Induction Motor Windings Faults Detection Using Active and Reactive Power Based Model Reference Adaptive System Estimator

Collince Georges Fouoken, Blaise Jean Teguia, Godpromesse KENNE

Abstract


The paper is concerned with detection of a stator and rotor winding faults in a squirrel-cage induction motor. The idea of the fault detection is based on a hypothesis that each of windings faults results in a sharp increase or decrease of internal parameters’ values of the machine, therefore it can be treated as a suitable fault symptom. Resistances of the stator and rotor windings seem to be adequate quantities due to their direct relationship with the machine windings. An observation and analysis of the parameters’ changes in a real- time domain enables to an incipient detection of the fault. It is evident that internal parameters of the machine can’t be measured directly during operation on the drive system thus the only way is an estimation by specialized algorithms. In the paper two estimators based on active (P) and reactive (Q) power based Model Reference Adaptive System (PQ-MRAS) estimators were utilized to achieve this goal. The estimator employs the active (P) and reactive (Q) power of the machine which is calculated by the only measurable signals, such as stator voltage and current. Two simple algorithms for faults detection are proposed as well. Detailed description of fault detection systems is included in the paper. Proposed systems were tested on computer simulations performed by MATLAB/Simulink software.


Keywords


induction motor, stator fault, rotor fault, faults detection, parameter estimator, MRAS, active power, reactive power.

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References


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