“Multiphase flow metering using capacitance transducer and multivariate calibration”
Authors: Øyvind Midttveit, Viktor Berge and Eivind Dykesteen,Affiliation: Christian Michelsen Research and NTNU, Department of Engineering Cybernetics
Reference: 1992, Vol 13, No 2, pp. 65-76.
Keywords: Process measurements, signal processing, feature extraction, chemometrics, multi-level modeling
Abstract: The method of multivariate calibration is experimentally investigated to establish estimators of the required pertinent flow parameters in multiphase pipe flow. The unfiltered primary signals, provided by a capacitance sensor, are analysed as discrete time series and the signal characteristics are extracted. The multivariate model that is generated estimates the flow composition based on the extracted information existing in the broad-band capacitance signal. The data analysis and test results are presented.
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DOI: 10.4173/mic.1992.2.1DOI forward links to this article:
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[1] ANDERSON, T.W. (1958). An Introduction to Multivariate Statistical Analysis, Wiley, pp. 272-287.
[2] BERNTSEN, H. (1989). Multivariate calibration as an identification method and its relationship to the extended Kalman filter, Proceedings of the 28th Conference on Decision and Control, Tampa, Florida. December 1989. Vol. 1.IEEE, New York, pp. 640-645.
[3] CAMO A/S (1989). UNSCRAMBLER User´s guide, Trondheim, Norway.
[4] DYKESTEEN, E. FRANTZEN, K.H. (1990). The CMI multiphase fraction meter, IBC Technical Services Ltd. The International Conference on Basic Principles and Industrial Applications of Multiphase Flow, London, 24-25 April 1990.
[5] GELADI, P. (1988). Notes on the history and nature of partial least squares, PLS modelling. Journal of Chemometrics, 2, 231-246 doi:10.1002/cem.1180020403
[6] GELADI, P. KOWALSKI, B.R. (1986). Partial least squares regression: a tutorial, Analytica Chimica Acta, 185, 1-17 doi:10.1016/0003-2670(86)80028-9
[7] GELADI, P. KOWALSKI, B.R. (1986). An example of 2-block predictive partial least squares regression with simulated data, Analytica Chimica Acta, 185, 19-32 doi:10.1016/0003-2670(86)80029-0
[8] HAMMER, E.A. (1983). Three-component flow measurement in oil/gas/water mixtures using capacitance transducers, Ph.D. Thesis.
[9] HELLAND, K., BERNTSEN, H.E., BORGEN, O.S. MARTENS, H. (1992). Recursive algorithm for partial least squares regression, Chemometrics and Intelligent Laboratory Systems, 14, 129-137 (Elsevier Science Publishers B.V., Amsterdam) doi:10.1016/0169-7439(92)80098-O
[10] MARTENS, H. NÆS, T. (1989). Multivariate Calibration, Wiley.
[11] QIN, S., McAVOY, T. J. (1991). Annual meeting of the American Institute of Chemical Engineers, Los Angeles, California, 17-22 November 1991. Paper 149d..AIChE, New York.
[12] TAITEL, Y., BORNEA, D. DUKLER, A.E. (1980). Modelling flow pattern transitions for steady upward gas-liquid flow in vertical tubes, AIChE Journal, 26, 345-354 doi:10.1002/aic.690260304
[13] VAN BEEK, L. (1967). Dielectric behaviour of heterogeneous systems, Progress in Dielectrics, 7, 71-113.
[14] WIDROW, B. LEHR, M.A. (1990). 30 Years of adaptive neural networks: Perceptron, Madaline, and backpropagation, Proceedings of the IEEE, 78, 1415-1442 doi:10.1109/5.58323
BibTeX:
@article{MIC-1992-2-1,
title={{Multiphase flow metering using capacitance transducer and multivariate calibration}},
author={Midttveit, Øyvind and Berge, Viktor and Dykesteen, Eivind},
journal={Modeling, Identification and Control},
volume={13},
number={2},
pages={65--76},
year={1992},
doi={10.4173/mic.1992.2.1},
publisher={Norwegian Society of Automatic Control}
};