建筑结构自振周期研究概述

An overview of research on natural vibration period of building structures

建筑结构自振周期是十分重要的结构动力特性参数,准确预测建筑结构自振周期是结构动力分析和设计的重要前提。国内外学者已经提出大量的结构自振周期经验公式,其中绝大部分是将自振周期表示为结构高度或层数的函数。深度学习是典型的数据驱动模型,可以多级提取数据特征,包含多因素对建筑自振周期的影响,这为自振周期研究提供了新思路。对学者们的研究进行概述,为研究自振周期提供一定的参考和依据。

The natural vibration period of a building structure is a very important structural dynamic characteristic parameter.Accurately predicting the natural vibration period of a building structure is an important prerequisite for structural dynamic analysis and design.Scholars at home and abroad have proposed a lot of empirical formulas for the natural vibration period of structures,most of which express the natural vibration period as a function of the structure height or the number of layers.Deep learning is a typical data-driven model,which can extract data features at multiple levels,including the influence of multiple factors on the natural vibration period of buildings,which provides a new idea for the study of natural vibration periods.This paper summarizes the research of scholars,and provides some reference and basis for the study of natural vibration period.