Aircraft Damage Inspection Using Sensor-Equipped Drones
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Solution Overview
Problem
Current aircraft inspection methods are poorly automated, prone to errors, and costly, failing to provide efficient and accurate detection of damage such as those caused by bird strikes, lightning strikes, or material fatigue.
Innovation Solution
An unmanned aerial vehicle operates in the vicinity of the aircraft, capturing measurement data using sensors, transmitting it wirelessly to a separate computer device for real-time or delayed detection of damage, utilizing AI and machine learning algorithms to analyze the data and potentially involving multiple drones for marking and repairing damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection by trained personnel is used, then detection accuracy can be maintained, but inspection cost and time consumption increase significantly
Solution Approach 1:
The patent replaces manual visual inspection by trained personnel with an automated optical measurement system using unmanned aerial vehicles equipped with sensors. The system captures measurement data of the aircraft surface and uses automated evaluation to detect damage, substituting human mechanical inspection with automated technological systems to achieve both high accuracy and improved productivity
Solution Approach 2:
The evaluation device automatically processes the measurement data captured by the sensor system, performing self-evaluation of the aircraft condition without requiring continuous human intervention. The system independently identifies damage locations and assesses their severity, enabling autonomous operation that maintains detection accuracy while dramatically improving inspection speed
2Reliability
If manual inspection methods are used, then detailed assessment can be performed, but error rates increase and automation is lacking
Solution Approach 1:
The patent replaces manual inspection processes with automated evaluation devices that process measurement data through computer algorithms. This substitution eliminates human errors inherent in manual inspection while maintaining detailed assessment capabilities through systematic automated analysis of aircraft surface conditions
Solution Approach 2:
The system implements automated feedback loops where measurement data is continuously captured, evaluated, and used to identify damage locations. The evaluation device provides systematic feedback on aircraft condition, enabling reliable detection and assessment without the variability and error-proneness of manual inspection methods
3Area of stationary object
If traditional inspection systems are used, then comprehensive coverage can be achieved, but cost effectiveness decreases
Solution Approach 1:
The patent divides the aircraft inspection task into multiple segments performed by unmanned aerial vehicles that can independently capture measurement data from different areas. This segmentation allows comprehensive coverage of the entire aircraft surface while reducing overall inspection costs through distributed, automated data collection across multiple independent units
Solution Approach 2:
The system replaces expensive traditional manual inspection methods with cost-effective automated evaluation devices mounted on unmanned aerial vehicles. This substitution maintains comprehensive inspection coverage while dramatically improving cost effectiveness through automated operation and reduced reliance on expensive human labor
Data Source
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AI summary
The invention relates to a computer-implemented method for inspecting an aircraft (1), comprising operating (20) an unmanned aircraft (100) in the area of the aircraft (1), and during operation (20) capturing (25) measurement data of the aircraft (1) by a sensor system (102) of the unmanned aircraft (100), sending (30) the measurement data to a computer device (3) separate from the unmanned aircraft (100) by means of a wireless communication method, and detecting (35) at least one damage location (2) of the aircraft (1) on the basis of the measurement data.