A cyclostationary analysis applied to detection and diagnosis of faults in helicopter gearboxes

  • Authors:
  • Edgar Estupiñan;Paul White;César San Martin

  • Affiliations:
  • Department of Mechanical Engineering, Universidad de Tarapacá, Arica, Chile;Institute of Sound and Vibration, University of Southampton, Southampton, UK;Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile and Department of Electrical Engineering, Universidad de La Frontera, Temuco, Chile

  • Venue:
  • CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
  • Year:
  • 2007

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Abstract

In several cases the vibration signals generated by rotating machines can be modeled as cyclostationary processes. A cyclostationary process is defined as a non-stationary process which has a periodic time variation in some of its statistics, and which can be characterized in terms of its order of periodicity. This study is focused on the use of cyclic spectral analysis, as a tool to analyze second-order periodicity signals (SOP), such as, those who are generated by either localized or distributed defects in bearings. Cyclic spectral analysis mainly consists of the estimation of the random aspects as well as the periodic behavior of a vibration signal, based on estimation of the spectral correlation density. The usefulness of cyclic spectral analysis for the condition monitoring of bearings, is demonstrated in this paper, through the analysis of several sections of vibration data collected during an endurance test of one of the two main gearbox transmissions of a helicopter.