结构动载荷识别研究进展
Research progress on structural dynamic load identification
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摘要: 作用于工程结构上的动载荷由于环境等限制难以通过直接测量的方式获取,基于动响应信息间接识别或重 构动载荷已成为一种十分有效的途径。动载荷识别经过数十年的发展,已经形成了一系列行之有效的方法。本文 总结了动载荷识别方法的研究历程及主要成果,系统性阐述了典型时、频域方法以及基于函数拟合思想、正则化策 略、贝叶斯框架、数据驱动等动载荷识别方法,并讨论了各方法的优缺点以及适用范围。此外,还针对载荷识别过程 中普遍存在的结构参数不确定问题以及输入条件不确定问题进行了总结。动载荷位置识别也是动载荷识别问题的 重要组成部分,本文对现有位置识别方法进行了归纳分析。探讨了动载荷识别方法的工程应用,并分析了现有方法 的局限性。结合当前实际工程应用中日益迫切的需求及动载荷识别领域面临的问题,展望了未来动载荷识别亟需 攻克的技术难题以及可能的发展方向和重点领域。Abstract: Direct measurement of dynamic loads on engineering structures is challenging due to environmental constraints. There? fore, the indirect identification or reconstruction of dynamic loads, using dynamic response information, has emerged as a highly ef? fective method. Over decades, dynamic load identification has evolved, resulting in a series of valid solutions. This paper begins by reviewing the research history and main achievements of dynamic load identification methods. It provides a systematic exposition of typical frequency domain and time domain methods, as well as dynamic load identification methods which are based on various ap? proaches such as function fitting, regularization strategies, Bayesian frameworks, and data-driven techniques. The advantages and disadvantages ,as well as application scope of each method, are also discussed. Additionally, this paper summarizes common is? sues in the load identification process, including uncertainties in structural parameters and input conditions. Identifying the position of dynamic loads is also a crucial aspect of the dynamic load identification problem. This paper analyzes the methods currently avail? able for position identification. This paper delves into the engineering applications of dynamic load identification methods and ana? lyzes the limitations of current methods. Considering the current challenges in the field of dynamic load identification and the in? creasing demands in practical engineering applications, the paper anticipates the technical difficulties that need to be addressed. It al? so discusses potential future development directions and key areas in dynamic load identification.