Autonomous Welding Path Planning for Interference-Free Arc Welding
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Solution Overview
Problem
Current welding processes face challenges in optimizing weld quality for arc welding, as existing methods fail to accurately determine torch motion and welding conditions necessary for a good surface property and defect-free weld bead, and struggle to correct positional discrepancies between offline teaching and actual welding, especially in continuous line welding.
Innovation Solution
A welding path autonomous optimization system that includes a database, interference analysis part, and output part, using three-dimensional CAD data and quality-welding-condition correlation database to determine a welding path that avoids interference and ensures optimal weld quality by adjusting torch movement and power source conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If offline teaching analysis is used to avoid interference between welding torch and workpiece, then interference avoidance is improved, but weld quality optimization deteriorates
Solution Approach 1:
The system segments the welding process optimization into two independent modules: interference analysis (robot motion planning) and weld quality optimization (welding condition determination). This allows each module to be optimized separately while working together to solve the overall problem.
Solution Approach 2:
The system introduces an intermediary database that stores welding condition information (torch tilt angle, welding speed, power source settings) separate from the robot motion data. This intermediary structure enables independent optimization of weld quality parameters without affecting interference avoidance calculations.
2Measurement precision
If coordinate correction is performed to correct positional relationship gap between offline teaching and actual welding, then positional accuracy is improved, but weld quality optimization deteriorates
Solution Approach 1:
The system separates positional correction (coordinate transformation) from weld quality optimization. Coordinate correction handles only the geometric alignment between offline teaching and actual welding positions, while weld quality parameters are determined independently through database lookup based on welding conditions.
Solution Approach 2:
The system creates a virtual model of the workpiece from three-dimensional CAD data and performs interference analysis in this virtual space. This copying approach allows accurate positional relationship simulation without affecting actual welding quality parameters.
3Reliability
If robot motion coordinate analysis is used for avoiding interference, then interference avoidance is improved, but weld quality optimization deteriorates
Solution Approach 1:
The system divides the control parameters into motion parameters (robot position and orientation for interference avoidance) and welding parameters (torch tilt angle, welding speed, power source settings for quality optimization). Each set is independently determined and then combined.
Solution Approach 2:
The system replaces traditional mechanical trial-and-error welding condition adjustment with an information-based database lookup system. Welding conditions are determined through information processing (querying the database based on welding type and position) rather than mechanical experimentation.
Data Source
AI summary
The welding path autonomous optimization system includes a quality—welding-condition correlation database in which a constraint condition of welding by a welding robot that operates a welding torch is stored, an interference analysis part configured to determine a welding path that does not interfere with an object to be welded based on three-dimensional CAD data of the object to be welded and the constraint condition stored in the quality—welding-condition correlation database, and a welding-robot-operation/welding-condition output part configured to output welding process information based on the welding path.