fault feature
5.Abstract: In order to process signal in depth and to extract the fault feature from original signal in machinery diagnosis，the graphical display algorithm that can keep the data length of wavelet transform results the same as that of original signal is used.The fault diagnosis of a bend axial piston pump via B-spline wavelet that has linear phase is provided.The results of study demonstrate that the new method has excellent feature and the weak fault signal can be extracted from the strong vibration background of the pump.
6.A singularity detection and denoising method based on analytic wavelet transform(AWT) and signal reconstruction was proposed to improve the accuracy of signal singularity detection and the efficiency of fault diagnosis. According to the difference of propagation characteristics of wavelet transform modulus maximum(WTMM) of signal and noise along the scale direction,signal denoising and fault feature extraction were realized.
7.It can be concluded that: presently the eastern segment of Qilianshan fault zone and its boundary region with Zhuanglanghe fault and Haiyuan fault is in an obvious background of strain accumulation; Lanzhou and Linxia area near the southern segment of Zhuanglanghe fault display a feature of strain accumulation in certain degree.
