Open AccessAn Extender Kalman Filter-based Induction Machines Faults Detection
Author(s) -
Abdelghani Chahmi,
Mokhtar Bendjebbar,
Bertrand Raison,
Mohamed Benbouzid
Publication year - 2016
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v6i2.pp535-548
Subject(s) - fault detection and isolation , computer science , kalman filter , context (archaeology) , extended kalman filter , fault (geology) , filter (signal processing) , signal (programming language) , control engineering , artificial intelligence , engineering , paleontology , seismology , actuator , computer vision , biology , programming language , geology
This paper deals with the detection and localization of electrical drives faults, especially those containing induction machines. First, the context of the study is presented and an Extended Kalman Filter is described for induction machines fault detection. Then the modeling procedure under faulty conditions is shown, and the machine diagnosis methods are developed. The proposed diagnosis approach requires only little experimental data, and more importantly it provides efficient simulation tools that allow characterizing faulty behavior.Fault detection uses signal processing techniques in known operating phases (fixed speed), considering and locating malfunctions.