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Analysis of higher-order bézier curves for approximation of the static magnetic properties of NO electrical steels
Ermin Rahmanović, Martin Petrun, 2024, original scientific article

Abstract: Adequate mathematical description of magnetization curves is indispensable in engineering. The accuracy of the description has a significant impact on the design of electric machines and devices. The aim of this paper was to analyze the capability of Bézier curves systematically, to describe the nonlinear static magnetic properties of non-oriented electrical steels, and to compare this approach versus the established mathematical descriptions. First, analytic functions versus measurements were analyzed. The Bézier curves were then compared systematically with the most adequate analytic functions. Next, the most suitable orders of Bézier curves were determined for the approximation of nonlinear magnetic properties, where the influence of the range of the input measurement dataset on the approximation process was analyzed. Last, the extrapolation capabilities of the Bézier curves and analytic functions were evaluated. The general conclusion is that Bézier curves have adequate flexibility and significant potential for the approximation and extrapolation of nonlinear properties of non-oriented electrical steels.
Keywords: analytical modeling, anhysteretic curve, applied mathematics, Bézier curve, curve fitting, first magnetization curve, major loop, mathematical modeling, non-oriented electrical steel
Published in DKUM: 01.02.2024; Views: 303; Downloads: 15
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Automated landmark points detection by using a mixture of approaches : the vole-teeth case
Božidar Potočnik, 2015, original scientific article

Abstract: This paper deals with the automated detection of a closed curvećs dominant points. We treat a curve as a 1-D function of the arc length. The problem of detecting dominant points is translated into seeking the extrema of the corresponding 1-D function. Three approaches for automated dominant points detection are presented: (1) an approach based on fitting polynomial, (2) an approach using 1-D computer registration and (3) an innovative approach based on a multi-resolution scheme, zero-crossing and hierarchical clustering. Afterwards, two methods are introduced based on the linearly and non-linearly mixing the results from the three approaches. We then mix the results in a mean-square error sense by using the linear and non-linear fittings, respectively. We experimentally demonstrate the problem of detecting 21 landmarks on 38 vole-teeth that by mixing, the detection accuracy is improved by up to 41.47 % with respect to the results for individual approaches, as applied within the mixture.
Keywords: closed curve, dominant point, landmark, automated detection, mixing model fitting, vole-tooth
Published in DKUM: 10.07.2015; Views: 1436; Downloads: 26
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