Intelligent condition monitoring system using acoustic emission

Some aspects of using AE for detecting an early development of failure in rolling element bearings are discussed. The results of an experimental study into ball bearing failure and the resulting change in AE signal are presented. The paper presents the results obtained by traditional statistical analysis based techniques and those obtained via a neural networks based approach. The results implicate an opportunity to perform the monitoring and diagnostic functions in near real-time.