Bridge modal parameters play an important role in bridge engineering; they can serve as useful indices for many applications, such as numerical mode calibration and updating, and bridge structural health monitoring (SHM). Recently, the indirect monitoring of bridges has been increasingly investigated and developed because it avoids the need for instrumentation on all bridges of a network. The natural frequencies of bridges have been extracted from the dynamic response of a vehicle numerically and in laboratory experiments. This study proposes an algorithm to extract the bridge mode shapes and damping ratio using similar indirect measurements enhanced by the Hilbert transform (HT). The theoretical closed-form equations are derived for a vehicle–bridge interaction (VBI) model in which the vehicle is represented as a moving sprung mass passing over a simply supported beam at a constant low speed. Then, a numerical simulation with a quarter-car model is adopted to verify the proposed algorithm, including case studies on the influence of the vehicle speed and road roughness. In addition, a laboratory test is conducted to further investigate the feasibility of the proposed algorithm.

Ambient and vehicle-induced bridge vibration tests are two important ways of collecting data for the purpose of system identification and performance evaluation of bridges. A common bridge form that has been very popular over the past number of decades is the steel truss bridge; this paper presents the vibration data of a steel truss bridge situated in Japan: the Old ADA bridge. The target bridge was built in 1959 and removed in 2012. Prior to the removal of the bridge, both ambient and vehicle-induced vibration data were collected. Five different damage scenarios were designed to represent different real-world cases by introducing artificial damage in the truss. In Case A, there was no damage; in Case B, one vertical member of the truss was cut to half its section depth at the bridge midspan; in Case C, the same vertical member at midspan was fully cut; in Case D, the vertical member cut was repaired and recovered; in Case E, one vertical member at the 5/8th span was fully cut. Ambient and vehicle-induced vibration data were collected for each case. Full-scale bridge damage tests of this nature are rare, and thus the collected data will be helpful in the research of system identification and damage detection using both ambient and vehicle-induced vibration data, providing a benchmark structure for structural health monitoring using data in real bridges.

An experimental investigation is carried out to verify the feasibility of using an instrumented vehicle to detect and monitor bridge dynamic parameters. The low-cost method consists of the use of a moving vehicle fitted with accelerometers on its axles. In the laboratory experiment, the vehicle–bridge interaction model consists of a scaled two-axle vehicle model crossing a simply supported steel beam. The bridge model also includes a scaled road surface profile. The effects of varying the vehicle model configuration and speed are investigated. A finite element beam model is calibrated using the experimental results, and a novel algorithm for the identification of global bridge stiffness is validated. Using measured vehicle accelerations as input to the algorithm, the beam stiffness is identified with a reasonable degree of accuracy.

Ageing and deterioration of infrastructure are a challenge facing transport authorities. In particular, there is a need for increased bridge monitoring in order to provide adequate maintenance, prioritise allocation of funds and guarantee acceptable levels of transport safety. Existing bridge structural health monitoring (SHM) techniques typically involve direct instrumentation of the bridge with sensors and equipment for the measurement of properties such as frequencies of vibration. These techniques are important as they can indicate the deterioration of the bridge condition. However, they can be labour intensive and expensive due to the requirement for on-site installations. In recent years, alternative low-cost indirect vibration-based SHM approaches have been proposed which utilise the dynamic response of a vehicle to carry out ‘drive-by’ pavement and/or bridge monitoring. The vehicle is fitted with sensors on its axles thus reducing the need for on-site installations. This paper investigates the use of low-cost sensors incorporating global navigation satellite systems (GNSS) for implementation of the drive-by system in practice, via field trials with an instrumented vehicle. The potential of smartphone technology to be harnessed for drive-by monitoring is established, while smartphone GNSS tracking applications are found to compare favourably in terms of accuracy, cost and ease of use to professional GNSS devices.

Structural Health Monitoring (SHM) is a technique that involves gathering information to ensure that a structure is safe and behaving as expected. Within SHM, vibration-based monitoring is generally seen as one of the more cost-effective types of monitoring. However, vibration-based monitoring has mostly been undertaken on long-span bridges using data collected with a dense network of sensors. Historically, the logistical difficulty of collecting data on short- and medium-span bridges has meant that the usefulness of vibration-based methods on these bridges is largely unknown. Therefore, this study proposes Minimal Information Data-modelling (MID). MID is an approach that utilises low-cost, easily implementable sensors that are potentially feasible for operators to purchase and operate across a network. This approach will be investigated to determine whether MID is a feasible approach for monitoring short- and medium- span bridges. The results from MID were assessed to determine whether they could detect a suitably small shift in frequency, which is indicative of damage. It was determined that the data models could reliably detect frequency shifts as low as 0.01 Hz. This magnitude of frequency shift is similar to the level of frequency shift reported for a range of bridge damage cases found by others and validated with FE models. The accuracy achieved by the data models indicates that MID could potentially be used as a damage detection method. The cost of the equipment used to collect the data was approximately £370, demonstrating that it is feasible to use MID to monitor bridges across an entire network.

Digital manufacturing has transformed many industries but has had only a limited impact in the construction sector. To capitalize on advanced manufacturing techniques, this paper introduces a radically new connection approach for gravity structural steel frames. The proposed intermeshed steel connection (ISC) exploits robotic abilities to cut structural steel member ends precisely to accelerate deployment and offer better disassembly options over existing approaches. Forces are transferred through common bearing surfaces at multiple contact points, and connections can be secured by small locking pieces. This paper introduces the geometry, manufacturing, and initial analysis and test results of the connection. The paper demonstrates the ability of the connection to (1) be manufactured within current industrial tolerances, (2) be erected and disassembled, and (3) perform at expected design levels.