Fast circular shapes detection in cylindrical ECT sensors by design selection and nonlinear black-box modeling

• Published in: Compel Vol. 36; no. 1; pp. 2 - 17
• Main Authors: Oussar, Yacine, Margo, Cedric, Lucas, Jérôme, Holé, Stéphane
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 01.01.2017; Emerald Group Publishing Limited; Emerald
• Subjects: Circularity; Design; Electrodes; Image reconstruction; Linear equations; Mathematical analysis; Physics; Position sensing; Sensors; Shape recognition; Support vector machines; Tomography; Non-linear modeling; Electrical capacitive tomography; Machine learning techniques
• ISSN: 0332-1649; 2054-5606
• DOI: 10.1108/COMPEL-09-2015-0352

Purpose Within the framework of image reconstruction in cylindrical electrical capacitance tomography (ECT) sensors, the purpose of this study is to select the structure of a sensor in terms of number and size of the electrodes, to predict the radius and the position of a single circular shape lying in the cross-section defined by the sensor electrodes. Design/methodology/approach Nonlinear black-box models using a set of physically independent capacitances and least-square support vector machines models selected with a sophisticated validation method are implemented. Findings The coordinates of circular shapes are well estimated in fixed and variable permittivity environments even with noisy data. Various numerical experiments are presented and discussed. Sensors formed by three or four electrodes covering 50 per cent of the sensor perimeter provide the best prediction performances. Research limitations/implications The proposed method is limited to the detection of a single circular shape in a cylindrical ECT sensor. Practical implications This method can be advantageously implemented in real-time applications, as it is numerically cost-effective and necessitates a small amount of measurements. Originality/value The contribution is two-fold: a fast computation of a circular shape position and radius with a satisfactory precision compared to the sensor size, and the determination of a cylindrical ECT sensor architecture that allows the most efficient predictions.