. using this new method, the engine vibration fault discrimination is increased.

The importance of impact noise control of hydraulic pile drivers is elaborated. The theory of acoustic fluidstructure coupling and the corresponding finite element method are introduced. According to the theoretical characteristics of impact frequency spectrum, the relation of noise and buffer time is analyzed. Using the finite element software ANSYS/LSDYNA, the numerical simulation of impact of a pile driver is carried out. The results show that the impact noise can be reduced by prolonging the buffer time.