Identification of inability states of rotating subsystems of vehicles and machines

• Autorzy: Pająk Michał , Lisjak Dragutin , Kolar Davor

Identyfikatory

DOI

10.2478/kones-2019-0014

• Języki publikacji: EN

Abstrakty

EN

One of the most important subsystems of the vehicles and machines operating currently in industry and transportation are the rotating subsystems. During the subsystems operation, due to the forcing factors influence, the technical state of them is changing and the failure can occur. In order to avoid such a situation the technical state should be identified online. To do this the analysis of the subsystems vibrations is performed. The identified technical state should be considered in a context of the ability and different inability states. Therefore, the first step of the diagnostic procedure is the ability and different inability states identification. In the article, it is proposed to accomplish this goal by the vibrations analysis in time domain. The described research started with the vibration signals acquisition using the experimental stand. In this way, the vibration signals for ability and different inability states were obtained. Afterwards, the signals were divided into learning and testing data sets. For each signal from learning data set, several characteristics were calculated, and they selected the most significant among them. Using the selected characteristics, the signals from the testing data set were analysed. Thanks to it, the testing vibrations signals were counted among the signals collected on the rotating subsystem operating in ability or selected inability state. The result of the performed studies and the accuracy of the technical state of the tested system identification can be found at the end of the article.

Słowa kluczowe

EN

rotating system; technical state; inability state; ability state; vibration signal; diagnostics; time domain analysis

• Wydawca: Łukasiewicz Research Network - Institute of Aviation ; European Science Society of Powertrain and Transport KONES Poland ; Wydawnictwo Instytutu Technicznego Wojsk Lotniczych
• Czasopismo: Journal of KONES
• Rocznik: 2019
• Tom: Vol. 26, No. 1
• Strony: 111--118
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Pająk Michał

• University of Technology and Humanities in Radom Department of Thermal Technology Stasieckiego Street 54, 26-600 Radom, Poland tel.: [phone]

autor

Lisjak Dragutin

• University of Zagreb Faculty of Mechanical Engineering and Naval Architecture Ivana Lučića Street 5, 10002 Zagreb, Croatia tel.: [phone]

autor

Kolar Davor

• University of Zagreb Faculty of Mechanical Engineering and Naval Architecture Ivana Lučića Street 5, 10002 Zagreb, Croatia tel.: [phone]

Bibliografia

• [1] Antoni, J., Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions, Journal of Sound and Vibration, Vol. 304, pp. 497-529, 2007. 117
• [2] Girtler, J., The semi-Markov model of the process of appearance of sea-going ship propulsion system ability and inability states in application to determining the reliability of these systems, Polish Maritime Research, Vol. 20, pp. 18-24, 2013.
• [3] Grządziela, A., Musiał, J., Muślewski, Ł., Pająk, M., A method for identification of non-coaxiality in engine shaft lines of a selected type of naval ships, Polish Maritime Research, Vol. 22, pp. 65-71, 2015.
• [4] Grządziela, A., Muślewski, Ł., High quality simulation of the effects of underwater detonation impact, Journal of Vibroengineering, Vol. 15, Iss. 1, pp. 106-113, 2013.
• [5] Gurr, C., Rulfs, H., Influence of transient operating conditions on propeller shaft bearings, Journal of Marine Engineering and Technology, No. 12, pp. 3-7, 2008.
• [6] Izydorczyk, J., Pionka, G., Tyma, G., Theory of Signals. Introduction 2nd Edition – Corrected and Amended, Helion, Gliwice 2006.
• [7] Kostek, R., Landowski, B., Muślewski, Ł., Simulation of rolling Bering vibration in diagnostics, Journal of Vibroengineering, Vol. 17, Iss. 8, 2015.
• [8] Lal, M., Riwari, R., Multi-fault identification in simple rotor-bearing-coupling systems based on forced response measurements, Mechanism and Machine Theory, Vol. 51, pp. 87-109, 2012.
• [9] Li, B., Mo-Yuen, C., Yodyium, T., et al., Neural-network-based motor rolling bearing fault diagnosis, IEEE Transactions on Industrial Electronics, Vol. 47 (5), pp. 1060-1069, 2000.
• [10] Molland, A. F., The Maritime Engineering Reference Book, A Guide to Ship Design, Construction and Operation, Butterworth-Heinemann, 2011.
• [11] Muślewski, Ł., Evaluation Method of Transport Systems Operation Quality, Polish Journal of Environmental Studies, Vol. 18, No. 2A, Olsztyn 2009.
• [12] Muślewski, Ł., Pająk, M., Grządziela, A., Musiał, J., Analysis of vibration time histories in the time domain for propulsion systems of minesweepers, Journal of Vibroengineering, Vol. 17, Iss. 3, pp. 1309-1316, 2015.
• [13] Qiu, H., Lee, J., Lin, J., et al., Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics, Journal of Sound and Vibration, Vol. 289, pp. 1066-1090, 2006.
• [14] Ruqiang, Y. R., Gao, R. X., Chen, X., Wavelets for fault diagnosis of rotary machines: A review with applications, Signal Processing, Vol. 96, pp. 1-15, 2014.
• [15] Szabatin, J., Signal Theory Fundamentals, WKŁ, Warszawa 2007.
• [16] Woropay, M., Landowski, B., Neubauer, A., Controlling reliability in the transport systems, B.P.E.-WIEM, Bydgoszcz – Radom 2004.
• [17] Woropay, M., Muślewski, Ł., Quality in a systemic approach, ITeE, Radom 2005.
• [18] Zieliński, T. P., Digital Processing of Signals. From theory to practice, WKŁ, Warszawa 2009.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).