Paper
25 April 2007 Neural network analysis of pulp flow speed in low coherence Doppler flowmetry measurement
Manne Hannula, Erkki Alarousu, Tuukka Prykäri, Risto Myllylä
Author Affiliations +
Proceedings Volume 6606, Advanced Laser Technologies 2006; 66061L (2007) https://doi.org/10.1117/12.730208
Event: Advanced Laser Technologies 2006, 2006, Brasov, Romania
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manne Hannula, Erkki Alarousu, Tuukka Prykäri, and Risto Myllylä "Neural network analysis of pulp flow speed in low coherence Doppler flowmetry measurement", Proc. SPIE 6606, Advanced Laser Technologies 2006, 66061L (25 April 2007); https://doi.org/10.1117/12.730208
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KEYWORDS
Doppler effect

Error analysis

Neural networks

Capillaries

Artificial neural networks

Free space optics

Analytical research

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