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Zang, Tingpeng (Zang, Tingpeng.) | Wang, Fengren (Wang, Fengren.) | Wen, Guangrui (Wen, Guangrui.) | Zhang, Zhifen (Zhang, Zhifen.)

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Aiming at deficiency in identifying modal parameters of a high speed rotor system using modeling approach, a new method for modal parameters recognition of a rotor system based on the empirical mode decomposition (EMD) and the stochastic subspace identification (SSI) was proposed here. Free damped response components of the rotor system's various modes were obtained with the narrow band-pass filtering algorithm from the rotor system's vibration responses under operation condition, and then EMD was used to decompose the processed signals and decrease the effects of mode mixing and other signal components. The random state model matrix of the rotor system was derived from a Hankel matrix constructed after using EMD with the singular value decomposition (SVD) and Kalman state filtering. The first and second order modal frequencies of the rotor system were identified with eigenvalue decomposition of the random state model matrix. The effectiveness of the proposed method was verified with simulation analysis and actual tests on a rotor system rig. © 2018, Editorial Office of Journal of Vibration and Shock. All right reserved.


Eigenvalue decomposition Empirical Mode Decomposition Identification techniques Modal parameters Operation conditions Rotor systems Simulation analysis Stochastic subspace identification

Author Community:

  • [ 1 ] [Zang, Tingpeng;Wang, Fengren;Wen, Guangrui;Zhang, Zhifen]The Research Institute of Diagnosis and Cybernetics, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an; 710049, China
  • [ 2 ] [Wen, Guangrui]School of Mechanical Engineering, Xinjiang University, Wulumuqi; 830047, China

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Zhendong yu Chongji/Journal of Vibration and Shock

ISSN: 1000-3835

Year: 2018

Issue: 5

Volume: 37

Page: 120-125

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 20

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