Fault Diagnosis of Gear based on Translation Invariant Multiwavelet Transform

Abstract

The vibration signal which reflecting the equipment fault feature often drowned in background noise when mechanical equipment occurring fault. The fault feature is very difficult to extract through frequency spectrum analysis. The translation invariant multiwavelet denoising method is applied to noisy impact simulation signal and extract impact features hidden in the noise. Then the method is applied to the signal analysis of gearbox test bed,the experimental results show that the impact feature frequency of broken tooth gearbox can be effectively extracted through the translation invariant multiwavelet denoising method and broken teeth fault can be diagnosed,an accurate basis for fault diagnosis is provided. Through the simulation and experiment analysis,the effectiveness of translation invariant multiwavelet denoising method in fault diagnosis is verified.

Keywords

• Multiwavelet;Translation invariant;Signal denoising;Fault diagnosis