Machine Vision Stud Welding for Precise I-Beam Alignment
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Solution Overview
Problem
Manual stud welding in steel erection projects is slow, labor-intensive, and prone to worker injuries, increasing construction time and costs due to the need for repeated bending and manual alignment of studs and ferrules.
Innovation Solution
A robotically-controlled stud welding system equipped with machine vision that automatically identifies and welds studs at pre-marked sites on beams, using a carriage with an imager and welding assembly to move along the beam, align, and weld studs with precision, reducing manual labor and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual techniques are used for feeding and aligning studs and ferrules into collets, then the process is flexible and adaptable to different welding sites, but the welding speed is slow and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical alignment operations with an automated vision-guided robotic system. The machine vision system captures images of welding sites, identifies their locations and orientations, and automatically controls the robotic arm to position studs and ferrules with precise alignment, eliminating the need for manual bending and alignment operations.
Solution Approach 2:
The system enables the welding process to be self-sufficient by automatically detecting welding site locations through machine vision, calculating the necessary alignment parameters, and executing the positioning and welding operations without human intervention. The robotic system adapts to different welding site configurations autonomously based on real-time image analysis.
2Manufacturing precision
If workers repeatedly bend over to place studs and ferrules, then precise placement can be achieved, but worker injuries increase and construction time increases
Solution Approach 1:
The patent replaces manual stud placement operations with an automated robotic system guided by machine vision. The system captures images, identifies welding site coordinates, and automatically positions studs with precise alignment, eliminating the need for workers to repeatedly bend over and manually align components, thereby reducing both construction time and injury risk while maintaining placement precision.
Solution Approach 2:
The machine vision system performs preliminary detection and identification of welding site locations and orientations before the robotic arm executes the placement operation. This advance positioning and alignment calculation ensures precise stud placement while eliminating repeated manual adjustments during the welding process.
3Adaptability or versatility
If manual alignment of studs and ferrules is performed, then adaptability to different welding sites is maintained, but the process becomes labor-intensive and slow
Solution Approach 1:
The machine vision system continuously captures images of the beam surface, identifies welding site locations and orientations, and provides real-time feedback to the robotic control system. This feedback loop enables the robotic arm to automatically adapt its positioning and alignment for each welding site, maintaining versatility while eliminating manual intervention and significantly improving welding efficiency.
Solution Approach 2:
The patent replaces manual adaptability operations with an automated vision-guided system that detects welding site characteristics through image analysis and automatically adjusts robotic arm positioning and orientation. This substitution maintains the system's ability to handle different welding site configurations while dramatically increasing welding speed and efficiency.
Data Source
AI summary
The present disclosure teaches systems and methods for robotic welding of studs onto the surface of I-beams. The systems and methods use machine vision to identify and locate welding sites on a surface of a beam or girder, moves and aligns studs to the welding sites, and welds studs to the surface at these sites.