Drone-Based Rock Slope Safety Evaluation Using Stereo Vision
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Solution Overview
Problem
Conventional joint surface safety evaluation methods are time-consuming, costly, and inefficient, particularly in accessing and predicting defects on rock slope surfaces, especially in mountainous areas, and lack effective tools for comprehensive safety assessment.
Innovation Solution
A joint surface safety evaluation apparatus using stereo image data to generate 3D point cloud data, extract rock slope surfaces through machine learning models, calculate evaluation scores based on inclination and direction angles, and determine safety levels, enabling remote evaluation and detailed safety assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If field visits by experts are used for joint surface safety evaluation, then safety evaluation can be performed, but it takes a lot of time and money and is dangerous due to difficult access in mountainous areas
Solution Approach 1:
The patent uses drone-based aerial imaging to create a virtual copy of the joint surface environment, allowing safety evaluation without physical presence at the hazardous site. The drone captures images and 3D point cloud data that replicate the joint surface geometry and features, enabling remote expert analysis.
Solution Approach 2:
The patent replaces the mechanical field visit approach with an optical/electromagnetic system. Instead of experts physically traveling to the site, the system uses drones equipped with cameras and laser scanners to capture data, substituting mechanical travel with aerial robotic inspection.
2Measurement precision
If conventional 3D laser scanning is used, then defect detection is possible, but it is inconvenient to separately provide a 3D laser scanner and a camera
Solution Approach 1:
The patent merges the 3D laser scanner and camera into a single integrated drone payload system. The drone platform simultaneously carries both the laser scanner for geometric data and the camera for visual data, eliminating the need for separate equipment deployments and simplifying the overall system configuration.
Solution Approach 2:
The drone serves as a universal platform that can perform multiple functions: aerial transport, laser scanning, photogrammetry, and visual imaging. This multi-functional approach replaces the need for multiple specialized devices, reducing system complexity while maintaining measurement precision.
3Loss of information
If conventional image analysis is used, then defect information can be obtained, but it cannot predict defects before they occur without 3D data
Solution Approach 1:
The patent transitions from 2D image analysis to 3D point cloud data processing. By capturing spatial coordinates, normal vectors, and surface geometry at multiple points across the joint surface, the system adds the third dimension of depth and spatial relationships, enabling prediction of potential defects based on 3D structural characteristics.
Solution Approach 2:
The system performs preliminary 3D modeling and geometric analysis to identify potential defect locations before actual damage occurs. By analyzing the 3D point cloud data for anomalies in surface geometry, normal vector inconsistencies, and spatial patterns, the system can predict future defects based on current structural state.
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 apparatus efficiently extracts rock slope surfaces, evaluates safety by grouping similar areas, and provides comprehensive safety ratings, considering both inclination and crack presence, facilitating safer and more cost-effective joint surface management.
Implementation Method 1
generate point cloud data constituted by a plurality of coordinates having a depth estimated from the stereo image data
Data Source
AI summary
The present disclosure relates to a joint surface safety evaluation apparatus and, more particularly, to a joint surface safety evaluation apparatus for generating mesh data consisting of a combination of a plurality of polygonal mesh surfaces, based on stereo image data generated by photographing an evaluation target surface, generating modeling data by overlapping the stereo image data and the mesh data, extracting a mesh surface corresponding to a rock slope surface by applying the modeling data to a learning model, and calculating a joint surface evaluation score regarding the evaluation target surface, by using a normal vector for each of a plurality of extracted mesh surfaces.