Model-based method with nonlinear ultrasonic system identification for mechanical structural health assessment

被引:59
作者
Chen, Hanxin [1 ,2 ]
Huang, Lang [1 ]
Yang, Liu [1 ]
Chen, Yongting [3 ]
Huang, Jinmin [1 ]
机构
[1] Wuhan Inst Technol, Sch Mech & Elect Engn, Wuhan 430073, Peoples R China
[2] Hubei Prov Key Lab Chem Equipment Intensificat &, Wuhan, Peoples R China
[3] Wuhan Britain China Sch, Wuhan, Peoples R China
基金
英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词
PULSED EDDY-CURRENT; REGRESSION; ALGORITHM; QUANTIFICATION; SELECTION;
D O I
10.1002/ett.3955
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Conventional methods for the structural nondestructive testing (NDT) such as pulsed eddy current (PEC), ultrasonic detection (UT), and so on are based on the output signal interpretation technique of the NDT system to extract the features to assess the structural health. In this article, a novel NDT method for the structural health monitoring from the different perspective is proposed, which is based on the structural system model between the exciting input and output response. Nonlinear autoregressive moving average with exogenous inputs (NARMAX) is used to establish the time domain model between the input signal and the output response. Frequency response (FRF) of NARMAX model from the time domain data is proposed to obtain the indicators to assess the structural health. The effectiveness and advantage of the proposed method are tested with two sets of experimental data by comparison with the existing method.
引用
收藏
页数:15
相关论文
共 28 条
[1]   A new class of wavelet networks for nonlinear system identification [J].
Billings, SA ;
Wei, HL .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2005, 16 (04) :862-874
[2]   IDENTIFICATION OF MIMO NON-LINEAR SYSTEMS USING A FORWARD-REGRESSION ORTHOGONAL ESTIMATOR [J].
BILLINGS, SA ;
CHEN, S ;
KORENBERG, MJ .
INTERNATIONAL JOURNAL OF CONTROL, 1989, 49 (06) :2157-2189
[3]  
Billings SA, 1998, CONTROL AND DYNAMIC SYSTEMS, P231
[4]   IDENTIFICATION OF NON-LINEAR OUTPUT-AFFINE SYSTEMS USING AN ORTHOGONAL LEAST-SQUARES ALGORITHM [J].
BILLINGS, SA ;
KORENBERG, MJ ;
CHEN, S .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1988, 19 (08) :1559-1568
[5]   Sparse model identification using a forward orthogonal regression algorithm aided by mutual information [J].
Billings, Stephen A. ;
Wei, Hua-Liang .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2007, 18 (01) :306-310
[6]   Particle Swarm Optimization Algorithm with Mutation Operator for Particle Filter Noise Reduction in Mechanical Fault Diagnosis [J].
Chen, Hanxin ;
Fan, Dong Liang ;
Fang, Lu ;
Huang, Wenjian ;
Huang, Jinmin ;
Cao, Chenghao ;
Yang, Liu ;
He, Yibin ;
Zeng, Li .
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2020, 34 (10)
[7]   Finite Element Analysis Model on Ultrasonic Phased Array Technique for Material Defect Time of Flight Diffraction Detection [J].
Chen, Hanxin ;
Fan, Dongliang ;
Huang, Jinmin ;
Huang, Wenjian ;
Zhang, Guangyu ;
Huang, Lang .
SCIENCE OF ADVANCED MATERIALS, 2020, 12 (05) :665-675
[8]   Multiple fault condition recognition of gearbox with sequential hypothesis test [J].
Chen, Hanxin ;
Shang, Yunfei ;
Sun, Kui .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 40 (02) :469-482
[9]  
Chen HX, 2013, SHOCK VIB, V20, P247, DOI [10.1155/2013/598490, 10.3233/SAV-2012-00741]
[10]   A novel organic/inorganic composite solid electrolyte with functionalized layers for improved room-temperature rate performance of solid-state lithium battery [J].
Chen, Hao ;
Jing, Mao-xiang ;
Han, Chong ;
Yang, Hua ;
Hua, Song ;
Chen, Fei ;
Chen, Li-Li ;
Zhou, Zu-xu ;
Ju, Bo-wei ;
Tu, Fei-yue ;
Shen, Xiang-qian ;
Qin, Shi-biao .
INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2019, 43 (11) :5912-5921