A Novel Method for the Dynamic Coefficients Identification of Journal Bearings using Kalman Filter

Yang Kang, Zhanqun Shi, Hao Zhang, Dong Zhen, Fengshou Gu

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


The dynamic coefficients identification of journal bearings is essential for instability analysis of rotation machinery. Aiming at the measured displacement of a single location, an improvement method associated with the Kalman filter is proposed to estimate the bearing dynamic coefficients. Firstly, a finite element model of the flexible rotor-bearing system was established and then modified by the modal test. Secondly, the model-based identification procedure was derived, in which the displacements of the shaft at bearings locations were estimated by the Kalman filter algorithm to identify the dynamic coefficients. Finally, considering the effect of the different process noise covariance, the corresponding numerical simulations were carried out to validate the preliminary accuracy. Furthermore, experimental tests were conducted to confirm the practicality, where the real stiffness and damping were comprehensively identified under the different operating conditions. The results show that the proposed method is not only highly accurate, but also stable under different measured locations. Compared with the conventional method, this study presents a more than high practicality approach to identify dynamic coefficients, including under the resonance condition. With high efficiency, it can be extended to predict the dynamic behaviour of rotor-bearing systems.

Original languageEnglish
Article number565
Number of pages17
JournalSensors (Switzerland)
Issue number2
Publication statusPublished - 20 Jan 2020


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