This paper introduces a cable damage identification method for cable-stayed bridges based on principal component analysis(PCA)to facilitate efficient cable damage detection.The proposed approach involves collecting the acceleration response of the cable structure when subjected to a moving load.Subsequently,the PCA method is employed to reduce the dimensionality of the time-domain signal.Statistical data are then extracted from the reduced dimension signal,and a multi-order statistical moment fusion index is constructed using the Dempster-Shafer(D-S)evidence theory for identification purposes.Using the Yonghe Bridge in Tianjin as a case study,the paper explores the impact of cable damage degree,load mass,and load moving speed on damage identification accuracy through finite element numerical simulations.The analysis results demonstrate the efficacy of the proposed method,highlighting its robust recognition capabilities and resilience to noise.The developed approach proves to be a promising tool for accurate and timely identification of cable damage in cable-stayed bridges,contributing to enhanced structural safety and maintenance practices.
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