Application of AE Techniques in Condition Monitoring and Diagnosis of Rotating Machinery

Condition monitoring (CM) is the process of monitoring a parameter of condition in machinery, such that a significant change is indicative of a developing failure. It is of great practical significance in manufacturing industry since it provides updated information regarding machine status on-line. This allows maintenance to be scheduled in order to avoid accidental outages that cause production loss and may lead to catastrophic machine failure. Rotating machines are recognized as the core and fundamental equipment of most engineering systems such as petrochemical plants, automotive industry, power stations, oil refinery, etc. that necessitate precise and ingenious performance. Bearings represent the most important part in rotating machinery. Major problems in the machines are due to bearing faults. It is therefore necessary to monitor and diagnose the bearing operating condition in order to avoid serious problems in the machinery.  This paper discusses the concept of acoustic emission (AE) monitoring techniques for detection and diagnosis of bearing deterioration and faults.  The acquired AE signals are processed and analyzed using LabVIEW and MATLAB to detect bearing problems at incipient stages