Aircraft Icing Detection Using Optical Sensor Reflectance
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Solution Overview
Problem
Conventional icing detection systems for aircraft are insufficient in detecting and preventing ice buildup on control surfaces and other critical components, leading to potential loss of control and reduced aerodynamic performance due to their inability to accurately detect even thin ice layers.
Innovation Solution
An optical sensor system configured to view exterior aircraft surfaces and components, using LIDAR or other sensors to output data on optical qualities such as shape and reflectance, which is compared to predetermined data to determine icing presence, and can activate a deice system if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional icing detection systems are used, then the system is simple and easy to operate, but the measurement precision is insufficient to detect thin ice layers
Solution Approach 1:
The patent replaces conventional mechanical or electrical icing detection systems with an optical sensing system using LIDAR. The LIDAR sensor emits laser pulses and measures the reflected light to detect ice accumulation on aircraft surfaces, providing precise measurement of ice thickness and distribution without complex mechanical contact sensors or electrical circuits on the aircraft surface.
Solution Approach 2:
The system changes the detection parameter from electrical or mechanical contact methods to optical parameters. By measuring the reflectance and time-of-flight of laser pulses, the system detects ice thickness through optical property changes, enabling precise detection of thin ice layers that conventional systems miss.
2Measurement precision
If optical sensors with line of sight view are used, then the measurement precision improves, but the device complexity increases due to mounting requirements
Solution Approach 1:
The LIDAR sensor serves multiple functions: it measures both the shape of aircraft surfaces and the presence of ice on those surfaces. By using a single optical sensor for both geometric mapping and icing detection, the system reduces the number of separate mounting locations and sensors needed, simplifying the overall device complexity while maintaining high measurement precision.
3Reliability
If real-time icing detection is implemented, then the reliability improves, but the use of energy increases due to continuous monitoring
Solution Approach 1:
The LIDAR sensor operates by emitting periodic laser pulses rather than continuous illumination. This pulsed operation mode provides real-time icing detection capability while significantly reducing energy consumption compared to continuous sensing, as the sensor only activates when measurement data is needed and allows the system to enter low-power states between pulses.
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
Provides real-time, accurate icing detection and counteraction, improving safety by effectively identifying and responding to ice buildup on aircraft surfaces, ensuring continued aerodynamic performance.
Implementation Method 1
The optical sensor can include a LIDAR sensor for example
Implementation Method 2
The sensor data can include reflectance of the exterior surface or component
Data Source
AI summary
A system for detecting icing includes an optical sensor configured to view at least a portion of an exterior surface or component of an aircraft and to output sensor data indicating at least one optical quality of the exterior surface or component, and an icing detection module. The icing detection module is configured to receive the sensor data from the optical sensor, compare the sensor data to predetermined quality data indicating at least one known optical quality of the exterior surface or component without icing, and determine the presence of icing on the exterior surface or component based on a difference between the sensor data and the predetermined quality data.