Radiographic Weld Defect Detection With Image Quality Gating
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Solution Overview
Problem
Existing radiographic testing methods for weld defects rely heavily on human inspectors, which are subjective and time-consuming, lacking objective and efficient automated defect detection.
Innovation Solution
A device and method utilizing machine learning models for radiographic testing, including reading region, image quality indicator detection, and defect detection, to automate the process of identifying weld defects through image processing and outputting detailed reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human inspectors perform radiographic testing manually, then subjective judgment and time-consuming inspection occur, but automation and efficiency are reduced
Solution Approach 1:
The patent replaces the mechanical human inspection process with an automated image processing system that uses algorithms to detect weld defects. The system processes radiographic images through multiple stages including reading region processing, image quality assessment, and defect detection, eliminating manual inspection while maintaining high accuracy in identifying weld defects.
2Productivity
If automated defect detection is implemented, then inspection time is reduced and efficiency is improved, but measurement precision and detection accuracy may be compromised
Solution Approach 1:
The patent divides the defect detection process into multiple specialized modules: reading region processing unit for identifying areas of interest, image quality processing unit for assessing image quality through wire counting, and defect processing unit for detecting actual defects. This segmentation allows each module to optimize for its specific function, maintaining high detection accuracy while achieving automation.
Solution Approach 2:
The system incorporates image quality assessment through wire counting that provides feedback on image quality indicators. This feedback mechanism ensures that only images meeting quality standards proceed to defect detection, maintaining measurement precision while enabling automated high-speed inspection.
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
The method significantly reduces inspection time and provides objective, accurate results by automating the detection of weld defects, enhancing efficiency and reliability.
Implementation Method 1
Radiographic testing (RT) is a testing method that selects radiation such as X-rays or gamma rays in accordance with usage conditions and purpose, passes the radiation through a test specimen, and forms an image
Data Source
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AI summary
Proposed are a device for inspecting a defect in a weld based on radiographic testing and a method therefor, and the method includes a step of evaluating a quality of the radiographic image according to the number of counted wires of the image quality indicator, a step of performing image processing so as to highlight features of the defect in the welded part in the reading region when the quality of the radiographic image satisfies a preset reference value, a step of detecting the defect in the welded part in the reading region, and a step of outputting a defect report that includes a defect location, a defect area, and a defect type according to the detected defect.