东南大学学报（自然科学版）2017，Vol.47Issue(4)：710-716,7.DOI:10.3969/j.issn.1001-0505.2017.04.014
基于图论聚类的随机子空间模态参数自动识别
Automatic stochastic subspace identification of modal parameters based on graph clustering
摘要
Abstract
In order to improve the degree of automation in the process of modal parameter identification for bridge structures based on the stochastic subspace identification method, and reduce human intervention, an automatic modal parameter identification method based on graph clustering for bridge structure is proposed.First, some methods are adopted to initially weed out the false modes caused by the data accuracy, noise and so on.Secondly, the graph clustering theory is used to identify the structural modal parameters according to the distances defined by structural frequency and modal assurance criterion (MAC) index, respectively, so as to finish the automatic modal parameters identification.The automation modal parameters identification of the structure is realized by the proposed method based on 0.5 h acceleration data of Guanhe bridge, and the identification results are verified by the corresponding finite element model.Then, the proposed method is used to identify the modal parameters of Guanhe bridge based on one-year acceleration data from its structural health monitoring system, which indicates that the method is feasible for the modal parameter automatic identification of the bridge structure with massive acceleration data.关键词
模态参数识别/图论聚类/随机子空间法/稳定图Key words
modal parameter identification/graph-based cluster/stochastic subspace identification method/stabilization diagram分类
通用工业技术引用本文复制引用
郑沛娟,林迪南,宗周红,余道兴..基于图论聚类的随机子空间模态参数自动识别[J].东南大学学报（自然科学版）,2017,47(4):710-716,7.基金项目
国家自然科学基金资助项目(51378112)、江苏高校优势学科建设工程资助项目. （51378112）
