  This paper proposes a damage detection method based on the train-induced
responses of high-speed railway box girder. Under the coupling effects of
bending and torsion, the traditional damage detection method based on the Euler
beam theory cannot be applied. In this research, the box girder section is
divided 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 residual
error of autoregressive (AR) model was used as a potential index of damage
features. The optimal order of the model was determined based on Bayesian
information criterion (BIC) criterion. Finally, the confidence boundary (CB) of
damage features (DF) constituting outliers can be estimated by Gaussian inverse
cumulative distribution function (ICDF). The numerical simulation results show
that the proposed method in this paper can effectively identify, locate and
quantify the damage, which verifies the accuracy of the proposed method. The
proposed method effectively identifies the early damage of all components on
the key section by using four strain sensors, and it is helpful for developing
effective maintenance strategies for high-speed railway box girder.
