Enhancing gearbox vibration signals under time-varying operating conditions by combining a whitening procedure and a synchronous processing method

Abstract

Condition monitoring is very important to avoid unexpected breakdowns of expensive rotating machines found in the power generation and mining industries. The fault information in vibration signals is often buried in low energy frequency bands. In addition to this, time-varying operating conditions and the presence of impulsive components result in the signal to have time-varying spectral content, which impedes the condition inference process. The instantaneous power spectrum is a powerful method that for bearing and gear damage detection under time-varying operating conditions. In this work, we propose a new method of using the instantaneous power spectrum for improved fault diagnosis under time-varying conditions by enhancing the fault information in the vibration signals. It is shown on experimental datasets that the proposed method enhances the fault information in the signal, whereafter it can be used to obtain reliable condition indicators under time-varying operating conditions.