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 50 条
[31]   Online Rotor Systems Condition Monitoring Using Nonlinear Output Frequency Response Functions Under Harmonic Excitations [J].
Zhu, Yun-Peng ;
Zhao, Yu-Lai ;
Lang, Z. Q. ;
Liu, Ze-Peng ;
Liu, Yang .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 18 (10) :6798-6808
[32]   Development of Sigmoidnet Based NARX Model for a Distillation Column [J].
Ramesh, K. ;
Abd Shukor, S. R. ;
Aziz, N. .
CHEMICAL PRODUCT AND PROCESS MODELING, 2008, 3 (02)
[33]   A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis [J].
Badihi, Hamed ;
Zhang, Youmin ;
Jiang, Bin ;
Pillay, Pragasen ;
Rakheja, Subhash .
PROCEEDINGS OF THE IEEE, 2022, 110 (06) :754-806
[34]   A method for maintenance decision based on condition monitoring [J].
Jiang Zhinong ;
Lai Yuehua ;
Zhang Jinjie ;
Yi Xiaojian .
2018 IEEE INTERNATIONAL CONFERENCE ON PROGNOSTICS AND HEALTH MANAGEMENT (ICPHM), 2018,
[35]   A Model-Based Monitoring Method for Offline Accelerated Testing of DC-Link Capacitor in Three-Phase Inverter Systems [J].
Zhou, Weiyang ;
Wang, Mengqi ;
Wu, Qunfang .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2021, 36 (01) :61-67
[36]   A Novel Roller Bearing Condition Monitoring Method Based on RHLCD and FVPMCD [J].
Pan, Haiyang ;
Zheng, Jinde ;
Liu, Qingyun .
IEEE ACCESS, 2019, 7 :96753-96763
[37]   Model-Based Method for Projective Clustering [J].
Chen, Lifei ;
Jiang, Qingshan ;
Wang, Shengrui .
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2012, 24 (07) :1291-1305
[38]   Research on Rotor Condition Monitoring based on D-S Evidence Theory [J].
Chen, Yuanchao ;
Wen, Guangrui ;
Dong, Xiaoni ;
Zhang, Zhifen .
2016 13TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2016, :848-853
[39]   Model-based condition monitoring of PEM fuel cell using Hotelling T2 control limit [J].
Xue, X. ;
Tang, J. ;
Sammes, N. ;
Ding, Y. .
JOURNAL OF POWER SOURCES, 2006, 162 (01) :388-399
[40]   Balancing method without trial weights for rotor systems based on similitude scale model [J].
Ruiduo Ye ;
Liping Wang ;
Xiaojie Hou ;
Zhong Luo ;
Qingkai Han .
Frontiers of Mechanical Engineering, 2018, 13 :571-580