Compound fault diagnosis of rolling bearings in variable speed based on adaptive chirp mode decomposition and generalized demodulation

Abstract When rolling bearings work under variable speed conditions and experience compound faults, their vibration signal components become more complex, some of which coexist in a narrow frequency band, and are easy to interfere with each other and coupled together. In some cases, the tachometer cannot or is difficult to install, resulting in insufficient speed information, further increasing the challenge of fault diagnosis. Aiming at the above problem of compound fault diagnosis in variable speed without tachometer, a compound fault diagnosis method of rolling bearings in variable speed based on adaptive chirp decomposition and generalized demodulation is proposed to solve the problem of determining fault components in time–frequency ridges extracted by ridge search algorithm. Firstly, the fast path search algorithm and ridge extraction method are used to fit the rotation frequency equation, and then the instantaneous frequency equation and phase function are obtained by combining the bearing fault characteristic coefficients. Then the signal components and the optimized instantaneous frequency ridge are obtained by adaptive chirp mode decomposition. Finally, the signal is stabilized by generalized demodulation. The method can optimize the initial instantaneous frequency of the vibration signal, accurately extract the fault characteristic components, and ensure that the time-varying fault characteristic component has a high energy concentration after generalized demodulation, and the result is not interfered by other signal components. Experimental analysis shows that the proposed method can accurately extract the compound fault characteristics of rolling bearings.