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
Link To Document :
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