A robotic welding system using image processing techniques and a CAD model to provide information to a multi‐intelligent decision module

Abstract

Purpose -The paper aims to propose a system that uses a combination of techniques to suggest weld requirements for ships parts. These suggestions are evaluated, decisions are made and then weld parameters are sent to a program generator. Design/methodology/approach -A pattern recognition system recognizes shipbuilding parts using shape contour information. Fourier-descriptors provide information and neural networks make decisions about shapes. Findings -The system has distinguished between various parts and programs have been generated so that the methods have proved to be valid approaches. Practical implications -The new system used a rudimentary curvature metric that measured Euclidean distance between two points in a window but the improved accuracy and ease of implementation can benefit other applications concerning curve approximation, node tracing, and image processing, but especially in identifying images of manufactured parts with distinct corners. Originality/value -A new proposed system has been presented that uses image processing techniques in combination with a computer-aided design model to provide information to a multi-intelligent decision module. This module will use different criteria to determine a best weld path. Once the weld path has been determined then the program generator and post-processor can be used to send a compatible program to the robot controller. The progress so far is described.

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