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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dc.contributor.author Patra, Jagdish Chandra.
dc.contributor.author Ang, Ee Luang.
dc.contributor.author Chaudhari, Narendra Shivaji.
dc.contributor.author Das, Amitabha.
dc.date.accessioned 2011-09-29T03:10:05Z
dc.date.available 2011-09-29T03:10:05Z
dc.date.copyright 2005
dc.date.issued 2011-09-29
dc.identifier.citation 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.
dc.identifier.issn 1110-8657
dc.identifier.uri http://hdl.handle.net/10220/7115
dc.description.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.
dc.format.extent 28 p.
dc.language.iso en
dc.relation.ispartofseries EURASIP journal on applied signal processing
dc.rights © 2005 Jagdish C. Patra et al.
dc.subject DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation.
dc.title Neural-network-based smart sensor framework operating in a harsh environment.
dc.type Journal Article
dc.contributor.school School of Computer Engineering
dc.identifier.doi http://dx.doi.org/10.1155/ASP.2005.558
dc.description.version Published version
dc.identifier.rims 128721

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