Defect Width Traceability Using Divide-and-Conquer
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image processing algorithms face challenges in accurately measuring the width of defects on large-diameter components in real-time, especially when the defect width approaches the diffraction limit of the system, leading to inefficiencies and inaccuracies in surface quality control.
Innovation Solution
A real-time traceability method based on divide-and-conquer, combining calibration transfer function (CTF), multidimensional eigenvector analysis using an electromagnetic field simulation database, and adaptive threshold segmentation, to estimate the width of defects effectively across different size ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing algorithms are used to measure defect width, then the measurement process is simple, but the measurement precision deteriorates when defect width approaches the diffraction limit
Solution Approach 1:
The patent segments the defect width measurement problem into three distinct ranges based on the diffraction limit: (1) defect width > diffraction limit using calibration transfer function, (2) defect width ≈ diffraction limit using electromagnetic field simulation database, and (3) defect width < diffraction limit using adaptive threshold segmentation. This segmentation allows each method to be optimized for its specific range, improving overall measurement precision across all defect sizes.
Solution Approach 2:
The patent changes the measurement parameters and methods based on the defect width relative to the diffraction limit. For larger defects, it uses geometric imaging parameters; for defects near the diffraction limit, it uses electromagnetic field simulation parameters; for smaller defects, it uses image processing parameters. This parameter adaptation resolves the contradiction by matching the measurement method to the physical regime of the defect.
2Productivity
If calibration transfer function is used for defect width traceability, then the measurement is fast, but the measurement precision deteriorates when defect width is close to the diffraction limit
Solution Approach 1:
The patent divides the measurement task into two segments: fast measurement for defects > diffraction limit using calibration transfer function, and precise measurement for defects ≈ diffraction limit using electromagnetic field simulation database. This segmentation maintains high productivity for most defects while ensuring precision for critical cases near the diffraction limit.
Solution Approach 2:
The patent introduces an intermediary classification step that first estimates defect width using the fast calibration transfer function, then determines whether further precise measurement is needed. This intermediary step acts as a gatekeeper, maintaining productivity by avoiding unnecessary complex calculations while ensuring precision when required.
3Measurement precision
If electromagnetic field simulation database is used for defect width traceability, then the measurement precision is improved for defects near diffraction limit, but the processing time increases
Solution Approach 1:
The patent segments the defect population by size relative to the diffraction limit, applying the computationally intensive electromagnetic field simulation database only to defects in the critical size range where precision is most needed. This selective application minimizes processing time for the overall defect population while maintaining high precision for critical cases.
Solution Approach 2:
The patent applies the high-precision electromagnetic field simulation method partially, only to defects near the diffraction limit where it is most needed, rather than applying it to all defects. This partial action achieves the necessary precision for critical measurements without the excessive processing time that would result from universal application.
4Productivity
If manual visual inspection is used for surface quality control, then the equipment complexity is low, but the productivity and measurement precision are poor
Solution Approach 1:
The patent segments the inspection system into automated image acquisition, algorithm-based measurement, and classification components, replacing manual visual inspection with a structured automated process. This segmentation enables high productivity through automation while managing complexity through modular design of the inspection system.
Solution Approach 2:
The patent replaces the mechanical/manual visual inspection system with an automated optical imaging and computational analysis system. This substitution dramatically improves productivity and measurement precision, with the complexity managed through software-based algorithms rather than mechanical complexity.
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 achieves accurate width recognition with a mean square deviation of less than 0.3 μm, overcoming limitations of traditional methods and enabling real-time detection of defects near the diffraction limit, and is adaptable for integration with future IoT and big data analysis.
Implementation Method 1
when the width of the defect is close to the diffraction limit of the system
Implementation Method 2
defect scattered dark-field imaging
Data Source
AI summary
In a real-time traceability method of a width of a defect based on divide-and-conquer provided by the present invention, through the calibration transfer function, the multidimensional eigenvector analysis technology based on the electromagnetic field simulation database of defect scattered dark-field imaging and the adaptive threshold segmentation method, the real-time traceability of the width of the defect greater than and close to the diffraction limit of the system is performed, respectively. The extreme random tree regression model is trained by multidimensional eigenvector analysis technology based on the multidimensional eigenvectors in the electromagnetic field simulation database of the defect scattered dark-field imaging. The present invention solves the problems that the width of the defect in defect detection is difficult to be accurately measured in real time, and the conventional image processing algorithm is difficult to accurately identify the width of the defect close to the diffraction limit of the system.