%A Peng ZHOU, Zhike PENG, Shiqian CHEN, Yang YANG, Wenming ZHANG %T Non-stationary signal analysis based on general parameterized time--frequency transform and its application in the feature extraction of a rotary machine %0 Journal Article %D 2018 %J Front. Mech. Eng. %J Frontiers of Mechanical Engineering %@ 2095-0233 %R 10.1007/s11465-017-0443-0 %P 292-300 %V 13 %N 2 %U {https://journal.hep.com.cn/fme/EN/10.1007/s11465-017-0443-0 %8 2018-03-16 %X

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time–frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.