Predictive Maintenance Applied to Three phase Induction Motors

Authors

  • Fatma Zohra DEKHANDJI Smart Grid Team, Laboratory of Signals and Systems, Institute of Electrical and Electronic Engineering, University M’hamed Bougara of Boumerdes, Avenue de l’indépendance, 35000, Algeria
  • Salah Eddine HALLEDJ Smart Grid Team, Laboratory of Signals and Systems, Institute of Electrical and Electronic Engineering, University M’hamed Bougara of Boumerdes, Avenue de l’indépendance, 35000, Algeria
  • Oussama ZABOUB Smart Grid Team, Laboratory of Signals and Systems, Institute of Electrical and Electronic Engineering, University M’hamed Bougara of Boumerdes, Avenue de l’indépendance, 35000, Algeria

DOI:

https://doi.org/10.51485/ajss.v4i2.84

Keywords:

Induction machines, Preventive maintenance, Reliability, faults

Abstract

Induction machines are widely used in industry. The operating conditions may sometimes lead the machine into different fault situations. The machine should be shut down when a fault is experienced to avoid complete process failure and for the safety of the workers. The predictive maintenance consists of scheduling maintenance activities only when a functional failure is detected. The advantages of predictive maintenance are accepted in many industries because of its efficiency in fault detection during early stages and thus reducing unscheduled down time. It increases productivity, improves quality and provides the feeling of safety and reliability to staff. The main types of external faults experienced by these motors are over loading; single phasing, unbalanced supply voltage, phase reversal, ground fault, under voltage and over voltage. MATLAB/SIMULINK simulation is used in this work for the detection and analysis of the faults on induction motor.

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Published

2019-12-15

How to Cite

[1]
DEKHANDJI, F.Z., HALLEDJ, S.E. and ZABOUB, O. 2019. Predictive Maintenance Applied to Three phase Induction Motors. Algerian Journal of Signals and Systems . 4, 2 (Dec. 2019), 71-88. DOI:https://doi.org/10.51485/ajss.v4i2.84.

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Articles