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Proceedings Paper

Neural network analysis of pulp flow speed in low coherence Doppler flowmetry measurement
Author(s): Manne Hannula; Erkki Alarousu; Tuukka Prykäri; Risto Myllylä
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Paper Abstract

Low Coherence Doppler Flowmetry (LCDF) measurement produces a signal, which frequency domain characteristics are in connection to the speed of the flow. In this study a LCDF measurement data of pulp flow in a capillary was analyzed with a simple Artificial Neural Network (ANN) method to estimate the flow speed. The accuracy of the method proved to be good, validation of the method resulted in absolute error of 14 ± 11 percentage units (mean±std) in flow speed estimation. The results of the study can be utilized in development of industrial pulp flow speed measurement instruments.

Paper Details

Date Published: 25 April 2007
PDF: 4 pages
Proc. SPIE 6606, Advanced Laser Technologies 2006, 66061L (25 April 2007); doi: 10.1117/12.730208
Show Author Affiliations
Manne Hannula, Univ. of Oulu (Finland)
Erkki Alarousu, Univ. of Oulu (Finland)
Tuukka Prykäri, Univ. of Oulu (Finland)
Risto Myllylä, Univ. of Oulu (Finland)


Published in SPIE Proceedings Vol. 6606:
Advanced Laser Technologies 2006
Dan C. Dumitras; Maria Dinescu; Vitally I. Konov, Editor(s)

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