Backward-Auto-Regressive Model Based Rotor-Bearing System Stability Prediction


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This paper focus on rotor-bearing system parameter identification with impulse excitation in horizon and vertical which is based on Backward -auto-regressive model. Singular value decomposition is applied to reduce the noise and the proper AR model order and de-noising threshold are selected. In this paper, the damping ratio is identified within the different rotating speed and different impulse excitation, and the error is calculated within the different noise level and different AR model order when compared with the ideal model. Though the theoretical analysis, simulation analysis and experimental research, We can indicate that the BAR model has a good performance in system identification and elimination of false modal.



Edited by:

Qingkai Han, Kazuhiko Takahashi, Chang-Hyun Oh and Zhong Luo




J. L. Yang et al., "Backward-Auto-Regressive Model Based Rotor-Bearing System Stability Prediction", Advanced Engineering Forum, Vols. 2-3, pp. 683-687, 2012

Online since:

December 2011


[1] Ping Zhong, Rotor Bearing System Identification Using Time Domain Methods. PhD thesis, University of Virginia, (1997).

[2] R. Douglas Martin, Victor J. Yohai. Robustness in Time Sequence and Estimating ARMA Models, University pf Washington, (1984).

[3] Aydin Kizilkaya, Ahmet H. Kayran, ARMA model parameter estimation based on the equivalent MA approach ,J. Digital Signal Processing 16(2006) 670-681.


[4] Palle Andersen. Identification of Civil Engineering Structures using Vector ARMA Models,J. Aalborg University, (1997).

[5] Ralf Christ, Josef Steinebach. Estimating the Adjustment Coefficient in an ARMA(p, q) Risk Model, J. Mathematics and Economics 17(1995)149-161.


[6] Qi-jiang Song, Han-Fu Chen. Identification of errors-in-variables systems with ARMA observation noises,J. System and Control Letters 57(2008) 420-424.


[7] Mark S. Voss, Xin Feng. ARMA Model Selection Using Particle Swarm Optimization and AIC Criteria,J. Marquette University, Milwaukee Wisconsin, (2002).


[8] Serena Ng, Pierre Perron. Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of Truncation Lag,J. Journal of the American Statistical Association, Volume 90, Issue 429(1995), 268-281.


[9] T. Patrik Nordberg, Ivar Gustafsson, Using QR factorization and SVD to solve input estimation problems in structural dynamics,J. Comput. Methods Appl. Mech. Engrg. 195(2006) 5891-5908.


[10] Charles Hunter Cloud, Stability of Rotors Supported by Tilting Pad Journal Bearings, D. University of Virginia, (2007).

[11] Tangbaoping, Jiangyonghua, Zhangxiangchun. The Method of Fault Feature Extracting Based on Singular Value Decomposition and Empirical Mode Decomposition Sliding Bearing, J. Chongqing University, China General Aviation Technology Institute, (2010).

[12] Yangshuzi, Wuya, Xuanjianping. Time Sequence Analysis of the Engineering Applications ,M. Huazhong Technology University press, (2007).

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