TY - JFULL AU - A. Ourici PY - 2009/7/ TI - Fault Classification of a Doubly FED Induction Machine Using Neural Network T2 - International Journal of Electrical and Computer Engineering SP - 1372 EP - 1376 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/4333 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 30, 2009 N2 - Rapid progress in process automation and tightening quality standards result in a growing demand being placed on fault detection and diagnostics methods to provide both speed and reliability of motor quality testing. Doubly fed induction generators are used mainly for wind energy conversion in MW power plants. This paper presents a detection of an inter turn stator and an open phase faults, in a doubly fed induction machine whose stator and rotor are supplied by two pulse width modulation (PWM) inverters. The method used in this article to detect these faults, is based on Park-s Vector Approach, using a neural network. ER -