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A new two-step approach is developed for damaged cable identification in a cable-stayed bridge from deck bending strain responses using Support Vector Machine. A Damaged Cable Identification Machine (DCIM) based on support vector classification is constructed to determine the damaged cable and a Damage Severity Identification Machine (DSIM) based on support vector regression is built to estimate the damage severity. A field cable-stayed bridge with a long-term monitoring system is used to verify the proposed method. The three-dimensional Finite Element Model (FEM) of the cable-stayed bridge is established using ANSYS, and the model is validated using the field testing results, such as the mode shape, natural frequencies and its bending strain responses of the bridge under a moving vehicle. Then the validated FEM is used to simulate the bending strain responses of the longitude deck near the cable anchors when the vehicle is passing over the bridge. Different damage scenarios are simulated for each cable with various severities. Based on damage indexes vector, the training datasets and testing datasets are acquired, including single damaged cable scenarios and double damaged cable scenarios. Eventually, DCIM is trained using Support Vector Classification Machine and DSIM is trained using Support Vector Regression Machine. The testing datasets are input in DCIM and DSIM to check their accuracy and generalization capability. Different noise levels including 5%, 10%, and 20% are considered to study their anti-noise capability. The results show that DCIM and DSIM both have good generalization capability and anti-noise capability.

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Considering the nonlinear property of suspension damping and tire stiffness, a full-vehicle model is built for a heavy-duty truck. A modified preview driver model with nonlinear time delay is inserted into the vehicle model to compute the suitable steering angle of the front wheel and to make the vehicle follow the required route. Next, the finite element model of a five-span continuous curved highway bridge is established, and the bridge's inherent frequencies and modes are obtained. The curved bridge and the vehicle are coupled by three-directional tire forces, and a three-directional driver-vehicle-bridge interaction model is presented. The presented vehicle model and bridge model are verified by comparing with the published works. The dynamic impact factors of vertical, lateral, and torsional displacements of the bridge are calculated when a vehicle is traversing through the bridge, and the impact factors' distributions along the bridge are analyzed. The effects of vehicle driving conditions on impact factors are also researched. It is found that the impact factor calculated from the present specification for a straight bridge is smaller than that from the three-directional drivervehicle-bridge interaction model, and the vertical and torsional impact effects at the third span midpoint are greater than the lateral impact effect.