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

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...

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Main Authors: Patra, Jagdish Chandra, Ang, Ee Luang, Chaudhari, Narendra Shivaji, Das, Amitabha
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2011
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Online Access:https://hdl.handle.net/10356/94140
http://hdl.handle.net/10220/7115
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-941402020-05-28T07:18:17Z Neural-network-based smart sensor framework operating in a harsh environment Patra, Jagdish Chandra Ang, Ee Luang Chaudhari, Narendra Shivaji Das, Amitabha School of Computer Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation 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. Published version 2011-09-29T03:10:05Z 2019-12-06T18:51:24Z 2011-09-29T03:10:05Z 2019-12-06T18:51:24Z 2005 2005 Journal Article Patra, J. C., Ang, E. L., Chaudhari, N. S., & Das, A. (2005). Neural-Network-Based Smart Sensor Framework Operating in a Harsh Environment. EURASIP Journal on Applied Signal Processing, 2005(4), 558-574. 1110-8657 https://hdl.handle.net/10356/94140 http://hdl.handle.net/10220/7115 10.1155/ASP.2005.558 128721 en EURASIP journal on applied signal processing © 2005 Jagdish C. Patra et al. 28 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
Patra, Jagdish Chandra
Ang, Ee Luang
Chaudhari, Narendra Shivaji
Das, Amitabha
Neural-network-based smart sensor framework operating in a harsh environment
description 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.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Patra, Jagdish Chandra
Ang, Ee Luang
Chaudhari, Narendra Shivaji
Das, Amitabha
format Article
author Patra, Jagdish Chandra
Ang, Ee Luang
Chaudhari, Narendra Shivaji
Das, Amitabha
author_sort Patra, Jagdish Chandra
title Neural-network-based smart sensor framework operating in a harsh environment
title_short Neural-network-based smart sensor framework operating in a harsh environment
title_full Neural-network-based smart sensor framework operating in a harsh environment
title_fullStr Neural-network-based smart sensor framework operating in a harsh environment
title_full_unstemmed Neural-network-based smart sensor framework operating in a harsh environment
title_sort neural-network-based smart sensor framework operating in a harsh environment
publishDate 2011
url https://hdl.handle.net/10356/94140
http://hdl.handle.net/10220/7115
_version_ 1681058185233825792