Abstract
This paper focuses on the diagnostics of ball bearings under time varying speed conditions. Compared to classical demodulation techniques, time-frequency approach allows to take into account transient occurrence or non-stationary phenomena along the timeline. Among the different time-frequency approaches available the simplest is the Short Time Fourier Transform (STFT). From a practical point of view, its implementation in an industrial environment has a main drawback: the industry usually needs a scalar value as output (like a semaphore: green, yellow and red light) to assess the bearing condition, while time-frequency approaches produce a bi-dimensional map that needs to be interpreted. The authors suggest to combine the information gathered by spectral kurtosis and energy distribution for the automatic selection of a filtering band that could extract from the STFT map the most informative component in time domain, reducing the complexity of the output to a mono-dimensional vector. A simple check if the output exceed a given threshold can then be used to obtain a scalar value.
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Cocconcelli, M., Zimroz, R., Rubini, R., Bartelmus, W. (2012). Kurtosis over Energy Distribution Approach for STFT Enhancement in Ball Bearing Diagnostics. In: Fakhfakh, T., Bartelmus, W., Chaari, F., Zimroz, R., Haddar, M. (eds) Condition Monitoring of Machinery in Non-Stationary Operations. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28768-8_6
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DOI: https://doi.org/10.1007/978-3-642-28768-8_6
Publisher Name: Springer, Berlin, Heidelberg
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