Pipe Welding Seam Tracking With Vision-Based Stitch Detection
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Solution Overview
Problem
Current methods for tracking welding seams in pipe welding, such as those using laser scanners, lack precision and require improved monitoring and automatic adjustment of welding parameters.
Innovation Solution
A robotic welding system with a camera attached to a torch arm continuously captures and processes frames to detect seam positions, stitch starts, and stitch ends, adjusting welding parameters accordingly to ensure precise tracking and quality control during spool welding operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser scanners are used for seam tracking, then the welding operation can be automated, but the precision of seam tracking is limited
Solution Approach 1:
The patent replaces traditional mechanical laser scanners with a vision-based system using cameras and image processing algorithms. The camera captures images of the weld seam, and software processes these images to determine seam position and guide the welding torch, substituting mechanical scanning with optical detection and computational analysis.
Solution Approach 2:
The system creates a visual copy (image) of the weld seam and processes this copy to determine seam position. Instead of directly measuring with mechanical sensors, the system captures an optical replica of the seam and uses image processing to extract positioning information from this copy.
2Device complexity
If passive vision systems are used for seam tracking, then device complexity is reduced, but measurement precision may be insufficient for thin plate closed-gap welding
Solution Approach 1:
The system performs preliminary positioning by detecting the weld seam before actual welding begins. The vision system captures images and processes them to determine the seam position in advance, allowing the welding torch to be accurately positioned before the welding operation starts, which is particularly important for thin plate closed-gap welding.
Solution Approach 2:
The system continuously monitors the weld seam position during welding and provides real-time feedback to adjust the torch position. The vision system captures images throughout the welding process, processes them to determine current seam position, and uses this information to correct any deviations from the intended weld path.
3Extent of automation
If real-time image processing is implemented for seam tracking, then welding parameter adjustment can be automated, but processing time and computational resources increase
Solution Approach 1:
The system processes only the necessary portions of the captured images to determine seam position and welding parameters. Rather than analyzing entire images or all possible features, the system focuses on extracting only the critical seam position information needed for control, reducing computational burden while maintaining automation.
Solution Approach 2:
The vision system captures and processes images at periodic intervals during welding rather than continuously. This periodic sampling provides sufficient information for parameter adjustment while reducing the total computational load and processing time required compared to continuous real-time analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enhances precision in seam tracking and welding parameter adjustment, achieving accurate and consistent welds with improved precision and efficiency in pipe welding operations.
Implementation Method 1
a camera positioned to capture images of an area around a welding arc
Data Source
Figure 1~2
Figure 2A
Figure 3
AI summary
The present disclosure provides a method for controlling a robotic welding system to weld pipe sections wherein the pipe sections are held in fixed relation to each other by a plurality of stitches at a seam between the pipe sections. The method comprises rotating the pipe sections so a camera may determine the seam position, moving a torch arm and welding torch so that the torch is over one of the plurality of stitches, adjusting welding parameters and determining stitch start when welding torch is over a stitch and further adjusting welding parameters and determining stitch end when welding torch moves past one of the plurality of stitches.