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Open AccessArticle

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

by Zhiwen Lu 1,2, Yong Lv 1,2,* and Huajiang Ouyang 3
1
The Key Laboratory of Metallurgical Equipment and Control of Education Ministry, Wuhan University of Science and Technology, Wuhan 430081, China
2
Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
3
School of Engineering, University of Liverpool, Liverpool L69 3GH, UK
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(12), 2428; https://doi.org/10.3390/app9122428
Received: 16 May 2019 / Revised: 12 June 2019 / Accepted: 12 June 2019 / Published: 14 June 2019
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. View Full-Text
Keywords: crack identification; model updating; rotor crack; kriging model; nonlinear characteristics crack identification; model updating; rotor crack; kriging model; nonlinear characteristics
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Lu, Z.; Lv, Y.; Ouyang, H. A Super-Harmonic Feature Based Updating Method for Crack Identification in Rotors Using a Kriging Surrogate Model. Appl. Sci. 2019, 9, 2428.

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