Are neural network techniques the solution to measurement validation, monitoring and automatic diagnosis of sensor faults?

Elena Gaura, M Kraft

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

Abstract

The appropriateness and feasibility of using artificial Neural Network (ANN) techniques to facilitate improved in-service performance of micromachined acceleration measuring devices is questioned in this research and its possible extrapolation to sensor fault diagnosis is attempted. Two examples of closed loop neuro-transducers are given: a micromachined accelerometer with capacitive pick-off and a neural network controlled tunnelling accelerometer. Based on the success of the ANN control method as applied to sensors, the authors investigate the possibility of developing self-diagnosis sensors based on ANNs and a strategy of such development is proposed.

Original languageEnglish
Title of host publicationProceedings of the 41st SICE Annual Conference, Vols 1-5
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2052-2057
Number of pages6
ISBN (Print)0780376315
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event41st Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE 2002) - OSAKA, Japan
Duration: 5 Aug 20027 Aug 2002

Conference

Conference41st Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE 2002)
CountryJapan
CityOSAKA
Period5/08/027/08/02

Keywords

  • micromachined sensors
  • closed loop control
  • fault diagnosis
  • artificial neural networks
  • ACCELEROMETER

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