Title :
Fault detection and prognosis methods for a monitoring system of rotating electrical machines
Author :
Ciandrini, Chiara ; Gallieri, Marco ; Giantomassi, Andrea ; Ippoliti, Gianluca ; Longhi, Sauro
Author_Institution :
Dipt. di Ing. Inf. Gestionale e dell´´Autom., Univ. Politec. delle Marche, Ancona, Italy
Abstract :
Companies are involved in a high competition for reducing the cost of production in order to maintain their market shares. Since the costs of maintenance contribute a substantial portion of the production costs, companies must budget maintenance effectively. Machine deterioration prognosis can decrease the costs of maintenance by minimizing the loss of production due to machine breakdown and avoiding the overstocking of spare parts. This paper gives a review of some fault detection and prognosis methods to diagnose faults and failure on rotating electrical machines. To develop the monitoring system accelerometers have been used to acquire vibration measurements. Performance are studied on a laboratory-scale experimental system.
Keywords :
electric machines; fault diagnosis; fault detection; machine deterioration prognosis; monitoring system; prognosis method; rotating electrical machine; Artificial neural networks; Circuit faults; Fault detection; Indexes; Monitoring; Principal component analysis; Vibrations;
Conference_Titel :
Industrial Electronics (ISIE), 2010 IEEE International Symposium on
Conference_Location :
Bari
Print_ISBN :
978-1-4244-6390-9
DOI :
10.1109/ISIE.2010.5637762