Adaptive fault diagnosis of rolling bearings based on EEMD and demodulated resonance

In order to solve problems affecting application of traditional demodulated resonance technology, such as, the lower signal to noise ratio for original signal of rolling bearings and the parameter selection of a band-pass filter depending on experiences of individuals, a method for fault diagnosis of rolling bearings based on combining EEMD adaptive denoising with adaptive demodulated resonance was presented. Firstly, the original signal was decomposed into many components via EEMD adaptively, and adaptive reconstruction was performed by using the correlation coefficient method to highlight fault characteristic signals. Then, the central frequency and bandwidth of a band-pass filter were determined with spectral kurtosis. Last, the filtered signal was analyzed by using energy operator demodulation spectrum. Numerical simulation signals and a rolling bearing test results showed the validity of the proposed method.