Defect Detection Apparatus Using Coordinate Data Correlation
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Solution Overview
Problem
Existing defect detection systems for structures struggle to accurately and automatically calculate the shape, length, width, position, and type of defects such as cracks on external appearances, particularly in complex surfaces like bridges, dams, and buildings, using ultratelephoto cameras and image analysis, without manual intervention.
Innovation Solution
A defect detection apparatus and program that includes a defect detection unit and a calculation unit, which uses imaging processing to identify defects in external appearance images from surveying instruments, correlating coordinate data to calculate defect data, enabling automatic detection and measurement of defects like cracks on various surface types, including vertical, horizontal, inclined, and free-form surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If ultratelephoto camera and image analysis are used to detect defects, then defect detection capability is improved, but automatic calculation of defect parameters (shape, length, width, position) cannot be achieved
Solution Approach 1:
The patent introduces coordinate data as an intermediary element that links the captured image data with the actual physical dimensions and positions of defects. The coordinate data serves as a mediator that enables the calculation unit to automatically compute defect parameters by correlating image coordinates with real-world measurements, thus achieving automatic calculation without manual intervention
Solution Approach 2:
The patent replaces manual measurement and calculation methods with an automated calculation unit that processes image data and coordinate data through computational algorithms. This substitution of mechanical/manual operations with computational processing enables automatic determination of defect shape, length, width, and position
2Measurement precision
If manual measurement and calculation methods are used, then defect parameters can be obtained, but time consumption and manual error increase
Solution Approach 1:
The system enables self-service by allowing the calculation unit to automatically process image data and compute defect parameters without requiring manual measurement or calculation. The automated processing reduces both time consumption and potential for human error, as the system performs measurements and calculations independently based on the captured images and coordinate data
Solution Approach 2:
Manual measurement and calculation operations are replaced with automated computational processing. The calculation unit uses algorithms to automatically determine defect parameters from image data, eliminating the need for time-consuming manual measurements and reducing human error in the process
Data Source
AI summary
A defect detection apparatus includes a defect detection unit and a calculation unit. The defect detection unit detects a defect that appears on an external appearance of a structure through imaging processing from external appearance image data that is generated by imaging the external appearance of the structure with a surveying instrument. The calculation unit calculates defect data relating to the defect detected by the defect detection unit by using coordinate data that is correlated with the external appearance image data.