首页|Automatic identification of structural modal parameters based on density peaks clustering algorithm

Automatic identification of structural modal parameters based on density peaks clustering algorithm

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  • NETL
  • NSTL
  • Wiley
Estimating modal parameters requires significant user interaction, especiallywhen parametric system identification methods are used and the physicalmodes are selected in the stabilization diagram. In this paper, a fast densitypeaks clustering algorithm combined with the covariance-driven stochasticsubspace identification method is used to automatically identify modal parameters.Before the automatic identification process, the spurious modes from thestochastic subspace identification method were eliminated by a two-stagemethod, including using the soft and hard verification criteria to remove spuriousmodes in the first stage and the removal of spurious modes based on thestability of physical modes in the second stage; thus, a better stabilization diagramwas obtained for the subsequent automatic identification. Furthermore,fast density peaks clustering algorithm was applied to select the appropriatestructure modes from the stabilization diagram. In the entire identificationprocess, no user participation was required. The proposed method was demonstratedon a 4-degree of freedom (DOF) numerical model and a benchmarkframe structure, and the results indicated that the modal parameters can beidentified accurately even with the noise effects using the default user-definedparameters. This method showed higher efficiency and universality than theexisting methods. Finally, the applicability and robustness of the proposedmethod in automated operational mode tracking were verified on a real cablestayedbridge.

automatic identificationdensity clusteringmodal parametersmode trackingstochastic subspace identification

Xiulin Zhang、Wensong Zhou、Yong Huang、Hui Li

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Key Lab of Smart Prevention andMitigation of Civil Engineering Disastersof the Ministry of Industry andInformation Technology, Harbin Instituteof Technology, Harbin, China,Key Lab of Structures Dynamic Behaviorand Control of the Ministry of Education,Harbin Institute of Technology, Harbin,China,School of Civil Engineering, HarbinInstitute of Technology, Harbin, China

2022

10.1002/stc.3138

Structural control and health monitoring

Structural control and health monitoring

EI
ISSN：1545-2255
年,卷(期)：2022.29(12)
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