%X On-line condition monitoring (CM) of heavy rotating machines plays an important role in industrial plants. It continuously provides the machine status which allows the detection of abnormalities and problems at incipient stages as well as the intervention of maintenance and production personnel at proper time to keep the plant running and to avoid serious accidents. Most of rotating machine failures is due to bearing faults. The ability to predict the bearing failure at early stage is of great importance. This paper discusses the concept of acoustic emission (AE) monitoring techniques, in which signal processing measurements are used to create a simple integrated structure for the integration of condition monitoring and real-time information management of systems. This allows AE signals with frequency range 100 KHz - 1MHz to be processed and analyzed using advanced signal processing and data analysis techniques. The effectiveness for AE monitoring system for early detection of healthy bearing is conducted. A system that is being developed to provide a test-bed for this concept is described. ©2007 IEEE.
%K Acoustic emission testing; Acoustic emissions; Acoustics; Bearings (structural); Data processing; Fault detection; Industrial emissions; Industrial plants; Information management; Management information systems; Monitoring; Real time systems; Rotating machinery; Rotation; Signal processing, Acoustic emission monitoring; AE signals; Bearing failures; Bearing faults; Data analysis techniques; Early detections; Early stages; Frequency ranges; Integrated structures; Line fault detections; Monitoring systems; Monitoring techniques; On-line condition monitoring; Production personnels; Rotating machines, Condition monitoring
%L scholars193
%J 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007
%O cited By 9; Conference of 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 ; Conference Date: 25 November 2007 Through 28 November 2007; Conference Code:74506
%R 10.1109/ICIAS.2007.4658516
%D 2007
%A M.A.A. Elmaleeh
%A N. Saad
%A N. Ahmed
%A M. Awan
%T On-line fault detection & diagnosis of rotating machines using acoustic emission monitoring techniques
%C Kuala Lumpur
%P 897-900