Accuracy control of contactless laser sensor system using whale optimization algorithm and moth-flame optimization

Abstract

Abstract This paper predict the effect of the object's morphology on the final accuracy of the scanned data, for the case of contactless laser scanning. On the basis of the scanned objects morphology, two important process parameters are specified namely scanning angle and distance of the laser from the part surface. Experiments have been performed with different scanning conditions using full factorial design. An analytical prediction model for determining the standard deviation of the final surface is developed in terms of the aforesaid scanning parameters using response surface methodology (RSM). Furthermore, the optimal scanning parameters are predicted after comparing two almost unexplored nature inspired algorithms i.e. Whale Optimization Algorithm (WOA) and Moth-Flame Optimization (MFO). Finally, two realistic non-trivial case studies are considered for validation of the proposed methodology. The result shows that the standard deviation of the final reverse engineered models significantly reduced by 21.6% and 13.77%. The adopted methodology provides the optimal combination of morphological scanning process parameters with a considerable reduction in standard deviation for final scanned surface models.