Radiographic Inspection Image Grain Diffraction Noise Reduction
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Solution Overview
Problem
Industrial radiography systems face challenges in non-destructive testing due to grain diffraction patterns that obscure defects and increase inspection time, leading to false positives or negatives, as these patterns vary with changes in object-detector and object-source distances.
Innovation Solution
A method and system that scale features of digital images to a common scale and remove grain diffraction pattern differences between images, forming an inspection image with reduced noise by retaining only common image features, facilitating defect detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If grain diffraction patterns are present in radiographic images, then imaging information is obtained, but defect detection accuracy deteriorates due to obscured defects and false positives/negatives
Solution Approach 1:
The patent applies the principle of converting harm into benefit by using the grain diffraction pattern variations across multiple images as a mechanism to identify and remove noise. Instead of treating the grain diffraction patterns as mere interference, the system leverages their consistent presence across multiple images at different distances to distinguish them from actual defects, thereby converting the harmful interference into a useful identifier for noise removal and improving defect detection accuracy.
Solution Approach 2:
The patent extracts the grain diffraction pattern information from the radiographic images by analyzing patterns across multiple images taken at different object-detector and object-source distances. The system separates the grain diffraction patterns from the actual defect information, allowing the grain patterns to be removed or suppressed while preserving the defect detection capability, thus extracting the harmful element from the useful information.
2Loss of information
If multiple digital images are acquired at different scales, then comprehensive inspection data is obtained, but image processing complexity increases due to scaling and grain difference removal requirements
Solution Approach 1:
The patent segments the image processing task into distinct steps: acquiring multiple digital images at different scales, scaling the images to a common scale, identifying grain diffraction patterns, and removing the grain differences. This segmentation allows each step to be optimized independently, managing the overall processing complexity while maintaining comprehensive inspection data from multiple images.
Solution Approach 2:
The patent utilizes parameter changes by acquiring images at different object-detector and object-source distances, which changes the scale and grain diffraction pattern parameters. The system then standardizes these parameters through scaling to a common scale, enabling consistent comparison and processing across all images while preserving the comprehensive information gained from varying acquisition parameters.
3Reliability
If grain diffraction patterns are removed through image processing, then noise is reduced and defect detection improves, but processing time increases
Solution Approach 1:
The patent applies preliminary action by acquiring multiple digital images at different scales before the actual inspection analysis. These pre-acquired images are then scaled to a common scale and processed to remove grain diffraction patterns, preparing the data in advance for reliable defect detection. This preliminary data collection and processing reduces the time needed during the actual inspection phase while maintaining high reliability.
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 solution significantly reduces noise in inspection images, improving defect detection accuracy and reducing false positives/negatives by eliminating grain diffraction pattern variations, thus enhancing the efficiency of non-destructive testing in industrial radiography.
Implementation Method 1
the first digital image having a first grain diffraction pattern at the first scale, the second digital image having a second grain diffraction pattern at the second scale
Data Source
AI summary
There is described a method for forming an inspection image of an object from radiographic imaging. The method has: forming the inspection image including scaling a feature of the object in one or more digital images to a common scale, the digital images including first and second digital images of the object, the first digital image having the feature at a first scale, the first digital image having a first grain diffraction pattern at the first scale, the second digital image having the feature at a second scale different from the first scale, the second digital image having a second grain diffraction pattern at the second scale, the second grain diffraction pattern different from the first grain diffraction pattern, the common scale common to both the first and second digital images after said scaling, and removing grain differences between the first and second grain diffraction patterns at the common scale.