• DocumentCode
    3600135
  • Title

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

  • Author

    Gaura, Elena ; Kraft, Michael

  • Author_Institution
    Sch. of Math. & Inf. Sci., Coventry Univ., UK
  • Volume
    3
  • fYear
    2002
  • Firstpage
    2052
  • 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.
  • Keywords
    closed loop systems; fault diagnosis; intelligent sensors; microsensors; neural nets; capacitive sensors; closed loop control; extrapolation; fault diagnosis; micromachined acceleration sensors; micromachined sensors; neural networks; neural transducers; tunnelling accelerometer; tunnelling current sensors; Acceleration; Accelerometers; Artificial neural networks; Capacitive sensors; Computerized monitoring; Electrodes; Fault diagnosis; Neural networks; Sensor phenomena and characterization; Sensor systems and applications;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE 2002. Proceedings of the 41st SICE Annual Conference
  • Print_ISBN
    0-7803-7631-5
  • Type

    conf

  • DOI
    10.1109/SICE.2002.1196649
  • Filename
    1196649