Cyclostationarity and real order derivatives in roller bearing fault detection

Abstract

Various methods are used in the field of machine diagnostics for recognizing cyclostationarity in signals. The real order derivatives of vibration signals, however, have been rarely reported from the perspective of their effect on the performance of cyclostationarity detection methods. In this paper, we use real order derivatives together with spectral correlation, spectral coherence and squared envelope. Our results suggest that adjusting the order of derivative can enhance the analysis outcome of spectral correlation and squared envelope in particular. Remarkably, the results also suggest that squared envolope, when used alongside real-order derivatives, may replace spectral correlation and spectral coherence. This approach allows obtaining results with reduced computational power, making it advantageous for applications like industrial edge computing where cost-effective hardware is crucial.