A Super-Harmonic Feature Based Updating Method for Crack Identification in Rotors Using a Kriging Surrogate Model

被引:17
作者
Lu, Zhiwen [1 ,2 ]
Lv, Yong [1 ,2 ]
Ouyang, Huajiang [3 ]
机构
[1] Wuhan Univ Sci & Technol, Educ Minist, Key Lab Met Equipment & Control, Wuhan 430081, Hubei, Peoples R China
[2] Wuhan Univ Sci & Technol, Hubei Key Lab Mech Transmiss & Mfg Engn, Wuhan 430081, Hubei, Peoples R China
[3] Univ Liverpool, Sch Engn, Liverpool L69 3GH, Merseyside, England
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 12期
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
crack identification; model updating; rotor crack; kriging model; nonlinear characteristics; PARAMETER-IDENTIFICATION; NEURAL-NETWORKS; SHAFTS; VIBRATIONS; SYSTEMS;
D O I
10.3390/app9122428
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Dynamic model updating based on finite element method (FEM) has been widely investigated for structural damage identification, especially for static structures. Despite the substantial advances in this method, the key issue still needs to be addressed to boost its efficiency in practical applications. This paper introduces the updating idea into crack identification for rotating rotors, which has been rarely addressed in the literature. To address the problem, a novel Kriging surrogate model-based FEM updating method is proposed for the breathing crack identification of rotors by using the super-harmonic nonlinear characteristics. In this method, the breathing crack induced nonlinear characteristics from two locations of the rotors are harnessed instead of the traditional linear damage features for more sensitive and accurate breathing crack identification. Moreover, a FEM of a two-disc rotor-bearing system with a response-dependent breathing crack is established, which is partly validated by experiments. In addition, the associated breathing crack induced nonlinear characteristics are investigated and used to construct the objective function of Kriging surrogate model. Finally, the feasibility and the effectiveness of the proposed method are verified by numerical experiments with Gaussian white noise contamination. Results demonstrate that the proposed method is effective, accurate, and robust for breathing crack identification in rotors and is promising for practical engineering applications.
引用
收藏
页数:19
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