Vision-Based Weld Parameter Setting for Intricate Workpieces
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual adjustment of welding power sources for intricate welds is time-consuming and prone to variations, reducing efficiency and accuracy in welding processes, particularly in applications like aerospace part welding.
Innovation Solution
A welding system that includes a visual acquisition system to capture digital images of the weld part and a part recognition system to compare these images with stored data, automatically determining and setting appropriate welding parameters for the welding power supply.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual adjustment of welding power sources is used, then the welding process can be performed with simple equipment, but the setup time increases and accuracy decreases
Solution Approach 1:
The welding system automatically identifies workpiece features and selects appropriate welding parameters without requiring manual operator input. The system serves itself by using onboard imaging devices and processing circuitry to autonomously configure welding settings, eliminating the time-consuming manual setup process while ensuring accurate parameter selection for each specific workpiece.
Solution Approach 2:
The patent replaces the manual mechanical adjustment process with an automated optical and electronic system. Imaging devices capture workpiece features, processing circuitry analyzes the visual data, and control systems automatically adjust welding parameters, substituting the manual mechanical tuning process with an automated vision-based system that improves both speed and accuracy.
2Productivity
If automated welding systems are implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The welding system integrates multiple functions into a single automated platform that can handle various workpiece types and welding processes. The imaging devices, processing circuitry, and parameter selection algorithms work together to provide universal automation capability across different welding applications, increasing productivity without requiring separate specialized systems for each welding type.
Solution Approach 2:
The patent introduces an intelligent intermediary layer consisting of imaging devices and processing circuitry that bridges the workpiece and the welding power source. This intermediary automatically captures workpiece features, processes the visual information, and translates it into appropriate welding parameters, simplifying the overall system architecture while enabling automated control.
3Reliability
If manual parameter setting is used, then the system remains simple to operate, but reliability decreases due to operator variations
Solution Approach 1:
The welding system incorporates a feedback mechanism where imaging devices continuously monitor workpiece features and the processing circuitry uses this information to automatically adjust and select welding parameters. This closed-loop feedback system ensures consistent parameter selection based on actual workpiece characteristics, eliminating operator variation and improving reliability without requiring high operator skill levels.
Solution Approach 2:
The system performs self-configuration by automatically identifying workpiece features and selecting appropriate welding parameters without human intervention. This self-service capability ensures that the same workpiece features always result in the same parameter selections, providing consistent and reliable operation regardless of operator skill or fatigue.
Data Source
AI summary
An example welding system includes: a visual acquisition system comprising an imaging device and configured to acquire a visual representation of a weld part and to convert the visual representation into data representative of weld part features; and a part recognition component comprising processing circuitry configured to: receive the digital data; identify one or more features of the weld part in response to receipt of the digital signal; compare the digital signal to stored data of a plurality of weld parts stored in a weld part database to match one or more identified features to a known weld part of the plurality of weld parts stored in the weld part database; identify weld settings stored in a weld parameter database associated with the matching known weld part of the plurality of weld parts stored in the weld part database; and send the weld settings to a welding power supply.