摘要桥梁结构的模态参数识别作为桥梁健康检测系统中的主要环节之一,参数识别的精确程度直接影响着桥梁健康评估的准确程度。因此,针对现阶段被广泛运用的确定随机子空间算法(Combined Determine-Stochastic Subspace Identification-CDSI)存在的不足-需人工参与稳定图中模态的辨识,提出了将基于密度的聚类算法(Density-Based Spatial Clustering Of Application With Noise-DBSCAN)嵌入到该识别算法中,以提高模态参数识别的效率。首先简单介绍了CDSI识别算法和DBSCAN聚类的相关原理及定义,其次详细介绍了如何将DBSCAN聚类算法有效地嵌入到CDSI算法中,以实现对稳定图中模态的智能化辨识;最后以某大型斜拉桥为识别对象,并将识别结果与MIDAS有限元软件所得结果作对比,结果表明,所提改进CDSI识别算法能够精确地识别出桥梁结构的固有频率值,且所得模态振型图与理论振型图具有很好的相似性。
Abstract:The modal parameter identification of bridge structures is one of the main items in the bridge health monitoring system. The accuracy of the parameter identification directly affects the accuracy of the bridge health evaluation. Based on the deficiencies of the Combined Determine-Stochastic Subspace Identification-CDSI, which is widely used at this stage, requires manual intervention in the Identify process of the modes in the stable graph, to solve this issue, a new method of Density-Based Spatial Clustering Of Application With Noise-DBSCAN is proposed. DBSCAN was inbuilt into the CDSI algorithm to improve the efficiency of modal parameter recognition. Firstly, it briefly introduces the relevant principles and definitions of the CDSI algorithm and DBSCAN clustering. Secondly, it introduces in detail how to effectively embed the DBSCAN clustering algorithm into the CDSI algorithm to realize the intelligent identification of the modes in the stable graph. Finally, a large cable-stayed bridge is taken as the identified objection, and then its identified results are compared with the results which are obtained by MIDAS finite element software. The results show that the improved CDSI algorithm can accurately identify the natural frequency of the bridge structure, and the obtained modal shape diagram has a commendable similarity with the theoretical shape diagram.
收稿日期: 2021-02-03
出版日期: 2022-06-15
引用本文:
单豪良1,陈永高1,孙泽阳2. 基于DBSCAN算法的改进确定-随机子空间模态参数识别算法[J]. 振动与冲击, 2022, 41(11): 156-163.
SHAN Haoliang1, CHEN Yonggao1, SUN Zeyang2. Improved CDSI algorithm based on DBSCAN algorithm. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(11): 156-163.
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