Identification and Damage Detection of Trusses Using Digital Processing of Vibration Signatures

Abstract:

Knowledge of the economic and social effects of aging, deterioration and extreme events on civil infrastructure have been accompanied by recognition of the need for advanced structural health monitoring and damage detection tools. In this paper the time-delay neural networks (TDNNs) have been implemented in detecting the damage in bridge structure using vibration signature analysis. A simulation study has been carried out for the incomplete measurement data. It has been observed that TDNNs have performed better than traditional neural networks in this application and the arithmetic of the TDNNs is simple.

• Periodical: Advanced Materials Research (Volumes 255-260)
• Pages: 659-663
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.255-260.659
• Online since: May 2011
• Authors: Lin Niu, Liao Yuan Ye
• Keywords: Bridge Truss, Damage Detection, Structural Health Monitoring (SHM), Time-Delay Neural Networks, Vibration Signature Analysis

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