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The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
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Updated: Nov 24, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Detection of Aircraft Touchdown Using Longitudinal Acceleration and Continuous Wavelet Transformation.

Jerzy Bakunowicz1, Paweł Rzucidło2

  • 1Frenchay Campus, The University of the West of England, Coldharbour Lane, Bristol BS16 1QY, UK.

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Summary

This study introduces a new method for detecting aircraft touchdowns using accelerometer data. The technique identifies unique vibration patterns during landing, enhancing safety for light aircraft.

Keywords:
MEMSaccelerationaccelerometersaeroplanecontinuous waveletdetectionlanding gearlight aircrafttouchdownvirtual sensing

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Area of Science:

  • Aerospace Engineering
  • Vibration Analysis
  • Signal Processing

Background:

  • Accurate detection of aircraft touchdown is crucial for flight safety and data analysis.
  • Traditional methods analyzing flight parameters like height and speed face challenges in precise touchdown determination.
  • Structural vibrations during landing offer a potential alternative data source.

Purpose of the Study:

  • To develop and validate a novel methodology for detecting aircraft touchdowns.
  • To leverage accelerometer data from airframe structures for touchdown identification.
  • To enhance the precision of touchdown event detection, particularly for light aircraft.

Main Methods:

  • Utilizing accelerometer data from the aircraft's cockpit or passenger compartment.
  • Applying continuous wavelet analysis (CWT) to identify unique periodic features in structural vibrations.
  • Analyzing longitudinal acceleration patterns caused by landing gear contact with the ground.

Main Results:

  • The study identified repetitive, unique periodic features in longitudinal acceleration during aircraft touchdown.
  • Continuous Wavelet Analysis effectively distinguished landing-induced vibrations from other flight phase vibrations.
  • Experimental verification on the MP-02 Czajka aircraft confirmed the proposed virtual touchdown detection method's efficacy.

Conclusions:

  • The proposed accelerometer-based method reliably detects aircraft touchdowns.
  • The technique shows significant promise for broader application, especially within the light aircraft category.
  • This approach offers a valuable tool for enhancing aviation safety and data acquisition.