铁道标准设计Issue(11)：84-88,107,6.DOI:10.13238/j.issn.1004-2954.2014.11.020
基于挠度的铁路双线简支钢桁梁桥杆件损伤程度识别研究
Damage Degree Identification of Railway Double-track Simply Supported Steel Truss Bridge Based on Deflection
摘要
Abstract
Using the bridge node maximum displacement change percentages as the damage degree identification indexes and the intelligent algorithm of Generalized Regression Neural Network ( GRNN) and ε-Supported Vector Regression ( ε-SVR), this paper studies the damage degree identification. Taking a railway double-track simply supported steel truss bridge as study example, the results show that:(1)GRNN model has a certain anti-noise capacity, but hasn't generalization; (2) SVR model has good anti-noise capacity and generalization; (3)When the node maximum displacement changes are taken as damage degree identification indexes, the intelligent algorithm should use ε-SVR instead of GRNN.关键词
铁路桥/钢桁梁桥/损伤程度识别/GRNN/着-SVRKey words
Railway bridge/Steel truss bridge/Damage degree identification/GRNN, ε-SVR分类
交通工程引用本文复制引用
梁滨波,任剑莹,苏木标..基于挠度的铁路双线简支钢桁梁桥杆件损伤程度识别研究[J].铁道标准设计,2014,(11):84-88,107,6.基金项目
国家自然科学基金(51278315) （51278315）
河北省自然科学基金(E2012210061) （E2012210061）
河北省教育厅基金(Z2013034) （Z2013034）
