Signal processing tools for non-stationary signals detection
作者： Thibaud Plazenet , Thierry Boileau , Cyrille Caironi , Babak Nahid-Mobarakeh
DOI: 10.1109/ICIT.2018.8352466
关键词:
摘要: In this paper we aim to compare the abilities and performances of signal processing tools detect non-stationary signals coming from condition monitoring electrical machines. From vast amount available tools, focus on existing methods suitable for real applications non-stationarities tracking quantification over time which is particularly interesting in fault diagnosis. First, assess spectral kurtosis, a tool that gained much attention because his capability characterize transients masked by strong noises. order non-stationarities, other are evaluated such as subtraction through short Fourier transform or Wiener filtering can remove stationary components. The analytical framework each first presented. Non-stationary tests based properties vibration bearings proposed effectiveness, advantages drawbacks detection. purpose select method best suited type non-stationarity improve reliability
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