A fault monitoring approach using model-based and neural network techniques applied to input–output feedback linearization control induction motor

  • Imadeddine Harzelli
  • Arezki Menacer
  • Tarek Ameid
Original Research


This paper presents a contribution to the fault monitoring approach and input–output feedback linearization control of the induction motor (IM) in the closed-loop drive. Two kinds of faults are considered in the machine, particularly the broken rotor bars and stator inter-turn short circuit faults. This approach has been employed to detect and identify simple and mixed defects during motor operation by utilizing advanced techniques. To achieve it, two procedures are applied for the fault monitoring: The model-based strategy, which used to generate a residual speed signal to indicate the presence of possible failures, by means the high gain observer in the closed-loop drive. However, this strategy is not able to recognise the type of faults but it can be affected by the disturbances. Therefore, the neural network (NN) technique is applied in order to identify the faults and distinguish them. However, the NN required a relevant database to achieve satisfactory results. Hence, the stator current analysis based on the HFFT combination of the Hilbert transform and fast Fourier transform is applied to extract the amplitude of the harmonics and used them as an input data set for NN. The obtained results show the efficiency of the fault monitoring system and its ability to detect and diagnosis any minor faults in a closed loop of the IM.


Induction motor (IM) Input–output feedback linearization (IOFL) control Fault monitoring Residual speed Neural network (NN) Hilbert transform (HT) 



Induction motor


Input-output feedback linearization


High gain observer


Neural network


Stator current envelope


K′ stator shorted turns

Uds, Uqs

(d, q) Axis voltages of the stator

Ids, Iqs

(d, q) Axis current components of the stator

Idr, Iqr

(d, q) Axis current components of the rotor


Short circuit ring current


Voltage vector


Current vector


Inductance matrix


Resistance matrix


Average radius of the air-gap


Direct voltage

Ua, Ub, Uc

Three phases voltages as, bs, cs

Ia, Ib, Ic

Three phases current as, bs, cs

U, U

(α, β) Axis voltages of the stator


Electrical rotor speed in rpm

ωref, Φref

Rotor reference speed and flux


k′ broken rotor bars


Measurable output


Control variable


State variable


Fundamental frequency


Motor slip


Resistance of the bar index k


Short circuit ring current of the portion k


Magnetic permeability of the air


Number of pole pairs


Air-gap mean diameter


Angle between two broken rotor bars


Stator resistance


Rotor resistance


Rotor bar resistance


Resistance of end ring


Rotor bar inductance


Inductance of end ring


Leakage inductance of stator


Mutual inductance


Number of turns per stator phase


Number of rotor bars


Length of the rotor


Inertia moment


Coefficient of damping

Te, TL

Electromagnetic torque, load torque


Current of the bar k


Current of the loop k


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Imadeddine Harzelli
    • 1
  • Arezki Menacer
    • 1
  • Tarek Ameid
    • 1
  1. 1.LGEB Laboratory, Electrical Engineering DepartmentBiskra UniversityBiskraAlgeria

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