Aircraft Buffet Detection Using Accelerometer Metrics
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Solution Overview
Problem
Traditional methods for detecting aircraft buffet rely on pilot perception, which is subjective and leads to inaccuracies due to varying pilot tolerances, making buffet detection unreliable and repeatable.
Innovation Solution
A system that uses onboard sensors to generate lateral and vertical acceleration datasets, calculates buffet metrics by applying weights to prioritize human-perceptible frequencies, and provides a buffet indicator based on these metrics to a display device, enabling automatic detection of initial and deterrent buffet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pilot perception methods are used for buffet detection, then the system is simple and easy to operate, but the measurement precision and reliability are poor due to varying pilot tolerances
Solution Approach 1:
The patent replaces the subjective human perception system with an objective automated detection system using accelerometers and signal processing algorithms. The system uses sensors to measure aircraft acceleration and applies computational methods to automatically detect buffet conditions, eliminating dependence on pilot subjective tolerance thresholds.
Solution Approach 2:
The system enables self-service buffet detection by automatically analyzing sensor data without requiring pilot intervention or subjective assessment. The automated algorithm continuously monitors acceleration data and independently determines when buffet conditions occur, allowing the system to serve itself rather than relying on human operators.
2Reliability
If automated sensor-based detection is implemented, then reliability and repeatability improve, but device complexity increases
Solution Approach 1:
The patent segments the detection system into distinct functional components: accelerometers for measuring vertical and lateral acceleration, a buffet detection algorithm for processing the signal data, and a display interface for presenting results. This modular segmentation allows each component to be optimized independently while working together to provide reliable automated detection.
3Measurement precision
If multiple sensors are used to capture comprehensive buffet data, then measurement precision improves, but the complexity of data processing increases
Solution Approach 1:
The patent merges vertical and lateral acceleration data from multiple sensors into a unified buffet metric through a combined detection algorithm. By integrating data from different sensor orientations and applying weightings to prioritize human-perceptible frequencies, the system consolidates multiple measurement streams into a single comprehensive buffet assessment, reducing the complexity of interpreting individual sensor readings.
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
The system provides a more reliable and repeatable detection of aircraft buffet, reducing pilot-dependent inaccuracies and enabling timely responses to avoid stall conditions by automatically determining buffet levels.
Implementation Method 1
The accelerometer sensor data includes vertical acceleration sensor data and lateral acceleration sensor data associated with a time window
Data Source
AI summary
A device includes one or more processors configured to access sensor data generated during a time window by one or more sensors onboard an aircraft. The one or more processors are configured to determine, based on the sensor data, a lateral acceleration dataset indicating frequency and magnitude of lateral buffet of the aircraft detected during the time window. The one or more processors are configured to determine, based on the sensor data, a vertical acceleration dataset indicating frequency and magnitude of vertical buffet of the aircraft detected during the time window. The one or more processors are configured to determine a buffet metric based on the lateral acceleration dataset and the vertical acceleration dataset. The one or more processors are configured to determine a buffet indicator based, at least in part, on the buffet metric. The one or more processors are configured to provide the buffet indicator to a display.