摘要
研究目的:由于受外部载荷、环境作用、灾害、人为等因素的影响,桥梁结构在服役期间会出现损伤,结构性能下降,其安全性己经引起人们的高度重视。如何去诊断桥梁结构的损伤,对其健康状况进行诊断和监测,己成为当今函待解决的一个重要课题。研究结论:针对桥梁健康监测Benchmark结构,基于加速度响应的自功率谱与主元分析法并结合马氏距离,提出结构整体损伤程度的评估方法:(1)提出的桥梁健康监测Benchmark结构损伤诊断方法可直接利用实测自功率谱进行损伤识别,不需要模态参数,不要求有完整的模态测试数据,因而避开了实际动测时一些模态参数的测不准及实测模态不完整问题;(2)损伤识别过程是通过分析实测自功率谱的数据特征、数据结构来完成的,不需建立结构的力学模型,因而对结构形式、约束方式及边界条件均没有特殊的要求;(3)采用力锤人工激励及SISO的动测方法,激励设备简单,操作方便;(4)本文方法对于在役桥梁的健康监测和损伤诊断具有一定参考价值。
Research purposes: Because the bridge structure of long - term using may be damaged by external load, environmental effect, natural calamities and human factors, its loading capability will decrease gradually, and its security has attracted more attention. Therefore, it is an imperative problem to detect bridge damages so that its security can be evaluated and monitored nowadays.Research conclusions:For the typical Benchmark structure, an assessment method by using the acceleration power spectrum and principal component analysis with the (1) The damage diagnosis method directly uses power spectrum for bridge damag of structural overall damage degree Mahalanobis distance is presented. e identification, does not need any modal parameters and integral modal data, so damage diagnosis results are not affected by modal errors and incomplete data. (2) The damage diagnosis, which is performed by analyzing data characteristics and data structure of power spectrum, does not need bridge mechanics mode, so it has not any special requirement for bridge structure types, restricting manner and boundary condition. (3) The dynamic test method using manual excitation and SISO is simple and convenient. (4) The damage diagnosis method proposed in the paper has very important theoretical and practical value for health monitoring and damage diagnosis of existing bridge
出处
《铁道工程学报》
EI
北大核心
2015年第11期80-86,共7页
Journal of Railway Engineering Society
基金
中央高校基本科研业务费(106112014CDJZR200006)
关键词
Benchmark结构
加速度响应
自功率谱
主成分分析
主元置信度准则
损伤识别
Benchmark structure
acceleration response
power spectrum
principal component analysis
principal component assurance criteria
damage identification