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
Kurtosis over Energy Distribution Approach for STFT Enhancement in Ball Bearing Diagnostics / Cocconcelli, Marco; R., Zimroz; Rubini, Riccardo; W., Bartelmus. - STAMPA. - (2012), pp. 51-59. (Intervento presentato al convegno The second International Conference Condition Monitoring of Machinery in Non-Stationary Operations tenutosi a Hammamet (Tunisia) nel 26-28 marzo 2012) [10.1007/978-3-642-28768-8_6].
Kurtosis over Energy Distribution Approach for STFT Enhancement in Ball Bearing Diagnostics
COCCONCELLI, Marco;RUBINI, Riccardo;
2012
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 valueFile | Dimensione | Formato | |
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