Hybrid evolutionary algorithm for microscrew thread parameter estimation

Authors:
Oleksandr Makeyev;Edward Sazonov;Mikhail Moklyachuk;Paulo Lopez-Meyer
Affiliations:
Department of Electrical and Computer Engineering, Clarkson University, 8 Clarkson Ave, Potsdam, NY 13699, USA;Department of Electrical and Computer Engineering, Clarkson University, 8 Clarkson Ave, Potsdam, NY 13699, USA;Department of Probability Theory, Statistics and Actuarial Mathematics, Taras Shevchenko National University of Kyiv, 64 Volodymyrska Street, Kyiv 01601, Ukraine;Department of Electrical and Computer Engineering, Clarkson University, 8 Clarkson Ave, Potsdam, NY 13699, USA
Venue:
Engineering Applications of Artificial Intelligence
Year:
2010

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Engineering Applications of Artificial Intelligence

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Abstract

In this paper we propose a novel approach to the problem of microscrew thread parameter estimation based on a hybrid evolutionary algorithm that combines a stochastic evolutionary algorithm with the deterministic inverse parabolic interpolation. The proposed method uses a machine vision system utilizing a single web camera. The hybrid evolutionary algorithm was tested on a specially created image database of microscrews. Experimental results prove speed and efficiency of the proposed method and its robustness to noise in the images. This method may be used in automated systems of real-time non-destructive quality control of microscrews and has potential for parameter estimation of different types of microparts.