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Neural-network-based smart sensor framework operating in a harsh environment.

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Neural-network-based smart sensor framework operating in a harsh environment.

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Title: Neural-network-based smart sensor framework operating in a harsh environment.
Author: Patra, Jagdish Chandra.; Ang, Ee Luang.; Chaudhari, Narendra Shivaji.; Das, Amitabha.
Copyright year: 2005
Abstract: We present an artificial neural-network- (NN-) based smart interface framework for sensors operating in harsh environments. The NN-based sensor can automatically compensate for the nonlinear response characteristics and its nonlinear dependency on the environmental parameters, with high accuracy. To show the potential of the proposed NN-based framework, we provide results of a smart capacitive pressure sensor (CPS) operating in a wide temperature range of 0 to 250° C. Through simulated experiments, we have shown that the NN-based CPS model is capable of providing pressure readout with a maximum full-scale (FS) error of only ±1.0% over this temperature range. A novel scheme for estimating the ambient temperature from the sensor characteristics itself is proposed. For this purpose, a second NN is utilized to estimate the ambient temperature accurately from the knowledge of the offset capacitance of the CPS. A microcontroller-unit- (MCU-) based implementation scheme is also provided.
Subject: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation.
Type: Journal Article
Series/ Journal Title: EURASIP journal on applied signal processing
School: School of Computer Engineering
Rights: © 2005 Jagdish C. Patra et al.
Version: Published version

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