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Detection and quantification of oil whirl instability in a rotor-journal bearing system using a novel dynamic recurrence index

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Abstract

This paper presents a new Dynamic Recurrence Index (DRI) to detect the occurrence and quantify the evolution of oil whirl instability in the rotor-journal bearing system by measuring the dynamical similarity between the normal working condition and unstable operating states of the system. In this method, two signals, one normal operating condition signal as the reference signal and one unstable operating condition signal, are reconstructed into the same phase space before the Cross-Recurrence Plots (CRP) are prepared. Then, the structure of these CRPs is analyzed by applying the Cross-Recurrence Quantification Analysis (CRQA) to estimate the dynamical difference between the normal operating condition and unstable operating states of the rotor-journal bearing system. Finally, those CRQA variables are mapped by Support Vector Data Description (SVDD) into a dynamic recurrence index to monitor the evolution and evaluate the severity degree of the oil whirl instability. The simulation and experimental results show that the CRQA variables and DRI are sensitive to the occurrence of oil whirl instability, and the proposed method is a practical approach to monitoring the oil whirl instability for the rotor-journal bearing system.

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Data availability

The simulation and experimental datasets analyzed during the current work are available in the OneDrive repository, [https://1drv.ms/u/s!AtNlnPMcJW38p0W-Kg6v-hnL0tU4?e=siuegP].

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Acknowledgements

This work is supported by the project from the National Natural Science Foundation of China (No. 52175077).

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Authors and Affiliations

  1. The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400044, People’s Republic of China

    Honglin Luo & Lin Bo

  2. National Engineering Laboratory for High-Speed Train, CRRC QINGDAO SIFANG CO., LTD, Qingdao, 266000, People’s Republic of China

    Chang Peng

  3. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, 100044, People’s Republic of China

    Dongming Hou

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  1. Honglin Luo
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  2. Lin Bo
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  3. Chang Peng
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  4. Dongming Hou
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Correspondence to Lin Bo.

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Luo, H., Bo, L., Peng, C. et al. Detection and quantification of oil whirl instability in a rotor-journal bearing system using a novel dynamic recurrence index. Nonlinear Dyn 111, 2229–2261 (2023). https://doi.org/10.1007/s11071-022-07932-3

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  • DOI: https://doi.org/10.1007/s11071-022-07932-3

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