Structural Damage Detection Based on Semi-supervised Fuzzy C-means Clustering

被引：0
|
作者：
Liu, Zhen [1 ]
Zhou, Qifeng [1 ]
Chi, Qijun [1 ]
Zhang, Yuanyuan [1 ]
Chen, Youling [1 ]
Qi, Sen [1 ]
机构：
[1] Xiamen Univ, Dept Automat, Xiamen 361005, Peoples R China
来源：
2014 PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE 2014) | 2014年
关键词：
Damage detection; Semi-supervised; Fuzzy C-means clustering; data fusion;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Structural damage detection is a key part of structural health monitoring. In recent years, intelligent detecting methods are used in this field and show good performance. This paper proposed a structural damage detection method based on data fusion and semi-supervised fuzzy C-means clustering. Compared with other intelligent method, our method can detect the damage location and extent, meanwhile, provide a confidence. Experiment results on a benchmark model show effectiveness of the proposed methods.
引用
收藏
页码：551 / 556
页数：6
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