Multiple Faults Diagnosis of Induction Motor Using Artificial Neural Network

  • Rajvardhan JigyasuEmail author
  • Lini Mathew
  • Amandeep Sharma
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 955)


This paper presents multiple fault diagnosis and detection using artificial neural feed forward network. In this work analysis is done on induction motor, as these motor are widely used in industries because of their robustness, easy maintenance etc. The current and vibration responses of healthy motor, motor with bearing, rotor and stator defects are analysed. The feature extraction process is done in time domain only. From the results it is cleared that among various transfer functions in ANN the trainlm performs best and traingdm performs worst for fault detection.


Induction motor Fault detection Fault diagnosis Artificial intelligence ANN Transfer functions Time domain analysis 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Rajvardhan Jigyasu
    • 1
    Email author
  • Lini Mathew
    • 1
  • Amandeep Sharma
    • 1
  1. 1.Electrical Engineering DepartmentNational Institute of Technical Teachers Training and ResearchChandigarhIndia

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