基于改进PCA-K均值聚类-特征值分析法的桁架式拱梁组合体系性能评估  

Performance Evaluation of Arch-Truss Girder Combination Bridge Based on Improved PCA-K-Means Cluster-Eigenvalue Analysis Algorithm

作　　者：王亮 刘磊 张伟 陈晓杰 桂成中 程雨 WANG Liang;LIU Lei;ZHANG Wei;CHEN Xiaojie;GUI Chengzhong;CHENG Yu(China Energy Construction Highway Group Co.,Ltd.,Beijing 100038,China;China Energy Construction(Guangdong)Zhongkai Expressway Co.,Ltd.,Jiangmen,Guangdong 529142,China;Department of Civil Engineering,Institute of Disaster Prevention,Sanhe,Hebei 065201,China;Beijing Disaster Prevention Science and Technology Co.,Ltd.,Mechanism and Disaster Prevention,CEA,Sanhe,Hebei 065201,China;CHECC Highway Maintenance and Inspection Technology Co.,Ltd.,Beijing 100097,China)

机构地区：[1]中电建路桥集团有限公司,北京100038 [2]中电建(广东)中开高速公路有限公司,广东江门529142 [3]防灾科技学院,土木工程学院,河北三河065201 [4]北京防灾科技有限公司,河北三河065201 [5]中咨公路养护检测技术有限公司,北京100097

出　　处：《河北工程大学学报(自然科学版)》2025年第1期9-17,共9页Journal of Hebei University of Engineering:Natural Science Edition

基　　金：中国地震局地震科技星火计划项目(XH24063A)。

摘　　要：提出一种基于改进PCA-K均值聚类-特征值分析法的双层桥面桁架式拱梁组合体系桥梁性能评估算法,并应用于基于安全监测的双层桥面桁架式拱梁组合体系中的吊杆体系养护阶段性能评估。该算法主要包括监测数据采集、多源异构数据预处理、关键因子确定、改进K均值聚类分析、目标阈值确定和基于特征值分析的性能评估等内容。通过收集桥梁性能监测数据,并对这些数据进行清洗,接着采用三次样条插值法对多源异构数据进行预处理。基于主成分分析法确定关键因子,并基于改进K均值聚类方法将性能参数数据分为三类。然后,基于有限元计算结果确定测点位置所对应的测点力学性能状态的目标阈值,通过将提取的均值与方差等特征值与目标阈值进行比较来评估桥梁性能状态。通过实例验证方法,并提出实际应用和未来研究方向的建议。研究表明,改进后K均值聚类方法与原始数据更接近,且相关系数最高,能够提高聚类分析的准确性和可靠性,基于改进PCA-K均值聚类-特征值分析法能够评估桥梁结构性能状态。This integrated study aims to provide a novel performance evaluation algorithm for doublelayer arch-truss girder composite bridges based on an improved PCA-K-means-feature analysis method,and to apply it to the performance evaluation of cable-stayed systems in the maintenance phase based on safety monitoring.This algorithm mainly includes monitoring data collection,pre-processing of heterogeneous data from multiple sources,determination of key factors,improvement of K-means cluster analysis,determination of target thresholds,and performance evaluation based on eigenvalue analysis.By collecting bridge performance monitoring data,cleaning these data,and then using the cubic spline interpolation method to preprocess multi-source heterogeneous data.Determine key factors based on prin-cipal component analysis and classify performance parameter data into three categories using an im-proved K-means cluster method.Then,based on the finite element calculation results,the target threshold for the mechanical performance state of the measurement point corresponding to the measure-ment point position is determined.The performance state of the bridge is evaluated by comparing the ex-tracted feature values such as mean and variance with the target threshold.Validate the method through examples and provide suggestions for practical applications and future research directions.Research has shown that the improved K-means cluster method can improve the accuracy and reliability of clustering analysis.Based on the improved PCA-K means cluster feature analysis method,the performance status of bridge structures can be evaluated.

关 键 词：拱梁组合体系 目标阈值 主成分分析法 K均值聚类法 性能评估 数据预处理 

分 类 号：U448[建筑科学—桥梁与隧道工程]