A NARX Model-Based Condition Monitoring Method for Rotor Systems

被引:2
作者
Gao, Yi [1 ]
Yu, Changshuai [1 ]
Zhu, Yun-Peng [2 ]
Luo, Zhong [1 ]
机构
[1] Northeastern Univ, Sch Mech Engn & Automat, Shenyang 110819, Peoples R China
[2] Queen Mary Univ London, Sch Engn & Mat Sci, London E1 4NS, England
关键词
NARX model; system identification; rotor system; condition monitoring; frequency analysis; NONLINEAR DYNAMICS; RUB-IMPACT; BEARING SYSTEM; ALGORITHM; CRACK;
D O I
10.3390/s23156878
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In this study, we developed a data-driven frequency domain analysis method for rotor systems using the NARX (Nonlinear Auto-Regressive with eXternal input) model established by system vibration signals. We propose a model-based index of fault features calculated in a multi-frequency range to facilitate condition monitoring of rotor systems. Four steps are included in the proposed method. Firstly, displacement vibration signals are collected at multiple monitored rotating speeds. Secondly, the collected signals are processed as output data and the corresponding input data is generated. Then, NARX models are developed with input and output data to characterize the rotor system. Finally, the NRSF (Nonlinear Response Spectrum Function)-based nonlinear fault index is calculated and compared to the healthy condition. An experimental application to the misaligned rotor system is also demonstrated to verify its effectiveness. Our results indicate that the value of the index directly reflects the severity of the misaligned fault.
引用
收藏
页数:13
相关论文
共 30 条
[1]  
Billings SA, 2013, NONLINEAR SYSTEM IDENTIFICATION: NARMAX METHODS IN THE TIME, FREQUENCY, AND SPATIO-TEMPORAL DOMAINS, P1, DOI 10.1002/9781118535561
[2]   Regularized orthogonal least squares algorithm for constructing radial basis function networks [J].
Chen, S ;
Chng, ES ;
Alkadhimi, K .
INTERNATIONAL JOURNAL OF CONTROL, 1996, 64 (05) :829-837
[3]   Nonlinear dynamics analysis of a dual-rotor-bearing-casing system based on a modified HB-AFT method [J].
Chen, Yi ;
Hou, Lei ;
Chen, Guo ;
Song, Huiying ;
Lin, Rongzhou ;
Jin, Yuhong ;
Chen, Yushu .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 185
[4]   Volterra-series-based nonlinear system modeling and its engineering applications: A state-of-the-art review [J].
Cheng, C. M. ;
Peng, Z. K. ;
Zhang, W. M. ;
Meng, G. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 87 :340-364
[5]   An automated methodology for performing time synchronous averaging of a gearbox signal without speed sensor [J].
Combet, F. ;
Gelman, L. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (06) :2590-2606
[6]   A novel data-driven model based parameter estimation of nonlinear systems [J].
Ge, Xiaobiao ;
Luo, Zhong ;
Ma, Ying ;
Liu, Haopeng ;
Zhu, Yunpeng .
JOURNAL OF SOUND AND VIBRATION, 2019, 453 :188-200
[7]   Nonlinear predictive model selection and model averaging using information criteria [J].
Gu, Yuanlin ;
Wei, Hua-Liang ;
Balikhin, Michael M. .
SYSTEMS SCIENCE & CONTROL ENGINEERING, 2018, 6 (01) :319-328
[8]   Nonlinear dynamics of rub-impact on a rotor-rubber bearing system with the Stribeck friction model [J].
Hua, Chunli ;
Rao, Zhushi ;
Ta, Na ;
Zhu, Zhencai .
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2015, 29 (08) :3109-3119
[9]   INPUT OUTPUT PARAMETRIC MODELS FOR NON-LINEAR SYSTEMS .1. DETERMINISTIC NON-LINEAR SYSTEMS [J].
LEONTARITIS, IJ ;
BILLINGS, SA .
INTERNATIONAL JOURNAL OF CONTROL, 1985, 41 (02) :303-328
[10]   Periodic response analysis of a misaligned rotor system by harmonic balance method with alternating frequency/time domain technique [J].
Li HongLiang ;
Chen YuShu ;
Hou Lei ;
Zhang ZhiYong .
SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2016, 59 (11) :1717-1729