Abstract
Vibration data recorded by accelerometer fixed on a mechanical coupling were treated using different data processing techniques as estimating general root mean square, partial root means square, mean, variance, partial variance, kurtosis, full Fourier spectra, and partial spectra, as well as using sequential probability ratio test (SPRT). The numerical results of these methods measured on an electromotive drive train-coupling were collected into a common data set, and a search method of deviation from the normal behavior was elaborated. This selects the bad couplings if at least three of the presented qualification parameters crosses either theoretically or experimentally settled limits. It was shown that the confidence level of such classification of good and bad species was better than 95 % compared with the results of thoroughly tested ones by conventional methods.
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Manhertz, G., Gardonyi, G. & Por, G. Managing measured vibration data for malfunction detection of an assembled mechanical coupling. Int J Adv Manuf Technol 75, 693–703 (2014). https://doi.org/10.1007/s00170-014-6138-3
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DOI: https://doi.org/10.1007/s00170-014-6138-3