A gear fault diagnosis using Hilbert spectrum based on MODWPT and a comparison with EMD approach

When gear fault occurs, the vibration signals always display non-stationary behavior. Therefore time-frequency analysis has become the well-accepted technique for vibration-based gear fault diagnosis. This paper presents the application of a new time-frequency signal processing technique, the Hilbert spectrum based on the maximal overlap discrete wavelet packet transform (MODWPT), to the analysis of simulation signals and gear fault vibration signals measured by the acceleration sensor fixed on the bearing house. As long as the decomposition scale and disjoint dyadic decomposition are chosen suitably, the original signal could be decomposed into a set of monocomponent signals whose instantaneous amplitude and instantaneous frequency own physical meaning. After the instantaneous amplitude and instantaneous frequency of each monocomponent signal are calculated by using MODWPT, the corresponding Hilbert spectrum could be obtained by assembling the instantaneous amplitude and instantaneous frequency. The simulation and practical application examples show that the Hilbert spectrum base on the MODWPT is superior to another competing method, namely, EMD (empirical mode decomposition)-based method, which has been widely used in the gear fault diagnosis.