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This paper proposes a damage detection method based on the train-inducedresponses of high-speed railway box girder. Under the coupling effects ofbending and torsion, the traditional damage detection method based on the Eulerbeam theory cannot be applied. In this research, the box girder section isdivided into different components based on the plate element analysis method.The strain responses were preprocessed based on Principal Component Analysis(PCA) method to remove the influence of train operation variation. The residualerror of autoregressive (AR) model was used as a potential index of damagefeatures. The optimal order of the model was determined based on Bayesianinformation criterion (BIC) criterion. Finally, the confidence boundary (CB) ofdamage features (DF) constituting outliers can be estimated by Gaussian inversecumulative distribution function (ICDF). The numerical simulation results showthat the proposed method in this paper can effectively identify, locate andquantify the damage, which verifies the accuracy of the proposed method. Theproposed method effectively identifies the early damage of all components onthe key section by using four strain sensors, and it is helpful for developingeffective maintenance strategies for high-speed railway box girder.

Damage detection of high-speed railway box girder using train-induced dynamic responses