Damage identification of concrete arch beam utilising residual frequency response function

Southern Cross university
Publication Type:
Conference Proceeding
Proceedings of the 23rd Australasian Conference on the Mechanics of Structures and Materials, 2014, pp. 1209 - 1214
Issue Date:
Full metadata record
One of the critical missions for bridge structural health monitoring (SHM) is to provide a reliable assessment technique to potential hazards caused by structural damage or other structural defects using continuously monitored vibration data. Recognising the needs and shortcomings of SHM, a project was established by NICTA, the University of Technology Sydney and The University of Sydney to develop reliable damage detection methods to provide robust and accurate assessment techniques for critical bridge infrastructure in Australia. This paper presents the progress of research and development of a vibration-based damage detection technique and its experimental validation in the laboratory. The proposed technique uses residual frequency response functions (FRFs) combined with principal component analysis (PCA) to form damage specific features (DSFs) that are incorporated in pattern recognition using artificial neural networks (ANNs). In the method, FRFs are obtained using modal analysis techniques and damage is identified using ANNs that innovatively map the DSF to damage characteristics, such as damage location and severity. The results of the experimental validation show that the proposed technique can successfully locate and quantify damage induced to a concrete arch beam simulating a real life structural component of the Sydney Harbour Bridge.
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