Development of prestress-loss identification method in the cable-anchorage system using impedance responses and artificial neural networks.

Abstract

In this paper, a method for identifying the loss of prestressing force (prestress-loss) in the cable-anchorage system of prestressed concrete structures using the impedance responses and artificial neural networks (ANNs) is developed. First, theories of impedance responses and damage detection methods for diagnosing the occurrence and the severity of prestress-loss are presented. In which, the occurrence of prestress-loss is determined by MAPD (Mean Absolute Percentage Deviation) index. Then, the severity of the prestress-loss is determined by ANNs. The feasibility of the developed method is verified by numerical simulations for a real cable-anchorage system with different levels of prestress-loss. The reliability of the numerical simulations for impedance responses is evaluated by comparison to experimental results. Finally, the occurrence and severity of the prestress-loss are exactly identified by the proposed method. The results of this study show that the proposed method is highly effective in determining the prestress-loss in the cable-anchorage system.