TY - JOUR
T1 - Two current sensor fault detection and isolation schemes for induction motor drives using algebraic estimation approach
AU - Rkhissi-Kammoun, Yosra
AU - Ghommam, Jawhar
AU - Boukhnifer, Moussa
AU - Mnif, Faisal
N1 - Publisher Copyright:
© 2018 International Association for Mathematics and Computers in Simulation (IMACS)
PY - 2019/3
Y1 - 2019/3
N2 - The paper focuses on single and multiple current sensors fault detection and isolation (FDI) for induction motor (IM) drives using only two current sensors. Two model based diagnosis methods are proposed to estimate the current residuals dynamics in the stationary reference frame: The first one is a differential algebraic estimation of fault dynamics and the second one is based on a combination of the Robust Integral Sign of the Error (RISE) observer with the algebraic approach. After detecting the fault occurrence, a logic based decision unit is then built to identify the faulty sensors. The resulting residuals are robust to load torque disturbances. Moreover, the developed fault estimators are simple with a 1-D model, based only on the input–output measurements and their derivatives and do not require a bank of observers. Furthermore, the used residual threshold is well defined and is suitable for the whole operating range. The ability of diagnosing the recovery of a sensor from a fault is also demonstrated. The validity of the developed approaches is analytically proved and a comparative study is carried out between the two FDI schemes.
AB - The paper focuses on single and multiple current sensors fault detection and isolation (FDI) for induction motor (IM) drives using only two current sensors. Two model based diagnosis methods are proposed to estimate the current residuals dynamics in the stationary reference frame: The first one is a differential algebraic estimation of fault dynamics and the second one is based on a combination of the Robust Integral Sign of the Error (RISE) observer with the algebraic approach. After detecting the fault occurrence, a logic based decision unit is then built to identify the faulty sensors. The resulting residuals are robust to load torque disturbances. Moreover, the developed fault estimators are simple with a 1-D model, based only on the input–output measurements and their derivatives and do not require a bank of observers. Furthermore, the used residual threshold is well defined and is suitable for the whole operating range. The ability of diagnosing the recovery of a sensor from a fault is also demonstrated. The validity of the developed approaches is analytically proved and a comparative study is carried out between the two FDI schemes.
KW - Current sensor fault detection and isolation
KW - Differential algebraic approach
KW - Electric vehicle
KW - Induction motor
KW - RISE observer
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U2 - 10.1016/j.matcom.2018.09.010
DO - 10.1016/j.matcom.2018.09.010
M3 - Article
AN - SCOPUS:85054464619
SN - 0378-4754
VL - 157
SP - 39
EP - 62
JO - Mathematics and Computers in Simulation
JF - Mathematics and Computers in Simulation
ER -