This article uses extracted bridge mode shapes to detect bridge damage, including both local damage such as that due to a bridge strike and global damage such as that due to foundation scour. Typically, only one accelerometer is required, which is mounted on an instrumented vehicle passing over the test bridge. This concept is referred to as ‘drive-by’ bridge health monitoring. For a simple vehicle/bridge interaction (VBI) model, where the vehicle is represented as a moving sprung mass, a closed-form solution for the bridge mode shape is derived from the acceleration response of the instrumented vehicle. The validity of the proposed algorithm is numerically verified using a VBI model. In addition, it is shown that the extracted mode shape can be used to assess the bridge condition. A damage index based on the extracted mode shape is proposed to detect bridge damage and to provide an indication of the damage level. In the numerical study, the factors that affect the accuracy of the proposed algorithm are investigated, including the vehicle speed and measurement noise. Two laboratory experiments are conducted to validate the mode shape extraction and bridge damage detection processes for cases of both local and global damage.

For bridges with surface foundations, scour is one of the main reasons for bridge failures. In regard to structural health monitoring, vibration-based scour detection techniques have received increasing attention over the past two decades. Scour occurs below the water surface in rivers or sea, leading to difficulty in equipment installation and maintenance. Recently, the concept of “drive-by” SHM using the indirect measurement of passing vehicle responses has been developed rapidly due to its convenience and low cost. This paper proposes a method to detect scour using the vehicle responses under an operational vehicle speed. The wavelet transform was applied to vehicle accelerations to obtain the wavelet energy. It was found that the wavelet energy increases with the increase in the scour damage level. However, the wavelet energy may also be affected by the on-site operating environments, such as sensor noise and other variabilities, which interferes with the identification of scour in practice. Hence, in this work, a statistical-wavelet-based approach was presented to effectively detect the presence of scour and even its location. The feasibility of the proposed approach is verified in both numerical simulation and lab experiments. The results show that the proposed method has a good potential to detect scour using indirect measurements.

Accurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usually strain gauges, placed at particular locations on the underside of the bridge. To improve axle detection in the measured signals, this paper proposes a wavelet transform and Shannon entropy with a correlation factor. The proposed approach is first verified by numerical simulation and is then tested in two field trials. The fidelity of the proposed approach is investigated including noise in the measurement, multiple presence, different vehicle velocities, different types of vehicle and in real traffic flow.

Recently, the ‘drive-by’ or vehicle scanning technique has attracted increasing attention over the last decade for the purpose of bridge health monitoring. The feasibility of this technique has been demonstrated by many field tests. In comparison to conventional bridge SHM, the concept of the drive-by bridge technique shows many advantages in terms of efficiency, economy, convenience, and mobility. It has been verified that wavelet transforms can successfully identify bridge damage and its location using the responses of a moving vehicle. However, the validity of this method is challenged by road roughness. This paper proposes a wavelet-based approach to detect bridge defects using wavelet energy. In addition, a damage index based on component wavelet energy is developed to localize the damage. A numerical simulation is modeled to verify the feasibility of the proposed approach, and the result shows that the proposed approach performs well even when considering road roughness in the vehicle and bridge interaction. Moreover, the effects of road surface profile, vehicle velocity, vehicle mass, noise signal, and different damage severity on the proposed approach are investigated. The proposed approach shows a great potential application in bridge health monitoring using indirect measurements from a moving vehicle.

Recently, Ultra-High Performance Concrete (UHPC) has attracted increasing attention in civil engineering. Numerous steel–UHPC composite structures have been constructed around the world. The proper consideration of the shear-lag effect has a significant influence on the safety of structures. In view of the shear-lag effect of steel–UHPC ribbed slab composite structure (SU-RSCS) in the elastic stage, a theoretical calculation model based on the bar simulation method is first developed. Then, the feasibility and accuracy of that are verified using both experimental data and numerical simulation. Moreover, many factors (including width-to-span ratio, the ratio of rib height to UHPC layer thickness, the ratio of rib width to rib spacing, and the number of transverse ribs) are parametrically investigated to further investigate the structural shear-lag effect using the proposed method. In addition, the orthogonal analysis is applied to determine the sensitivity of each parameter to the shear-lag effect. The parametric interactions are also considered. At last, the comparison between calculation results of the proposed method and specifications are discussed. The results show that the proposed approach can accurately predict the shear-lag effect on SU-RSCSs in the elastic stage. It is also found that the width-to-span ratio has a great influence on the structural shear-lag effect, while the number of transverse ribs has no significant influence on that.