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Crack Contour Modeling Based on a Metaheuristic Algorithm and Micro-Laser Line Projection.

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  • 1Centro de Investigaciones en Óptica, A. C., Lomas del Bosque 115, Col. Comas del Campestre, León 37000, GTO, Mexico.

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Summary

A novel bio-inspired genetic algorithm models surface crack contours using Bezier functions and laser scanning data. This approach offers a highly accurate, non-destructive method for assessing surface quality in manufacturing.

Keywords:
Bezier basis functioncrack contour modelmetaheuristic genetic algorithmmicro-laser line scanning

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Area of Science:

  • Materials Science
  • Computer Vision
  • Biomimetics

Background:

  • Manufacturing industries require non-destructive techniques for surface crack characterization to ensure product quality.
  • Bio-inspired metaheuristic algorithms are crucial for computer vision tasks, including surface crack assessment.
  • Accurate modeling of micro-crack contours is essential for determining surface quality.

Purpose of the Study:

  • To develop and implement a bio-inspired algorithm for constructing precise crack contour models.
  • To utilize Bezier functions and crack coordinates for accurate crack region determination.
  • To enhance traditional crack contour inspection methods using microscope image processing.

Main Methods:

  • Implementation of a metaheuristic genetic algorithm to build crack contour models.
  • Integration of a microscope vision system with micro-laser line scanning to obtain crack coordinates.
  • Fitting Bezier functions to crack topography using an objective function with control points.

Main Results:

  • The proposed technique successfully models micro-scale crack contours.
  • Achieved a relative error of less than 2% in contour modeling.
  • Demonstrated superior performance compared to conventional image processing algorithms.

Conclusions:

  • The developed bio-inspired algorithm provides an accurate and efficient method for crack contour modeling.
  • This technique enhances surface quality inspection in manufacturing through non-destructive characterization.
  • The study validates the effectiveness of metaheuristic algorithms in biomimetic applications for computer vision.