采用具有线性相位的B样条小波,应用图形显示算法并结合小波变换快速算法将信号分解到不同的频带上,且分解结果和原信号长度保持一致,可对信号进行深层次的处理,克服了传统的信号处理方法不易提取微弱信息的不足通过对矿用斜轴式柱塞泵振动信号的分析,分离出了配流副磨损、球铰松动、缸体及泵轴支撑轴承的故障特征,为液压泵的故障诊断提供了依据,并为信噪分离、微弱信号提取及设备的早期故障诊断提供了一条有效途径 The B-spline wavelet with linear phase is applied to decompose the signal into different frequency bands by applying the graphic display algorithm combined with the fast algorithm of wavelet transform. The decomposition result is consistent with the original signal length, and the signal can be deeply processed, The traditional signal processing method is not easy to extract the weakness of the lack of information through the mining inclined shaft piston pump vibration signal analysis, separated from the deputy with wear and tear, ball hinge loose, cylinder and pump shaft bearing failure characteristics for the hydraulic Pump fault diagnosis provides a basis for the signal and noise separation, weak signal extraction and equipment for early fault diagnosis provides an effective way