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

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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. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Estupiñan, E., White, P., & Martin, C. S. (2007). A cyclostationary analysis applied to detection and diagnosis of faults in helicopter gearboxes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4756 LNCS, pp. 61–70). https://doi.org/10.1007/978-3-540-76725-1_7

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