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A Benchmark Problem for Comparison of Vibration-Based Crack Identification Methods

Bing Li1,2, Zhengjia He1

State Key Laboratory for Manufacturing System, Xi’an Jiaotong University, Xi’an 710072, China.
Corresponding author.
Tel.: +86-29-82663689; Fax: +86-29-82663689; Email: bli@mail.xjtu.edu.cn (B. Li)

Computer Modeling in Engineering & Sciences 2013, 93(4), 293-316. https://doi.org/10.3970/cmes.2013.093.293

Abstract

The vibration-based crack identification problem insists of finding a measured vibration parameter from a complete crack-detection-database constructed by numerical simulation. It is one of the classical optimization problems. Many intelligence methods, such as neural network (NN), genetic algorithm (GA), determinant transformation (DT), and frequency contour (FC) etc., have been extensively employed as optimization tools to achieve this task. The aim of this paper is to propose a benchmark problem to compare these extensive-used optimization methods in terms of crack identification precision and computational time. The merit and demerits for each method are discussed. The results suggest that FC is a visualized, stable and easily applied method for detecting crack in practice. The conclusions of current studies are useful to investigators in deciding which method should be chosen in their crack inspections.

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Cite This Article

APA Style
Li, B., He, Z. (2013). A benchmark problem for comparison of vibration-based crack identification methods. Computer Modeling in Engineering & Sciences, 93(4), 293-316. https://doi.org/10.3970/cmes.2013.093.293
Vancouver Style
Li B, He Z. A benchmark problem for comparison of vibration-based crack identification methods. Comput Model Eng Sci. 2013;93(4):293-316 https://doi.org/10.3970/cmes.2013.093.293
IEEE Style
B. Li and Z. He, “A Benchmark Problem for Comparison of Vibration-Based Crack Identification Methods,” Comput. Model. Eng. Sci., vol. 93, no. 4, pp. 293-316, 2013. https://doi.org/10.3970/cmes.2013.093.293



cc Copyright © 2013 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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