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Appl. Sci. 2017, 7(9), 911;

The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems

School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China
Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education, Northeastern University, Shenyang 110819, China
Department of Automatic Control and System Engineering, University of Sheffield, Sheffield S13JD, UK
Author to whom correspondence should be addressed.
Received: 19 July 2017 / Revised: 11 August 2017 / Accepted: 26 August 2017 / Published: 5 September 2017
(This article belongs to the Section Mechanical Engineering)
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In practice, it is usually difficult to obtain the physical model of nonlinear, rotor-bearing systems due to uncertain nonlinearities. In order to solve this issue to conduct the analysis and design of nonlinear, rotor-bearing systems, in this study, a data driven NARX (Nonlinear Auto-Regressive with exogenous inputs) model is identified. Due to the lack of the random input signal which is required in the identification of a system′s NARX model, for nonlinear, rotor-bearing systems, a new multi-harmonic input based model identification approach is introduced. Moreover, the identification results of NARX models on the nonlinear, rotor-bearing systems are validated under different conditions (such as: low speed, critical speed, and over critical speed), illustrating the applicability of the proposed approach. Finally, an experimental test is conducted to identify the NARX model of the nonlinear rotor test rig, showing that the NARX model can be used to reproduce the characteristics of the underlying system accurately, which provides a reliable model for dynamic analysis, control, and fault diagnosis of the nonlinear, rotor-bearing system. View Full-Text
Keywords: NARX model; nonlinear, rotor-bearing systems; system identification; multi-harmonic excitation NARX model; nonlinear, rotor-bearing systems; system identification; multi-harmonic excitation

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Ma, Y.; Liu, H.; Zhu, Y.; Wang, F.; Luo, Z. The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems. Appl. Sci. 2017, 7, 911.

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