Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Article

Download file Download BibTeX

Title

Advanced Spectral Diagnostics of Jet Engine Vibrations Using Non-Contact Laser Vibrometry and Fourier Methods

Authors

[ 1 ] Instytut Energetyki Cieplnej, Wydział Inżynierii Środowiska i Energetyki, Politechnika Poznańska | [ 2 ] Instytut Analizy Konstrukcji, Wydział Inżynierii Lądowej i Transportu, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.7] Civil engineering, geodesy and transport
[2.10] Environmental engineering, mining and energy

Year of publication

2025

Published in

Energies

Journal year: 2025 | Journal volume: vol. 18 | Journal number: iss. 18

Article type

scientific article

Publication language

english

Keywords
EN
  • jet engine diagnostics
  • vibration analysis
  • Fourier transform
  • laser vibrometry
  • non-contact measurement
  • signal processing
  • bearing damage detection
Abstract

EN This study presents an advanced diagnostic methodology for assessing mechanical faults in high-performance jet engines using non-contact laser vibrometry and Fourier-based vi-bration analysis. Focusing on Pratt & Whitney F100-PW-229 engines used in F-16 aircraft, thise research identifies critical measurement locations, including the gearbox, turbine, and compressor supports. High-resolution vibration signals were collected under test bench conditions and processed using fFast Fourier tTransform (FFT) techniques to extract frequency-domain features indicative of rotor imbalances, bearing wear, and structural anomalies. Comparative analysis between nominal and degraded engines confirmed strong correlations between analytical predictions and empirical spectral patterns. Thise study introduces a signal processing framework combining time–frequency analysis with Relief- F-based feature selection, laying the groundwork for future integration with ma-chine learning algorithms. This non-intrusive, efficient diagnostic method supports early fault detection, enhances engine availability, and contributes to the development of a na-tional vibration reference database, especially vital in the absence of OEM-supplied tools.

Date of online publication

11.09.2025

Pages (from - to)

4837-1 - 4837-22

DOI

10.3390/en18184837

URL

https://www.mdpi.com/1996-1073/18/18/4837

Comments

Article number: 4837

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Release date

11.09.2025

Date of Open Access to the publication

at the time of publication

Full text of article

Download file

Access level to full text

public

Ministry points / journal

140

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.