Abstract
This article presents a hybrid system for self-compensation and self-validation of intelligent industrial instruments that combines a Neuro-Fuzzy model, based on the ANFIS architecture, capable of compensating errors caused by non-calibrated instruments, and a validation model based on Fuzzy Logic that provides the level of confidence of measurements. The proposed system indicates to the specialist when a new calibration must be performed. The hybrid system is tested with a differential pressure instrument, used in mining for level and pressure controls.
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© 2011 Springer-Verlag Berlin Heidelberg
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Sanchez, J.E.R., Vellasco, M.M.B.R., Tanscheit, R. (2011). An Intelligent Model for Self-compensation and Self-validation of Sensor Measurements. In: Fanelli, A.M., Pedrycz, W., Petrosino, A. (eds) Fuzzy Logic and Applications. WILF 2011. Lecture Notes in Computer Science(), vol 6857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23713-3_34
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DOI: https://doi.org/10.1007/978-3-642-23713-3_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23712-6
Online ISBN: 978-3-642-23713-3
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