Complex Adaptive Chrip Modal Decomposition and Its Application in the Condition Analysis of Power Generation Equipment

Complex signal decomposition technology is widely used in rotating machinery fault diagnosis and other fields. However, problems such as phase shift in the existing methods limit their application. Inspired by complex empirical mode decomposition and adaptive chirp mode matching methods, this study proposes a new complex signal decomposition approach, named Complex Adaptive Chrip Mode Decomposition (CACMD). CACMD completely solves the phase shift problem of traditional methods. This is exciting for applications that care about the phase of the signal. Based on CACMD, we propose an approach for constructing a complex signal time-frequency representation, that is, the CACMD Wigner-Ville distribution (CACMD-WVD). Thanks to the excellent performance of CACMD, CACMDWVD suppresses the interference terms of traditional WVD. The effectiveness of the proposed method has been verified by numerical simulation. Besides, a set of real signals of vibration signals during the startup process of a hydroelectric unit also illustrates the superiority of the method.