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EN
This paper deals with the problem of detecting spectral changes in non stationary noisy signals using non parametric tools. Belonging to this class, the time frequency representations (TFRs) allow a better insight into complicated processes by displaying the content of the signal in a 2-dimensional space. We propose in this article to extract exploitable knowledge from the time-frequency domain by the use of distance measures between TFRs. After presenting the different resulting stationarity indices, we show their performances in a monitoring context : the early detection of gear faults. The analysis of vibration signals which are representative of physical processes in gearboxes finally demonstrates the potential monitoring capability of the proposed methods.
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