Abstract
The paper introduces the concept of Intelligent Spectrogram as a general tool for analysis of non-stationary signals. The method is based on a self-tuning mechanism, which automatically provides optimum window length of the spectrogram. The method calculates coefficients of variation (also known as relative standard deviation) for time and frequency scales and finds extremum value of their product. The proposed Intelligent Spectrogram might serve as an auxiliary tool for initial analysis of complex non-stationary signals, for which selection of particular window length might be beneficial for one class of signal components, but highly detrimental to others. The idea of the method is presented on a simulated signal, while its practical performance is illustrated on a real signal from a wind turbine run-down.
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