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Auto-compensation of nonlinear influence of environmental parameters on the sensor characteristics using neural networks

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Auto-compensation of nonlinear influence of environmental parameters on the sensor characteristics using neural networks

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Title: Auto-compensation of nonlinear influence of environmental parameters on the sensor characteristics using neural networks
Author: Patra, Jagdish Chandra; Ang, Ee Luang; Das, Amitabha; Chaudhari, Narendra Shivaji
Copyright year: 2005
Abstract: Usually the environmental parameters influence the sensor characteristics in a nonlinear manner. Therefore obtaining correct readout from a sensor under varying environmental conditions is a complex problem. In this paper we propose a neural network (NN)-based interface framework to automatically compensate for the nonlinear influence of the environmental temperature and the nonlinear-response characteristics of a capacitive pressure sensor (CPS) to provide correct readout. With extensive simulation studies we have shown that the NN-based inverse model of the CPS can estimate the applied pressure with a maximum error of ± 1.0% for a wide temperature variation from 0 to 250°C. A microcontroller unit-based implementation scheme is also proposed.
Subject: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
Type: Journal Article
Series/ Journal Title: ISA transactions
School: School of Computer Engineering
Rights: © 2005 ISA—The Instrumentation, Systems, and Automation Society. This is the author created version of a work that has been peer reviewed and accepted for publication by ISA transactions, ISA—The Instrumentation, Systems, and Automation Society. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI: http://dx.doi.org/10.1016/S0019-0578(07)60175-X ]
Version: Accepted version

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