Cyclostationary Approach for Long Term Vibration Data Analysis

Abstract

Condition monitoring of the rotating machines plays a key role in their maintenance. It is challenging task, especially in case of machines operating in the varying conditions (e.g. wind turbines, road headers). Typically the spectral analysis is used for the damage detection. Undoubtedly, this method is suitable for simple signals in order to analyse the energy of the signal. The local fault reveals in the vibration as a pulse train with high energy. However, for complex data with many different components and high contamination it can be insufficient to analyse only the envelope spectrum. In order to detect fault in such signals the cyclostationary approach can be applied, which gives a possibility to detect many different sources of faults. In this article the long term data is analysed, in particular there are presented results for the simulated and real case. For each observation the bi-frequency map is computed. It is shown that analysing the modulation frequency we are able to track the development of the damage. The results are compared with the classical spectral approach.