In-flight Flutter Assessment via Vibration Mode Analysis
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Solution Overview
Problem
Current methods for in-flight flutter evaluation of airplanes are time-consuming and expensive, as they require post-flight analysis of vibration data, and are not capable of real-time assessment, leading to inefficiencies in determining damping coefficients for flutter prevention.
Innovation Solution
A computer-implemented method for real-time in-flight assessment of flutter using vibration sensors, which calculates mode shapes, damping coefficients, and autocorrelation functions through modified Fast Fourier Transform and least squares error analysis, allowing for immediate evaluation of aeroelastic properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If post-flight analysis of vibration data is used for flutter evaluation, then measurement precision can be maintained, but evaluation time and cost increase significantly
Solution Approach 1:
The system performs preliminary calculations of autocorrelation functions and spectral density during the flight test itself, rather than waiting for post-flight analysis. By pre-computing these critical parameters in real-time, the invention eliminates the time-consuming post-processing step while maintaining measurement precision through continuous monitoring and immediate evaluation of damping coefficients.
Solution Approach 2:
The invention enables continuous flutter evaluation throughout the flight test by maintaining ongoing calculation of vibration parameters, autocorrelation functions, and spectral density. This continuous processing allows real-time assessment of damping coefficients without interrupting the flight test sequence, thereby reducing total evaluation time while preserving measurement accuracy through uninterrupted data collection and analysis.
2Speed
If conventional Fast Fourier Transform algorithms are used for signal analysis, then computational speed is improved, but frequency resolution deteriorates for low-frequency vibrations
Solution Approach 1:
The invention modifies the Fast Fourier Transform parameters by adjusting the analysis window length and sampling rate to optimize for low-frequency vibrations. By changing these parameters, the system achieves both high computational speed through efficient FFT algorithms and sufficient frequency resolution for detecting flutter vibrations in the low-frequency range, resolving the trade-off between processing speed and measurement precision.
3Difficulty of detecting and measuring
If impulse excitation with rocket actuators is used for in-flight evaluation, then flutter can be detected, but device complexity and evaluation cost increase
Solution Approach 1:
The invention employs the airplane's own structural vibrations during normal flight operations as the excitation source, eliminating the need for external impulse excitation devices. By utilizing the aircraft's natural motion and aerodynamic forces, the system achieves flutter detection without adding complex rocket actuators or artificial excitation mechanisms, thereby reducing device complexity while maintaining detection capability.
Solution Approach 2:
The invention uses the autocorrelation function as an intermediary mathematical tool to extract flutter characteristics from vibration data. Instead of requiring complex physical excitation devices, the system processes vibration signals through autocorrelation analysis to identify damping coefficients and flutter tendencies, simplifying the overall measurement apparatus while maintaining effective flutter detection through computational rather than mechanical means.
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
This method enables quick and cost-effective in-flight evaluation of flutter, reducing test time and costs, while preserving accurate damping coefficient values and natural frequencies, facilitating safer and more efficient aircraft production.
Implementation Method 1
Flutter vibrations are self excited aeroelastic vibrations of an airplane structure during flight
Implementation Method 2
Flutter vibrations are self excited aeroelastic vibrations of an airplane structure during flight. At certain flight velocities, aerodynamic forces related to vibrating movement
Implementation Method 3
Fast Fourier Transform is commonly used for this purpose. However, typical Fast Fourier Transform algorithms are suitable for analysis of long segments of a signal and for high frequencies of the order of thousands of Hz
Implementation Method 4
the impulse response of a monitored object may be substituted with a self correlation function (also called an autocorrelation) of a stochastically excited signal
Implementation Method 5
The known methods for evaluation of flutter damping coefficients involve artificial excitation of vibrations and post-flight analysis of these vibrations for flights with consecutively increasing velocities. Impulse, harmonic or stochastic excitations are used. This requires mounting of measurement apparatus on the airplane
Data Source
AI summary
A computer-implemented method for in-flight assessment of freedom from flutter of an airplane, involving analyzing the airplane structure vibrations based on signals indicated by sensors located on the airplane structure. The computations are performed in real-time based on current measurement data collected from the sensors. For measurement data from individual sensors there are determined mode shapes of vibrations. The relevancy of modes of vibrations is determined by subtracting from the vibrations signal the particular mode of vibrations and calculating the value of decrease in the rest sum of squares.