Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for largescale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bumpinduced excitation is estimated via a detailed analysis in four periods: separation, freefall, contact, and coupled vibrations. The precise estimation of bumpinduced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a twospan continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1degree of freedom (DOF) car model and 4DOF model.

Review of Structural Health Monitoring Methods Regarding a MultiSensor Approach for Damage Assessment of Metal and Composite Structures Structural health monitoring (SHM) is the continuous onboard monitoring of a structurexe2x80x99s condition during operation by integrated systems of sensors. SHM is believed to have the potential to increase the safety of the structure while reducing its deadweight and downtime. Numerous SHM methods exist that allow the observation and assessment of different damages of different kinds of structures. Recently data fusion on different levels has been getting attention for joint damage evaluation by different SHM methods to achieve increased assessment accuracy and reliability. However, little attention is given to the question of which SHM methods are promising to combine. The current article addresses this issue by demonstrating the theoretical capabilities of a number of prominent SHM methods by comparing their fundamental physical models to the actual effects of damage on metal and composite structures. Furthermore, an overview of the stateoftheart damage assessment concepts for different levels of SHM is given. As a result, dynamic SHM methods using ultrasonic waves and vibrations appear to be very powerful but suffer from their sensitivity to environmental influences. Combining such dynamic methods with static strainbased or conductivitybased methods and with additional sensors for environmental entities might yield a robust multisensor SHM approach. For demonstration, a potent system of sensors is defined and a possible joint data evaluation scheme for a multisensor SHM approach is presented.