A vibration-based bridge scour detection procedure using a cantilever-based piezoelectric energy harvesting device (EHD) is proposed here. This has an advantage over an accelerometer-based method in that potentially, the requirement for a power source can be negated with the only power requirement being the storage and/or transmission of the data. Ideally, this source of power could be fulfilled by the EHD itself, although much research is currently being done to explore this. The open-circuit EHD voltage is used here to detect bridge frequency shifts arising due to scour. Using one EHD attached to the central bridge pier, both scour at the pier of installation and scour at another bridge pier can be detected from the EHD voltage generated during the bridge free-vibration stage, while the harvester is attached to a healthy pier. The method would work best with an initial modal analysis of the bridge structure in order to identify frequencies that may be sensitive to scour. Frequency components corresponding to harmonic loading and electrical interference arising from experiments are removed using the filter bank property of singular spectrum analysis (SSA). These frequencies can then be monitored by using harvested voltage from the energy harvesting device and successfully utilised towards structural health monitoring of a model bridge affected by scour.

This paper experimentally investigates a vibration-based scour monitoring approach applicable to bridges with multiple simply supported spans on shallow foundations. A monitoring strategy based on the relative changes in pier-mode shape amplitudes due to scour is postulated. The first global mode shape of a bridge structure with multiple spans is extracted from acceleration measurements using an output-only approach, frequency domain decomposition (FDD). The relative changes of the pier-mode shape amplitudes under scour are then tracked. Here, each pier-mode shape value is compared with the mean values of the remaining piers in a process that creates a mean-normalized mode shape (MNMS). The approach is demonstrated on a scaled model of a bridge with four spans, supported on sprung foundations, where scour is simulated by the replacement of springs, with springs of lower stiffness corresponding to a reduction in foundation stiffness. It is shown that at a given “scoured” pier, significant increases in the MNMS value occur, suggesting that the location of the scour can be identified. The magnitude of the MNMS at a given pier also increases with an increase in stiffness loss due to scour. In practice, the approach would work best by carrying out a visual inspection of the bridge to establish the initial health condition at the time of sensor installation. After this initial process, the bridge can be monitored remotely for scour on an ongoing basis.

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.