Procedure of fault detection for driving systems using self-organizing neural networks

Gheorghe Puscasu, Vasile Palade, Alexandru Stancu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

In the paper it is proposed a neural network based procedure for the recognition of faults to a DC driving system. The analysis procedure of the faults can be used to warn the human user when a new class of faults is detected.

Original languageEnglish
Title of host publicationProceedings of the Mediterranean Electrotechnical Conference - MELECON
PublisherIEEE
Pages446-448
Number of pages3
Volume2
ISBN (Print)0-7803-6290-X
DOIs
Publication statusPublished - 2000
Externally publishedYes
Event10th Mediterranean Electrotechnical Conference - Lemesos, Cyprus
Duration: 29 May 200031 May 2000

Conference

Conference10th Mediterranean Electrotechnical Conference
Abbreviated titleMALECON2000
CountryCyprus
CityLemesos
Period29/05/0031/05/00

Keywords

  • Fault detection
  • Neural networks
  • DC motors
  • Data mining
  • Transfer functions
  • Pattern recognition
  • Fault diagnosis
  • Induction motors
  • Equations
  • Optimization methods
  • electric machine analysis computing
  • DC motor drives
  • fault diagnosis
  • machine theory
  • self-organising feature maps
  • learning (artificial intelligence)
  • fault class
  • DC motor drive system
  • fault detection
  • self-organizing neural networks
  • analysis procedure
  • fault recognition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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  • Cite this

    Puscasu, G., Palade, V., & Stancu, A. (2000). Procedure of fault detection for driving systems using self-organizing neural networks. In Proceedings of the Mediterranean Electrotechnical Conference - MELECON (Vol. 2, pp. 446-448). IEEE. https://doi.org/10.1109/MELCON.2000.879966