说明：  ：提出一种基于对偶树复小波块阈值的信号降噪方法，并将其成功应用于机械故障诊断中。机械设备的振动信号都或多或少地含有噪声，导致弱故障信息的提取一直是故障诊断的难点和热点。提出的降噪方法充分利用对偶树复小波变换的平移不变性和块阈值法的更优估计特性，可以获得比常规的小波降噪方法以及基于常规离散正交小波变换的 NeighBlock 降噪法更高的信噪比， 不仅能有效抑制高斯白噪声， 还能够去除冲击信号中的脉冲噪声。
(：A denoising method of block thresholding based on DT-CWT (Dual-tree complex wavelet transform) is proposed, aiming at the difficulty of extracting weak failure information in machinery vibration signals. The presented method can obtain higher signal-to-noise ratio (SNR) than NeighBlock and other common methods based on orthonormal discrete wavelet trans- form, because of improving asymptotic optimality of block thresholding estimator and shift invariance of DT-CWT. It can not only suppress white Gaussian noise, but also remove spike pulse noise in impulsive signal effectively.)