Concrete Structure Damage Assessment Using Local-Global Image Analysis
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Solution Overview
Problem
Existing methods for determining the damage degree of concrete structures based on crack widths and grid patterns are inadequate as they do not effectively integrate local and global range information, leading to inconsistencies and worker variability in damage assessment.
Innovation Solution
An information processing apparatus and method that utilizes a combination of local and global image processing techniques, including machine learning algorithms and image reduction methods, to accurately determine crack widths and grid patterns, integrating these features to assess damage degree.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If image reduction is performed to determine grid patterns in global range, then global structure assessment is improved, but local crack width information may be lost
Solution Approach 1:
The patent divides the damage assessment into two distinct segments: local range analysis for crack width measurement and global range analysis for grid pattern determination. The local range process operates on the original high-resolution image to preserve measurement precision, while the global range process operates on a reduced image to capture overall structural patterns. This segmentation allows both precision and global context to be maintained without compromise.
2Reliability
If automated image processing is implemented to reduce worker variability, then consistency in damage assessment is improved, but complexity of the processing system increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: a local range process for crack detection and width measurement, and a global range process for grid pattern recognition. Each module performs a specific function with clear input-output relationships, making the overall complex system manageable and maintainable while ensuring consistent, automated assessment without worker variability.
3Measurement precision
If both local and global range analyses are performed separately, then assessment accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs image reduction as a preliminary action before global range analysis. By pre-reducing the image to an appropriate size for grid pattern recognition, the system avoids the computational burden of analyzing full-resolution images for global features, thereby reducing processing time while maintaining assessment accuracy through the subsequent local range analysis on the original image.
Data Source
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AI summary
An information processing apparatus comprises detection means for detecting a defect occurring in a structure by using local information about the structure based on a first image of the structure, first determination means for determining a global state of the structure based on a result of detection of the defect by the detection means and global information indicating information about a wider area than an area of the structure indicated by the local information, the global information being based on a second image having a lower resolution than that of the first image, and second determination means for determining a degree of damage to a predetermined area of the structure based on a result of determination made by the first determination means of the global state of the structure.