DocumentCode :
1374517
Title :
An intelligent pressure sensor using neural networks
Author :
Patra, Jagdish Chandra ; Kot, Alex C. ; Panda, Ganapati
Volume :
49
Issue :
4
fYear :
2000
fDate :
8/1/2000 12:00:00 AM
Firstpage :
829
Lastpage :
834
Abstract :
In this paper, we propose a scheme of an intelligent capacitive pressure sensor (CPS) using an artificial neural network (ANN). A switched-capacitor circuit (SCC) converts the change in capacitance of the pressure-sensor into an equivalent voltage. The effect of change in environmental conditions on the CPS and subsequently upon the output of the SCC is nonlinear in nature. Especially, change in ambient temperature causes response characteristics of the CPS to become highly nonlinear, and complex signal processing may be required to obtain correct readout. The proposed ANN-based scheme incorporates intelligence into the sensor. It is revealed from the simulation studies that this CPS model can provide correct pressure readout within ±1% error (full scale) over a range of temperature variations from -20°C to 70°C. Two ANN schemes, direct modeling and inverse modeling of a CPS, are reported. The former modeling technique enables an estimate of the nonlinear sensor characteristics, whereas the latter technique estimates the applied pressure which is used for direct digital readout. When there is a change in ambient temperature, the ANN automatically compensates for this change based on the distributive information stored in its weights
Keywords :
capacitive sensors; computerised instrumentation; digital readout; fault diagnosis; intelligent sensors; multilayer perceptrons; nonlinear systems; pressure sensors; signal processing; -20 to 70 C; artificial neural network; capacitive pressure sensor; compensation; direct modeling; distributive information; equivalent voltage; intelligent pressure sensor; inverse modeling; multilayer perceptrons; nonlinear sensor characteristics; pressure-sensor; response characteristics; signal processing; switched-capacitor circuit; Artificial intelligence; Artificial neural networks; Capacitive sensors; Intelligent networks; Intelligent sensors; Inverse problems; Neural networks; Sensor phenomena and characterization; Switched capacitor circuits; Temperature sensors;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/19.863933
Filename :
863933
Link To Document :
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