PSI - Issue 16

Ihor Javorskyj et al. / Procedia Structural Integrity 16 (2019) 205–210 Ihor Javorskyj et al. / Structural Integrity Procedia 00 (2019) 000 – 000

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The establishing properties of a spectrum are the result of presence of a distributed fault in rotary units, which manifests itself in uneven radial load and also accompanied by a local fault development. 4. Conclusion The developed methods of the spectral analysis of the stochastic vibrations for unknown non-stationary period were used for ascertaining of the states of the rotary machinery. The new diagnostic indicators were formed and their efficiency for fault detection at the early stages of their initiation was shown. The characteristic peculiarities of the faults were established in frequency domain. These peculiarities manifest both in the different frequency bands, their bandwidths and spectrum forms. On the basis of worked out processing methods the software product is created and it was used in vibrodianostic system “Javir - 70” during realization of the diagnostic monitoring of the real industry units. Antoni, J., 2007. Cyclic spectral analysis of rolling element bearing signals: fact and fictions. Journal of Sound and Vibration 304 (8), 447 – 529. Antoni, J., 2009. Cyclostationarity by examples. Mechanical Systems and Signal Processing 23, 987 – 1036. Javorskyj, I., Kravets, I., Matsko, I., Yuzefovych, R., 2017. Periodically correlated random processes: Application in early diagnostics of mechanical systems. Mechanical Systems and Signal Processing 83, 406 – 438. Javorskyj, I., 2013. Mathematical models and analysis of stochastic oscillations, Lviv, pp. 804. (In Ukrainian) Javorskyj, I., Yuzefovych, R., Matsko, I., Zakrzewski, Z., Majewski, J., 2017. Coherent covariance analysis of periodically correlated random processes for unknown non-stationarity period. Digital Signal Processing 65, 27 – 51. Javorskyj, I., Yuzefovych, R., Matsko, I., Zakrzewski, Z., Majewski, J., 2018. Covariance analysis of periodically correlated random processes for unknown non-stationarity period, In Advances in Signal Processing: Reviews . Ed. Sergey Y. Yurish, International Frequency Sensor Association Publishing, Barselona, Spain, 155 – 276. References