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http://dx.doi.org/10.12989/sss.2018.22.6.699

Health monitoring of pedestrian truss bridges using cone-shaped kernel distribution  

Ahmadi, Hamid Reza (Department of Civil Engineering, Faculty of Engineering, University of Maragheh)
Anvari, Diana (Department of Civil Engineering, Bandar Abbas Branch, Islamic Azad University)
Publication Information
Smart Structures and Systems / v.22, no.6, 2018 , pp. 699-709 More about this Journal
Abstract
With increasing traffic volumes and rising vehicle traffic, especially in cities, the number of pedestrian bridges has also increased significantly. Like all other structures, pedestrian bridges also suffer damage. In order to increase the safety of pedestrians, it is necessary to identify existing damage and to repair them to ensure the safety of the bridge structures. Owing to the shortcomings of local methods in identifying damage and in order to enhance the reliability of detection and identification of structural faults, signal methods have seen significant development in recent years. In this research, a new methodology, based on cone-shaped kernel distribution with a new damage index, has been used for damage detection in pedestrian truss bridges. To evaluate the proposed method, the numerical models of the Warren Type steel truss and the Arregar steel footbridge were used. Based on the results, the proposed method and damage index identified the damage and determined its location with a high degree of precision. Given the ease of use, the proposed method can be used to identify faults in pedestrian bridges.
Keywords
pedestrian truss bridges; damage detection; cone-shaped kernel distribution; time-frequency distribution;
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