古建筑健康监测评估系统中数据后处理数学模型的深度分析与应用  

Deep Analysis and Application of Mathematical Model of Data Post-Processing in Health Monitoring and Evaluation System of Ancient Buildings

作　　者：顾若凡 韩兵康 GU Ruo-fan;HAN Bing-kang(Tongji University College of Civil Engineering,Shanghai 200092,China)

机构地区：[1]同济大学土木工程学院,上海200092

出　　处：《工程建设与设计》2025年第3期154-157,共4页Construction & Design for Engineering

摘　　要：针对古建筑健康监测评估系统中的数据后处理问题,深入分析了当前监测数据的处理现状,并提出了一系列数学模型与方法。通过数据的归一化处理、不确定度分析与模糊隶属函数、高斯混合模型(GMM)、极值分布以及相关性分析与皮尔逊系数等方法,结果表明这些模型能够有效提升数据处理的精度和可靠性,为古建筑的结构安全评估提供了科学依据,揭示了数据间的内在联系,显著提高了监测系统的预警能力和决策支持水平。Aiming at the problem of data post-processing in the health monitoring and evaluation system of ancient buildings,this paper deeply analyzes the current situation of monitoring data processing,and puts forward a series of mathematical models and methods.Through data normalization,uncertainty analysis and fuzzy membership function,Gaussian mixture model(GMM),extreme value distribution,correlation analysis and Pearson coefficient,the results show that these models can effectively improve the accuracy and reliability of data processing,provide scientific basis for the structural safety assessment of ancient buildings,reveal the internal relationship between data,and significantly improve the early warning ability and decision support level of the monitoring system.

关 键 词：古建筑 监测系统 沉降值监测 模型分析 

分 类 号：TU317[建筑科学—结构工程] TU29