3D Crack Quantification via Depth Perception
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current visual inspection methods for structures are qualitative and non-adaptive, failing to reliably quantify crack thickness, especially in inaccessible regions, and existing Non-Destructive Testing methods are not effective for contactless crack detection and quantification.
Innovation Solution
The development of contactless remote-sensing crack detection and quantification methodologies using three-dimensional scene reconstruction, image processing, and pattern recognition, which incorporate depth perception to analyze images from any distance and focal length, suitable for integration with autonomous or semi-autonomous robotic systems for inspecting concrete structures like buildings, dams, and bridges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection methods are used for crack detection, then the inspection can be performed visually, but the method is highly qualitative and cannot reliably quantify crack thickness
Solution Approach 1:
The patent transitions from 2D image analysis to 3D scene reconstruction by incorporating depth perception through multi-view geometry and structure-from-motion techniques. This dimensional enhancement enables accurate crack thickness quantification by recovering three-dimensional coordinates of crack surfaces from multiple two-dimensional images taken from different viewpoints.
Solution Approach 2:
The patent introduces an intermediary processing system that bridges visual inspection and crack quantification. This system includes image acquisition devices, feature extraction algorithms, 3D reconstruction modules, and crack characterization algorithms that work together to transform qualitative visual data into quantitative crack measurements.
2Reliability
If optical devices such as binoculars are used to inspect inaccessible regions, then detection capability is improved, but the method remains nonadaptive and cannot quantify crack thickness reliably
Solution Approach 1:
The patent implements dynamic adaptability through automated feature detection and classification algorithms that can identify and characterize cracks of varying sizes, orientations, and patterns. The system adapts to different inspection scenarios by adjusting parameters such as image resolution requirements, depth perception methods, and crack detection thresholds based on the specific structural context.
Solution Approach 2:
The patent creates a universal inspection system that can handle multiple types of structures (buildings, bridges, dams) and various crack configurations through a single integrated platform. The system combines multiple functions including image capture, 3D reconstruction, crack detection, thickness measurement, and pattern recognition into one versatile methodology applicable to diverse inspection scenarios.
3Ease of operation
If contactless remote-sensing methodologies are used, then inaccessible regions can be inspected, but the system requires three-dimensional scene reconstruction and depth perception
Solution Approach 1:
The patent creates a digital 3D copy of the inspected structure's surface through photogrammetry and structure-from-motion techniques. By reconstructing the three-dimensional geometry from multiple 2D images, the system generates a virtual model that can be analyzed without physical contact, enabling inspection of inaccessible regions while maintaining measurement accuracy.
Data Source
AI summary
Contact-less remote-sensing crack detection and/quantification methodologies are described, which are based on three-dimensional (3D) scene reconstruction, image processing, and pattern recognition. The systems and methodologies can utilize depth perception for detecting and/or quantifying cracks. These methodologies can provide the ability to analyze images captured from any distance and using any focal length or resolution. This adaptive feature may be especially useful for incorporation into mobile systems, such as unmanned aerial vehicles (UAV) or mobile autonomous or semi-autonomous robotic systems such as wheel-based or track-based radio controlled robots, as utilizing such structural inspection methods onto those mobile platforms may allow inaccessible regions to be properly inspected for cracks.