Automatic modal parameter identification based on improved two-stage FCM algorithm

被引：2
|
作者：
He M. [1 ]
Liang P. [1 ,2 ]
Li L. [1 ]
Ye C. [1 ]
机构：
[1] School of Highway, Chang'an University, Xi'an
[2] Engeeirng Reacher Center for Large Highway Structure Safety of Ministry of Education, Chang'an University, Xi'an
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2019年 / 49卷 / 05期
关键词：
Automatic identification; Improved fuzzy c-means algorithm; Modal identification; Stabilization diagram; Uncertainty of modal parameters;
D O I：
10.3969/j.issn.1001-0505.2019.05.018
中图分类号：
学科分类号：
摘要：
An improved two-stage clustering method was proposed for automatic stabilization diagram identification. Firstly, the uncertainty of modal parameters was introduced to eliminate the false modal results. This process eliminated most of the false results to provide a clearer stabilization diagram for automatic identification. Secondly, an improved fuzzy c-means (FCM)algorithm was introduced to interpret the stabilization diagram. The algorithm identified the optimal cluster number by an iteration process. Firstly, many clustering results were obtained. Then, these different results were integrated as a judgement matrix. And an iterative graph-partitioning process was implemented to identify the desired cluster number and the final identification result. Finally, the algorithm was validated through Z24 Benchmark and a suspension bridge. The results show that the uncertainty of modal parameters discriminate the false modal parameters better than the traditional index. The proposed algorithm can successfully interpret the stabilization diagram without any user-specified parameter, thus showing strong robustness. The algorithm can be applied in automatic modal identification for bridge health monitoring. © 2019, Editorial Department of Journal of Southeast University. All right reserved.
引用
收藏
页码：940 / 948
页数：8
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