摘要
近海结构服役环境恶劣,长期受到风浪流等复杂荷载作用,关键结构部件易受损,对其进行局部、早期损伤识别与定位有重要意义。由于动力信号采集技术的发展、损伤监测实时性的要求,基于动力响应的损伤识别方法已成为研究热点。目前对于结构损伤识别有两种不同的思路:基于模态及其衍生的动力指纹的参数化损伤识别方法以及利用时间序列特征、信号能量相关性等非典型参数方法。由于近海结构外部激励的复杂性,非典型参数方法逐渐成为动力响应损伤识别中最具应用前景的方法,文章对现有基于非典型参数方法的近海结构损伤识别体系进行系统梳理,比较了各种方法的优缺点,总结了目前非典型参数损伤识别方法面临的挑战,展望动力响应损伤识别的发展前景,为动力响应损伤识别在实际工程的应用提供参考。
Offshore structures are subjected to severe service environment and complex loads such as wind,wave and current for a long time,and the key structural components are easy to be damaged,so it is important to identify and locate the local and early damage.Due to the development of dynamic signal acquisition technology and the requirement of real-time damage monitoring,the damage identification method based on dynamic response has become a research hotspot.At present,there are two different approaches to structural damage identification:parametric damage identification based on the mode and its derived dynamic fingerprint,and atypical parametric methods using time series features and signal energy correlation.Due to the complexity of external excitation of offshore structures,the atypical parameter method has gradually become the most promising method for dynamic response damage identification.This paper systematically reviewed the existing atypical parameter methods for structural damage identification in offshore structures.It compared the advantages and disadvantages of various methods,summarized the challenges faced by atypical parameter,looked ahead to the development prospects of dynamic response damage identification,and provided reference for the practical application of dynamic response damage identification in engineering.
作者
胡艳
王启明
李成明
HU Yan;WANG Qiming;LI Chengming(School of Mathematics,Hohai University,Nanjing 211100,China)
出处
《水道港口》
2024年第3期357-366,共10页
Journal of Waterway and Harbor
基金
国家自然科学基金项目(51709093)
国家重点研发计划项目(2022YFB3207400)
江苏省研究生科研与实践创新计划项目(422003263)。
关键词
近海结构
动力响应
结构损伤识别
信号分解
非典型参数识别方法
offshore structure
dynamic response
structural damage identification
decomposition of signal
atypical parameter identification
