Drone Malfunction Detection via Acceleration Radar Chart Analysis
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Solution Overview
Problem
Current drone monitoring systems rely on UTM and remote ID data, assuming drones are functioning normally, but fail to detect malfunctioning drones, which can lead to crashes and safety risks.
Innovation Solution
A flying object monitoring system that includes a reception unit for flight information, a calculation unit to calculate acceleration, a representation unit to create a radar chart image of acceleration, and a determination unit to identify malfunctioning drones based on the radar chart image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If drone monitoring relies on UTM and remote ID data, then information about registered drones can be obtained, but malfunctioning drones cannot be detected
Solution Approach 1:
The patent introduces an acceleration sensor as an intermediary device that directly measures drone motion. This sensor acts as a mediator between the drone's actual physical state and the monitoring system, providing direct acceleration data that reveals malfunction conditions not detectable through UTM or remote ID information alone.
Solution Approach 2:
The patent replaces reliance on electronic communication systems (UTM, remote ID) with direct mechanical measurement (acceleration sensing). By substituting the electronic information channel with a mechanical measurement channel, the system can detect actual physical anomalies that indicate drone malfunction, independent of electronic system status.
2Reliability
If drone trajectories are displayed for health check, then flight stability can be confirmed, but trajectories of multiple drones overlap and cannot be identified
Solution Approach 1:
The patent extracts the essential health indicator (acceleration data) from the complex trajectory visualization. Instead of displaying and analyzing entire flight paths, the system extracts and monitors only the acceleration characteristics, which directly indicate drone health status without the complexity of overlapping trajectory visualizations.
Solution Approach 2:
The patent changes the monitoring parameter from spatial trajectory coordinates to temporal acceleration values. This parameter transformation converts the complex two-dimensional trajectory problem into a simpler one-dimensional acceleration time-series analysis, making it easier to identify individual drone health status even when multiple drones are operating simultaneously.
3Reliability
If acceleration data is analyzed for each drone, then malfunctioning drones can be detected, but processing time increases
Solution Approach 1:
The patent applies partial action by focusing monitoring efforts only on acceleration parameters that are most indicative of malfunction, rather than analyzing all possible flight parameters. This selective approach maintains high detection accuracy while reducing overall processing time and computational burden.
Data Source
AI summary
According to one embodiment, a flying object monitoring system comprises a reception unit which receives flight information of a flying object, a calculation unit which calculates acceleration in each flight direction of the flying object from the flight information, a representation unit which represents the calculated acceleration with an acceleration distribution image formed by plotting the calculated acceleration with respect to the flight direction, and a determination unit which determines whether the flying object is malfunctioning based on the acceleration distribution image.