Spur Bevel Gearbox Fault Diagnosis Using Wavelet Packet Transform for Feature Extraction

Gear as an important transmission component in the production of modern industrial, used in all areas of production and life, its stable and reliable work has great social significance. In this paper, gear fault diagnosis based on wavelet packet for fault feature extraction has been proposed for gear fault detection and diagnosis. First, this paper analyzes the variations of gear fault vibration signal, using time-domain and frequency-domain sign attributes to characterize these gear vibration signal and then extract fault sign attributes by using wavelet packet. This paper introduces a kind of new method for wavelet de-noise, eliminating the problem of wavelet de-noise decompose level and de-noise threshold value selection, at the same time analysis a kind of wavelet packet transform method, eliminating the frequency and frequency band confusion, reducing the error in fault sign attribute extraction. At last, using fault simulation platform to simulate different conditions and different gear fault vibration signals. The results demonstrate that this method can accurately and reliably detect failure modes in a gearbox.