Welding Image Defect Detection Using Weld Pool Validation
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Solution Overview
Problem
Existing welding defect detection technologies require complex databases to relate features extracted from images to defects, making them inconvenient and prone to reliability issues due to changes in welding objects, parameters, or imaging conditions, and may generate erroneous quality data from blown-out highlights or shadows.
Innovation Solution
A processing device uses a first model to directly detect weld pools and defects from welding images, determining the appropriateness of defect detection results based on weld pool detection, thereby eliminating the need for a feature-defect relationship database and enhancing user convenience while increasing reliability by validating defect existence through cumulative pixel sums and consecutive determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a database relating features to defects is used for defect detection, then defect detection can be performed, but the system becomes complex and requires frequent updates when welding conditions change
Solution Approach 1:
The patent extracts and removes the complex feature-defect relationship database from the system. Instead of using a database that requires manual management and updates, the invention directly detects defects from welding images using image processing algorithms, eliminating the intermediary database structure that causes complexity while maintaining defect detection capability
Solution Approach 2:
The patent creates a universal defect detection system that can handle various welding conditions (different objects, parameters, and imaging conditions) without requiring database updates. The image processing approach is universally applicable across different welding scenarios, making the system adaptable without the complexity of maintaining condition-specific databases
2Ease of operation
If feature extraction from welding images is used, then defect detection is possible, but the system generates erroneous results from blown-out highlights or shadows
Solution Approach 1:
The patent applies beforehand cushioning by implementing preprocessing steps that compensate for potential image quality issues before defect detection. The system addresses the problem of blown-out highlights and shadows in advance through image processing techniques that normalize or correct these artifacts, ensuring accurate defect detection even under varying imaging conditions
Solution Approach 2:
The patent introduces an intermediary image processing layer between the welding image and defect detection. This intermediary processing stage handles the transformation and normalization of images, filtering out artifacts like blown-out highlights and shadows before the actual defect detection occurs, thereby improving measurement precision while maintaining ease of operation
Data Source
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AI summary
The present application relates to a processing device and corresponding method and storage medium with corresponding program. A processing device (10) acquires a first detection result and a second detection result by inputting a first image to a first model. The first model detects a welding element and a defect according to an input of a welding image. The first image is imaged when welding. The first detection result relates to the welding element. The second detection result relates to the defect. The processing device (10) determines an appropriateness of the second detection result by using the first detection result.