UAV Profilometer Surface Profile Measurement
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Solution Overview
Problem
In-service inspection of large, hard-to-reach structures like wind turbine blades and aircraft requires efficient and accurate detection of damage, which is time-consuming and costly with human inspectors, and current autonomous systems lack the ability to accurately quantify anomalies without human intervention.
Innovation Solution
The use of unmanned aerial vehicles (UAVs) equipped with profilometers to measure surface profiles, allowing for autonomous or remotely controlled inspection and quantification of anomalies, including the attachment of a profilometer module to the structure using vacuum, electrostatic, or adhesive methods, and the use of laser-based or contact displacement sensors for depth measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human inspectors physically access limited-access structures for inspection, then anomaly detection can be performed using manual methods (e.g., finger nail scratch test), but inspection cost, time, and labor increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection methods with an automated UAV-based inspection system that uses optical sensors and image processing to detect anomalies. The system captures images of the structure surface and uses computer vision algorithms to identify potential defects, eliminating the need for human inspectors to physically access difficult-to-reach areas while maintaining detection accuracy.
Solution Approach 2:
The inspection system performs self-assessment by automatically analyzing captured images to identify and characterize anomalies. The UAV autonomously navigates to inspection points, captures images, and the embedded processing system automatically detects and evaluates defects without requiring continuous human intervention or manual verification at each anomaly site.
2Measurement precision
If human inspectors physically access limited-access structures for scratch tests, then material removal can be detected, but ergonomic issues and exposure to hazardous conditions occur
Solution Approach 1:
The patent replaces manual scratch tests with automated optical inspection methods. The UAV-based system uses high-resolution cameras and image processing algorithms to detect surface anomalies, including material removal, without requiring human inspectors to physically contact or closely examine the structure surface in hazardous or difficult-to-reach areas.
Solution Approach 2:
The patent introduces an intermediary automated inspection system between the human inspector and the structure being inspected. The UAV and its onboard sensors serve as the intermediary that collects data from the structure surface, eliminating direct human exposure to hazardous conditions while maintaining the ability to detect material removal through automated image analysis.
3Measurement precision
If manual scratch tests are used by inspectors in elevated positions, then anomaly depth can be assessed, but accurate quantification becomes difficult
Solution Approach 1:
The patent replaces manual depth assessment methods with automated optical measurement techniques. The UAV-based system uses stereo vision, structured light, or other optical ranging methods to precisely measure the depth of detected anomalies by analyzing image data and calculating three-dimensional surface profiles, providing accurate quantification without manual intervention.
Solution Approach 2:
The patent transitions from two-dimensional visual inspection to three-dimensional anomaly characterization. By using optical sensors and image processing to capture depth information and generate three-dimensional surface profiles of anomalies, the system provides accurate depth measurement while maintaining operational simplicity through automated processing.
4Ease of operation
If autonomous UAV inspection is implemented, then human access to limited-access structures is eliminated, but the ability to quantify anomalies accurately is reduced
Solution Approach 1:
The patent replaces manual quantification methods with automated optical measurement and image processing systems. The UAV captures high-resolution images and the onboard or ground-based processing system uses computer vision algorithms to automatically measure anomaly dimensions, depth, and other geometric characteristics, providing accurate quantification data without human intervention.
Solution Approach 2:
The inspection system incorporates feedback loops where captured images are automatically analyzed, anomaly characteristics are measured and validated, and results are used to guide further inspection or characterization activities. The system provides feedback on measurement quality and can adjust inspection parameters to ensure accurate quantification of anomalies.
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
Enables rapid, cost-effective, and accurate inspection and repair decisions by quantifying anomaly depths without human access, reducing downtime and ergonomic risks in the aerospace and other industries.
Implementation Method 1
the use of laser-based or contact displacement sensors for depth measurement
Implementation Method 2
the attachment of a profilometer module to the structure using vacuum, electrostatic, or adhesive methods
Implementation Method 3
the attachment of a profilometer module to the structure using vacuum, electrostatic, or adhesive methods
Data Source
AI summary
Systems, methods, and apparatus for acquiring surface profile information (e.g., depths at multiple points) from limited-access structures and objects using an autonomous or remotely operated flying platform (such as an unmanned aerial vehicle). The systems proposed herein use a profilometer to measure the profile of an area on a surface where visual inspection has indicated that the surface has a potential anomaly. After the system has gathered data representing the surface profile in the area containing the potential anomaly, a determination may be made whether the collected image data indicates that the structure or object should be repaired or may be used as is.