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 language | English |
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Title of host publication | Proceedings of the 41st SICE Annual Conference, Vols 1-5 |
Place of Publication | Piscataway, NJ |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 2052-2057 |
Number of pages | 6 |
ISBN (Print) | 0780376315 |
DOIs | |
Publication status | Published - 2002 |
Externally published | Yes |
Event | 41st Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE 2002) - OSAKA, Japan Duration: 5 Aug 2002 → 7 Aug 2002 |
Conference
Conference | 41st Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE 2002) |
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Country | Japan |
City | OSAKA |
Period | 5/08/02 → 7/08/02 |
Keywords
- micromachined sensors
- closed loop control
- fault diagnosis
- artificial neural networks
- ACCELEROMETER