Bearing Fault Diagnosis based on Vibration Signature Analysis using Discrete Wavelet Transform

A rolling element bearing defect is very common in rotating machine. It is an important part of, and widely used in plant machinery. Incipient fault diagnosis of rolling element bearing is essential because failure of machine due to bearing defect leads to serious consequence in terms of downtime and production loss. The production efficiency and plant safety can be improvise by continuous monitoring the condition of bearing .Vibration signal analysis plays important role in condition based monitoring because vibration signal carries dynamic information of machine, which enable it to detect different fault of machine. Many traditional features and analysis techniques are used in fault diagnosis such as time series analysis, frequency domain analysis and time frequency domain along with raw vibration signal. The use of discrte wavelet transforms (DWT) with Time synchronous averaging (TSA) is proposed in this work for fault diagnosis. The proposed work compares fault diagnosis capabilities of DWT using raw vibration signal and time synchronous signal of the machine vibration. Keyword : DWT, TSA , Bearing defect