Structural Damage Identification by Neural Networks and Modal Analysis
نویسندگان
چکیده
The basis for the approach to damage identification is that changes in the structure's physical properties. This paper proposes a nondestructive testing technique based on modal analysis is discussed in order to develop a new, efficient and simple damage detection method for civil structures. This paper presents a sensitivity study comparing the sensitivities of frequencies, mode shapes, and modal flexibilities. Sensitivity-based analysis for the features vectors extraction. The neural networks (NNs) are introduced in this study, the combined parameters of the "frequency change ratios (FCRs) and shifts in modal flexibilities (SMFs)" are presented as the input features of NNs in structural damage identification. It is also shown, through a simulation, that this method is verified to be practical for the location and extent of structural damage identification.
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