Aircraft Sensor Failure Detection via Anemo-Inertial Loop Deviation Analysis
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Solution Overview
Problem
Current methods for detecting sensor failures on aircraft, such as ice accretion on Pitot tubes, are not robust and may result in partial or undetected anomalies, especially when all sensors provide coherent but incorrect data, leading to potential incidents and accidents.
Innovation Solution
A method involving an anemo-inertial loop that measures horizontal acceleration and airspeed, computes intermediate parameters based on deviations between short-term anemo-inertial and anemometric speeds, and loops to detect failures by accumulating deviations, with variable gains and corrections, to determine the presence of sensor anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If ice accretion detection methods are implemented, then blockage detection capability is improved, but not all failure cases are well characterized and anomalies may only be partially detected
Solution Approach 1:
The patent creates a universal detection framework based on aerodynamic models that can handle multiple types of sensor failures (ice accretion, blockages, calibration errors) through a single coherent approach. This multi-functional model detects anomalies across different failure modes that were previously requiring separate detection methods.
Solution Approach 2:
The system implements feedback by continuously comparing actual sensor measurements with expected values derived from the aerodynamic model. This feedback mechanism allows the system to detect deviations indicating sensor failures and adjust or flag the data accordingly, improving detection completeness across various failure scenarios.
2Measurement precision
If anemo-inertial loop with intermediate parameters is implemented, then failure detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the failure detection process into distinct computational stages: computing intermediate parameters from sensor measurements, comparing these with model predictions, and making detection decisions. This segmentation makes the complex computation more manageable and allows for optimization at each stage.
Solution Approach 2:
The system performs preliminary computations of intermediate parameters (such as derived pressure and temperature values) before the actual failure detection comparison. This preliminary action organizes the computational workload and enables more accurate detection by preparing refined data in advance.
Data Source
AI summary
A method for detecting a failure of at least one sensor on board an aircraft is provided. The method includes implementing an anemo-inertial loop including obtaining a computed horizontal speed, based on an integration of a measured horizontal acceleration and obtainment of a short-term anemo-inertial speed from the computed horizontal speed; developing at least one intermediate loop parameter based on a deviation between the short-term anemo-inertial speed and the anemometric speed or the airspeed; and observing a failure detection parameter obtained from an intermediate parameter of the anemo-inertial loop and determining the presence of a failure on one of the sensors of the aircraft, based on the value of the observed failure detection parameter.