Damage Identification Method for Irregular Continuous Box Girder Bridge Based on RBF Neural Network Optimized by PSO

Abstract:

A damage identification method suitable for the characteristics of the irregular continuous box girder bridge is presented. The damage index structured by the ratio of mode shape and relative change in strain mode is represented as input data to identify the structure damage by means of PSO-RBF neural network. Finally, the numerical simulation calculation for the damage identification of an irregular continuous box girder bridge with the length of 4×30 meters verifies the feasibility and validity of the proposed method.

• Periodical: Applied Mechanics and Materials (Volume 470)
• Pages: 1034-1038
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.470.1034
• Online since: December 2013
• Authors: Han Bing Liu, Ping Yi Sun, Guo Jin Tan*, Yan Hua Wang
• Keywords: Damage Identification, Irregular Continuous Box Girder Bridge, PSO, RSF Neural Network, Strain Mode

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