Bearing natural degradation detection in a gearbox: A comparative study of the effectiveness of adaptive filter algorithms and spectral kurtosis

Faris Elasha, Cristobal Ruiz-Carcel, David Mba

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

Bearing faults detection at the earliest stages is vital in avoiding future catastrophic failures. Many traditional techniques have been established and utilized in detecting bearing faults, though, these diagnostic techniques are not always successful when the bearing faults take place in gearboxes where the vibration signal is complex; under such circumstances it may be necessary to separate the bearing signal from the complex signal. The objective of this paper is to assess the effectiveness of an adaptive filter algorithms compared to a Spectral Kurtosis (SK) algorithm in diagnosing a bearing defects in a gearbox. Two adaptive filters have been used for the purpose of bearing signal separation, these algorithms were Least Mean Square (LMS) and Fast Block LMS (FBLMS) algorithms. These algorithms were applied to identify a bearing defects in a gearbox employed for an aircraft control system for which endurance tests were performed. The results show that the LMS algorithm is capable of detecting the bearing fault earlier in comparison to the other algorithms.

Original languageEnglish
Title of host publicationDynamics, Vibration and Control; Energy; Fluids Engineering; Micro and Nano Manufacturing
PublisherWeb Portal ASME (American Society of Mechanical Engineers)
Number of pages6
Volume2
ISBN (Electronic)9780791845844
DOIs
Publication statusPublished - 2014
EventASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014 - Copenhagen, Denmark
Duration: 25 Jul 201427 Jul 2014

Conference

ConferenceASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014
CountryDenmark
CityCopenhagen
Period25/07/1427/07/14

Keywords

  • Adaptive filter
  • Bearing Diagnostics
  • Gearbox
  • Signal separation
  • Vibration

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computational Mechanics
  • Computer Science Applications
  • Modelling and Simulation

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  • Cite this

    Elasha, F., Ruiz-Carcel, C., & Mba, D. (2014). Bearing natural degradation detection in a gearbox: A comparative study of the effectiveness of adaptive filter algorithms and spectral kurtosis. In Dynamics, Vibration and Control; Energy; Fluids Engineering; Micro and Nano Manufacturing (Vol. 2). Web Portal ASME (American Society of Mechanical Engineers). https://doi.org/10.1115/ESDA2014-20244