Smart wireless sensor networks for online faults diagnosis in induction machine

Hattab Guesmi, Samira Ben Salem, Khmais Bacha, Sherali Zeadally

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Online induction machine faults diagnosis is a concern to guarantee the overall production process efficiency. Nowadays, the industry demands the integration of smart wireless sensors networks (WSN) to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can produce sever damages. The origin of most recurrent faults in rotary machines is in the components: stator, rotor, bearing and others. This work presents a novel methodology for the online faults diagnosis in induction motors. This technique uses the smart WSN to obtain the machine condition based on the motor stator current analysis. The implementation of the proposed smart sensor methodology allows the system to perform online fault detection in a fully automated way. Simulation results presented show the efficiency of the proposed method to detect simple and multiple faults in induction machine. It provides detailed analysis to address challenges in designing and deploying WSNs in industrial environments, and its reliability.

Original languageEnglish
Pages (from-to)226-239
Number of pages14
JournalComputers and Electrical Engineering
Volume41
Issue numberC
DOIs
StatePublished - 2015

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Ltd. All rights reserved.

Keywords

  • Fault diagnosis
  • Induction motor
  • MCSA
  • Online monitoring
  • Smart sensor
  • WSN

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science
  • Electrical and Electronic Engineering

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