利用真实信号小波系数相邻层间相关性强的特性,将基于小波熵的相关去噪法应用于矿用齿轮箱振动信号的处理,进行有用系数和噪声系数的划分,并对有用的小波系数进行重构,恢复原有真实信号,去噪过程中采用小波熵自适应设定阈值。为比较小波自适应相关去噪和硬阈值与传统相关性去噪的性能,分别对仿真信号和齿轮箱实测振动信号进行去噪处理,通过3种去噪方法的重构波形对比和信噪比与标准差的定量评价,以及实测信号的功率谱分析,表明小波熵相关去噪法有效提高了矿用齿轮箱振动信号的可信度。
A de-noising method based on Adaptive Wavelet Correlation Analysis (AWCA) is attempted to be applied to the vibration signal for mine gearbox using characteristics of strongly correlative between adjacent layers of the wavelet coefficients of real signal. The wavelet coefficients can be divided into available coefficients and noise coefficients, and adaptive threshold method based on wavelet entropy is applied, the available coefficients are reconstructed to restore the original real signal after de-noising process. The method is applied to the simulated signal and vibration signal of mine gearbox respectively and is compared with methods of wavelet hard threshold and traditional correlation de-noising in the reconstructed waveforms, SNR and standard deviation, and the measured signal power spectral chart. The results indicate that the de-noising method based on AWCA can effectively remove noise and reserve available signal and can effectively improve the reliability of mine gearbox vibration signal.
