在施结构健康监测数据解耦及处理方法研究

Study on Decoupling and Processing Methods of Structural Health Monitoring Data in Construction

在施结构健康监测数据受周围环境周期性变化及随机性因素的影响,施工加载引起的力学状态变化难以直接观测。基于经验模态分解方法,提出了数据解耦及处理方法,通过构造序列对数据进行多级解耦,滤除原始数据中周期性变化和随机性因素,得到能够体现施工加载的趋势变化部分。通过对某大跨度结构工程案例的研究应用,对健康监测数据进行解耦处理,验证方法的适用性。

Structural health monitoring data during construction are affected by periodic environmental changes and random factors,making it difficult to directly observe mechanical state changes induced by construction loading.Based on the empirical mode decomposition method,a data decoupling and processing method is proposed.By constructing sequences to decouple the data at multiple levels,periodic changes and random factors in the original data are filtered out,resulting in a trend component that reflects construction loading.The applicability of the method is verified through the decoupling and analysis of health monitoring data from a large-span structural engineering case.