Open AccessMixed model‐based and signal‐based approach for open‐switches fault diagnostic in sensorless speed vector controlled induction motor drive using sliding mode observer
Author(s) -
Maamouri Rebah,
Trabelsi Mohamed,
Boussak Mohamed,
M'Sahli Faouzi
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.5131
Subject(s) - control theory (sociology) , fault detection and isolation , observer (physics) , fault (geology) , engineering , induction motor , stationary reference frame , signal (programming language) , computer science , control engineering , rotor (electric) , electronic engineering , voltage , artificial intelligence , actuator , control (management) , physics , quantum mechanics , electrical engineering , programming language , mechanical engineering , seismology , geology
This study deals with a mixed model‐based and signal‐based approach for sensorless speed‐controlled induction motor drive (IM) and insulated‐gate bipolar transistors open‐switch fault diagnosis. In comparison to the classical sensored drive systems, this structure presents particular characteristics in post‐fault operation mode which can be taken into account for fault detection and identification process designing. Firstly, the fault effects analysis is achieved in the abc frame of the IM. Based on such analysis, a diagnostic algorithm, using the measured and estimated currents, is used to define the fault indices, which allow the detection of single open‐switch, multiple open‐switch and open‐phase faults. The sensorless control algorithm used for rotor speed estimation, as well as the fault diagnostic algorithm, are all based on a first‐order sliding mode observer. In addition to the simplicity and the fast fault detection, there are no‐additional sensors or extra‐hardware used by the proposed method. Experimental results, based on a dSPACE DS1104 controller board and a 3‐kW induction machine, are shown to validate the proposed strategy.