Aircraft Tyre Wear Forecasting for Residual Landing Prediction
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Solution Overview
Problem
Current methods for forecasting the wear state and maintenance of aeroplane tyres are inadequate, leading to unpredictable tyre removal due to performance deviations and external damage, which burdens maintenance operations and increases costs.
Innovation Solution
A computer-implemented method using machine learning, specifically gradient boosting regressor (GBR), to forecast the remaining lifetime of aeroplane tyres based on historic flight data and general tyre information without additional sensors, predicting the number of landings until the removal threshold is reached.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional forecasting methods are used for aeroplane tyre wear, then maintenance operations become unpredictable and costs increase, but adding sensors or complex measurement systems increases device complexity and operational burden
Solution Approach 1:
The patent uses image capture to create a visual copy of the tyre tread pattern, which is then processed through template matching to forecast wear state. This avoids the need for physical sensors on the tyre while achieving accurate wear prediction through optical copying and digital analysis
Solution Approach 2:
The patent replaces mechanical sensor-based measurement systems with an optical imaging and image processing system. Instead of using physical sensors to measure tread depth, the system uses captured images and computer vision algorithms to analyze wear patterns and predict remaining lifetime
2Adaptability or versatility
If prior-art forecasting methods are applied to aeroplane tyres, then wear state can be displayed, but these methods are not applicable to aeroplane tyres due to their unique wear characteristics and operational conditions
Solution Approach 1:
The patent uses multiple local templates corresponding to different regions of the tyre tread (shoulder, center, etc.) to capture the non-uniform wear patterns characteristic of aeroplane tyres. Each local template is matched independently to provide region-specific wear analysis, which is then integrated into the overall forecast
Solution Approach 2:
The patent transforms the wear analysis from direct tread depth measurement to template matching of tread pattern geometry. By changing the parameter from absolute depth measurement to relative pattern matching, the system adapts to the unique wear characteristics of aeroplane tyres while maintaining precision
3Measurement precision
If wear forecasting is performed without considering specific aeroplane tyre parameters, then the method is simpler, but the forecasting accuracy decreases due to significant performance deviations
Solution Approach 1:
The patent segments the tyre tread into multiple local regions (shoulder, center, etc.) and creates specific templates for each region. This segmentation allows the system to capture the non-uniform wear patterns of aeroplane tyres and process each region independently, improving overall forecasting accuracy while managing data complexity through structured organization
4Measurement precision
If additional sensors are added to measure tyre wear parameters, then measurement precision improves, but device complexity and operational burden increase
Solution Approach 1:
The patent uses optical imaging to create a digital copy of the tyre tread pattern, eliminating the need for physical sensors. The image capture device records the tread geometry, which is then analyzed through template matching to derive wear parameters with high precision without any contact with the tyre surface
Data Source
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AI summary
The invention relates to a computer-implemented forecasting method (200) for forecasting a number of residual landings (remaining LPT) corresponding to achievement of a removal threshold of an identified tyre, which is output by a forecasting model. During the forecasting method, a value of the removal threshold of the identified tyre, which is installed on an identified aeroplane, is compared with the number of residual landings (remaining LPT) before achievement of the removal threshold of the identified tyre, and as a consequence a system (100) that carries out the forecasting method creates a maintenance schedule for the identified tyre.