Aircraft Ice Detection System Using Sensor Segmentation
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Solution Overview
Problem
Current aircraft icing detection systems are unable to differentiate between normal and supercooled large drop icing conditions, which can lead to unsafe operating conditions due to their inability to detect ice formation caused by varying sizes of supercooled water drops.
Innovation Solution
An ice detection system comprising a first group of sensors and a second group of sensors, strategically located on an aircraft to detect different types of icing conditions, with a processor unit to monitor data and initiate actions in response to the presence of either type of icing condition, specifically designed to differentiate between normal and supercooled large drop icing conditions based on drop size and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current sensors are used for icing detection, then the system is simple and easy to operate, but the system cannot differentiate between normal and supercooled large drop icing conditions
Solution Approach 1:
The detection system is divided into multiple sensor groups (first group and second group) positioned at different locations on the aircraft. Each sensor group detects icing conditions at its specific location, and the processor compares data between groups to differentiate between normal icing and supercooled large drop icing conditions based on spatial distribution patterns.
Solution Approach 2:
The invention adds a spatial dimension to icing detection by deploying sensors at multiple locations rather than using a single sensor. This multi-location approach enables the system to detect patterns and differences in icing formation across the aircraft surface, providing the capability to differentiate between icing types.
2Reliability
If multiple sensor groups are deployed to detect different icing conditions, then the detection accuracy is improved, but the device complexity increases
Solution Approach 1:
The system segments the detection function across multiple sensor groups located at different positions on the aircraft. Each sensor group independently monitors its local area, and the processor integrates these segmented measurements to provide comprehensive and reliable detection of different icing conditions.
Solution Approach 2:
The processor continuously receives data from multiple sensor groups and compares the measurements to identify patterns indicative of different icing types. This feedback mechanism enables real-time differentiation between normal icing and supercooled large drop icing conditions, improving detection reliability.
Data Source
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AI summary
An ice detection system (122) comprising a first group of sensors (148) and a second group of sensors (170). The first group of sensors (148) is located in a first group of locations on an aircraft (100). The first group of sensors (148) in the first group of locations is configured to detect a first type of icing condition for the aircraft (100). The second group of sensors (170) is located in a second group of locations on the aircraft (100). The second group of sensors (170) in the second group of locations is configured to detect a second type of icing condition for the aircraft (100).