Weld Bead Defect Segmentation Using Shift-Region Volume Analysis
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Solution Overview
Problem
Existing weld bead inspection methods inaccurately determine the need for repair welding, leading to unnecessary repairs due to fluctuations in weld bead shape caused by environmental changes or surface dirt, despite maintaining welding quality standards.
Innovation Solution
A method and device that divide shape mismatch data into equally spaced windows, calculate volumes of shift regions, and identify segments with predetermined volumes as defective, accurately detecting repair welding segments by comparing with master data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional weld bead inspection methods are used to detect shape mismatches, then any deviation from standard shape is identified as defective, but this leads to unnecessary repair welding due to environmental changes or surface dirt that do not affect welding quality
Solution Approach 1:
The patent divides the shape mismatch data into N equally divided windows along the welding direction, then further divides each window into multiple segments. This segmentation allows localized analysis of shape deviations, distinguishing between minor fluctuations (environmental changes, surface dirt) and significant defects that actually require repair welding.
Solution Approach 2:
The patent applies different evaluation criteria to different segments of the weld bead. By calculating segment ratios (defective segment length divided by total window length) and comparing against threshold values, the system determines repair necessity based on local defect characteristics rather than applying a uniform standard across the entire weld bead.
2Manufacturing precision
If strict shape inspection is applied to all weld beads, then welding quality standards are maintained, but unnecessary repair welding increases due to normal shape fluctuations
Solution Approach 1:
The patent introduces multiple parameter thresholds (first threshold value for segment ratio, second threshold value for volume ratio) that dynamically adjust the inspection criteria. By comparing calculated ratios against these thresholds, the system maintains quality standards while allowing normal shape fluctuations that do not compromise welding performance.
3Measurement precision
If detailed segment analysis is performed on shape mismatch data, then accurate defective segment identification is achieved, but calculation complexity and processing time increase
Solution Approach 1:
The patent segments the weld bead into N windows along the welding direction, with each window further divided into multiple segments. This hierarchical segmentation structure enables systematic calculation of segment ratios and volume ratios, achieving precise defective segment identification through organized, stepwise processing rather than overwhelming complex analysis.
Data Source
AI summary
A repair welding segment detection method includes generating, based on a result of the inspection determination, shape mismatch data obtained by extracting a shape mismatch portion of the weld bead, dividing the shape mismatch data into N, where N is an integer of 2 or more, equally divided windows in a direction perpendicular to a welding direction of the weld bead, setting a shift region formed by i, where i: an integer of 1 or more, continuous windows among the N windows, separately calculating volumes of (N−i+1) shift regions obtained by shifting one by one the i windows forming the shift region in the welding direction, and determining that a shift region having a volume of a predetermined value or more among the calculated volumes of the (N−i+1) respective shift regions is a defective segment of the weld bead.