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52. On-line fault detection method for induction machines based on signal convolution

Author

Antonio Garcia Espinosa, Luis Romeral, Jordi-Roger Riba Ruiz, Juan Antonio Ortega, Jordi Cusidó, Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica, Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica, and Universitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group

Subjects
Errors de sistemes (Enginyeria), Computer science, Stator, Energy Engineering and Power Technology, Control engineering, Fault (power engineering), Signal, Fault detection and isolation, Convolution, law.invention, Fault indicator, Quantitative Biology::Subcellular Processes, Wavelet, law, Enginyeria electrònica::Electrònica de potència [Àrees temàtiques de la UPC], Motors elèctrics d'inducció, Electrical and Electronic Engineering, System failures (Engineering), Induction motor, Electric motors, Induction
Abstract

A new technique for induction motor fault detection and diagnosis is presented. This technique, which has been experimentally verified in stationary and non-stationary motor conditions, is based on the convolution of wavelet-based functions with motor stator currents. These functions are tuned to specific fault frequencies taking into account motor speed and load torque, thus considering variable operation conditions of the motor. Based on this technique an automatic system for fault diagnosis is also presented, which is suited for easy software implementation. Copyright © 2010 John Wiley & Sons, Ltd.

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