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Complexity
Volume 2018, Article ID 7356189, 9 pages
https://doi.org/10.1155/2018/7356189
Research Article

Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model

1The State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan 430081, China
2Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Wuhan 430081, China
3Ministry of Education, Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
4National Demonstration Center for Experimental Machinery Education, Wuhan University of Science and Technology, Wuhan 430081, China
5Smart Materials and Structures Laboratory, Department of Mechanical Engineering, University of Houston, Houston, TX 77204, USA

Correspondence should be addressed to Gangbing Song; ude.hu@gnosg

Received 11 August 2017; Accepted 3 January 2018; Published 31 January 2018

Academic Editor: Michele Scarpiniti

Copyright © 2018 Changming Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Changming Liu, Di Zhou, Zhigang Wang, Dan Yang, and Gangbing Song, “Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model,” Complexity, vol. 2018, Article ID 7356189, 9 pages, 2018. https://doi.org/10.1155/2018/7356189.