Substructural Damage Identification of Stone Arch Bridge Based on Probabilistic Neural Network

Feng Qi Guo; Zhi Wu Yu

doi:10.4028/www.scientific.net/AMM.178-181.2433

Paper Titles

About the Structural Robustness of Through Arch Bridges
p.2412

Comparative Study on Seismic Performance of Prestressed Concrete Box-Girder Bridges with Corrugated Steel Webs
p.2418

Comparative Study on the Vertical Dynamic Responses of Simply Supported Beam Subjected to Two Typical Vehicle Models
p.2424

Automatic Identification of Fundamental Frequency for Tied Arch Bridge Suspender Tension Monitoring
p.2429

Substructural Damage Identification of Stone Arch Bridge Based on Probabilistic Neural Network
p.2433

Research on Alignment Error of Cable-Stayed Bridge Based on Stream of Variation
p.2439

Based on ANSYS the Application of Virtual Crack Close Technique in the Calculation of Strain Energy Release Rate in Interface Crack
p.2444

Solar Radiation-Induced Temperature Variation of Concrete Bridge Piers
p.2451

Spatial Analysis of Vehicle-Bridge Coupled Vibration Response between Curved Continuous Rigid-Frame Bridge and Motor Vehicle
p.2456

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 178-181Substructural Damage Identification of Stone Arch...

Substructural Damage Identification of Stone Arch Bridge Based on Probabilistic Neural Network

Abstract:

Stone arch bridge was divided into three substructures. They were main arch, vertical wall and vice arch or carriageway board. Probabilistic neural network was applied to substructural damage identification. Static displacement and low-order frequencies were taken as input parameters of the network training. A numerical model was developed to simulate the process of substructural damage identification of stone arch bridge. The effects of noise data to training and recognition were researched. The results show that it is feasible and effective to use probabilistic neural network in substructural damage identification of stone arch bridge.