东南大学学报（自然科学版）2025，Vol.55Issue(5)：1346-1355,10.DOI:10.3969/j.issn.1001-0505.2025.05.015
基于RRTO-DBSCAN算法的柔性光伏支架动力特性识别研究
Research on identifying dynamic characteristics of flexible photovoltaic brackets based on RRTO-DBSCAN algorithm
摘要
Abstract
Flexible photovoltaic(PV)support structures frequently suffer damage caused by wind-induced vibra-tions,and their mechanical mechanisms are relatively complex,necessitating in-depth research into their dynamic performance.To obtain the dynamic characteristics of a flexible PV support structure,field dynamic testing is con-ducted using ambient excitation.An improved density-based spatial clustering of applications with noise(DBSCAN)method based on the rapidly-exploring random tree-based optimizer(RRTO)is proposed in this pa-per.First,starting from the principles of stabilization diagrams,the RRTO optimization algorithm,and DBSCAN clustering,the key parameters(MinPts and Eps)of the DBSCAN algorithm are adaptively determined using the RRTO optimization algorithm combined with modal distance.Modal parameter identification of the flexible PV support structure is performed using this approach,yielding critical vibration characteristics such as natural fre-quencies,damping ratios,and mode shapes.The results demonstrate that the improved RRTO-DBSCAN cluster-ing algorithm enables automatic noise discrimination,reduces manual intervention in the analysis process,opti-mizes modal parameter identification,and enhances both the accuracy and efficiency of the analytical procedure.关键词
柔性光伏/环境激励/模态识别/RRTO算法Key words
flexible photovoltaics/environmental excitation/modal identification/rapidly-exploring random tree-based optimizer(RRTO)分类
建筑与水利引用本文复制引用
白凡,闫旭,李波,田玉基,杨娜,刘威..基于RRTO-DBSCAN算法的柔性光伏支架动力特性识别研究[J].东南大学学报（自然科学版）,2025,55(5):1346-1355,10.基金项目
中央高校基本科研业务费重点资助项目(2024JBZY017) （2024JBZY017）
结构风工程与城市风环境北京市重点实验室开放基金资助项目(2024-2) （2024-2）
国家自然科学基金面上资助项目(52478119). （52478119）
