Airport Pavement Defect Detection Using UAS Orthomosaics
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Solution Overview
Problem
Current airport pavement management programs rely on manual inspections and average pavement condition index (PCI) assessments, which fail to track individual defects, leading to accelerated deterioration and costly repairs, as they do not provide frequent monitoring, detailed defect tracking, or integrated maintenance planning.
Innovation Solution
The method involves acquiring aerial images using unmanned aerial systems (UAS), generating orthomosaics, and applying photogrammetry and image analysis to determine defect locations and extent, producing heatmaps and enhanced distress layers for detailed condition assessment, and recommending targeted maintenance based on PCI values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection and average PCI assessment are used, then overall pavement condition can be assessed, but individual defects cannot be tracked and localized deterioration is missed
Solution Approach 1:
The pavement surface is divided into multiple inspection points distributed across the entire pavement area. Each inspection point captures local defect information, and these segmented measurements are aggregated to provide both detailed defect tracking and overall pavement condition assessment, resolving the contradiction between precision and complexity
Solution Approach 2:
A mobile inspection device serves as an intermediary between manual inspection methods and automated analysis systems. The device collects data at multiple locations and transmits it to a processing system, enabling precise defect detection while maintaining operational simplicity through standardized data collection procedures
2Reliability
If average PCI is used to determine maintenance timing, then overall pavement management is simplified, but localized defects lead to accelerated deterioration and accidents
Solution Approach 1:
The pavement is segmented into multiple monitoring zones with inspection points distributed throughout. This segmentation allows maintenance decisions to be based on localized defect conditions rather than average PCI, improving safety while maintaining ease of operation through automated data aggregation
Solution Approach 2:
The system continuously collects defect data at multiple inspection points and provides feedback on both local and overall pavement conditions. This feedback mechanism enables timely maintenance decisions based on actual defect progression, improving safety without complicating operational decision-making
3Productivity
If manual inspection is performed, then overall pavement condition can be evaluated, but frequent monitoring and defect tracking over time are not achieved
Solution Approach 1:
The inspection system is designed to operate continuously at multiple distributed points, enabling frequent monitoring without interrupting pavement operations. The mobile device can rapidly collect data at each inspection point and transmit it for analysis, maintaining continuous defect tracking while improving productivity through parallel inspection operations
Solution Approach 2:
The mobile inspection device acts as an intermediary that rapidly collects data at multiple locations and transmits it to centralized processing systems. This intermediary function enables frequent monitoring and continuous defect tracking by eliminating manual data processing delays and enabling automated analysis of defect progression over time
4Ease of manufacture
If extensive repairs are performed when only small portions are damaged, then pavement safety is ensured, but repair costs and resource consumption increase
Solution Approach 1:
The pavement is segmented into multiple inspection points that provide localized defect information. This segmentation enables identification of specific damaged areas rather than treating the entire pavement surface, allowing cost-efficient repairs only where needed while maintaining reliability through targeted maintenance
Solution Approach 2:
The system performs preliminary inspection and analysis at multiple locations to identify defects early in their progression. By detecting defects before they spread or worsen, the system enables timely, localized repairs that prevent the need for extensive rehabilitation, improving cost efficiency while maintaining pavement reliability
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
This approach enables frequent monitoring, detailed defect tracking, and cost-effective maintenance by providing actionable insights into pavement conditions, predicting future deterioration, and optimizing repair operations.
Implementation Method 1
acquiring aerial images of the site from above, for example by an unmanned aerial system (UAS)
Implementation Method 2
using photogrammetry tools to generate an orthomosaic that represents the airport pavement surface
Implementation Method 3
using image analysis tools to determine the location and extent of defects in the pavement
Data Source
AI summary
An example embodiment of the present invention provides a method of assessing the condition of a pavement site, comprising: (a) acquiring aerial images of the site from above, for example by an unmanned aerial system (UAS); (b) using photogrammetry tools to generate an orthomosaic that represents the airport pavement surface; (c) using image analysis tools and machine learning methods to determine the location and extent of defects in the pavement; (c) producing an image representation of the site and the defects, where the location and extent of defects are discernible from the image; (d) using software application techniques to store and present defect data and other related information for client-side user access.