The transport network in many regions around the world is vulnerable to extreme weather events. How the infrastructure responds to these hazards is crucial, not only for the protection of human life and the structures themselves, but also for socio-economic reasons. Following Storm Desmond in December 2015, 131 bridges needed urgent inspections and repairs, with the total economic damage to the region estimated to be £1.3 billion . The most common cause of bridge failure in the UK and Ireland is scour, with 140 railway bridge failures during 65 separate flood events between 1846 and 2013 attributed to scour alone . A review of 1502 bridge failures in the United States of America from 1966 to 2005, identified that 58% of these were a direct result of hydraulic action, with 32.8% and 15.5% of failures attributed to flooding and scour, respectively .
Scour, a dynamic phenomenon affected by a number of factors including water depth, flow speed, substructure geometry and material properties of the sediment , is defined as the removal of the underlying material from beneath the foundations of piers and abutments of bridges. However during periods of heavy rainfall, it is often a multi-hazard combination of flooding and scour which will ultimately lead to the failure of a bridge structure . Numerous studies have been performed to monitor the resilience of the built environment against these multi-hazard events as a method of predicting how vulnerable the transport system is; including INFRARISK , INTACT  and RAIN  projects. A review of the fragility of the transport system can assist asset owners to determine the most vulnerable structures at risk on the transport network. With these studies, an understanding remains that risk cannot be removed from all bridges, which means prioritising at-risk vulnerable structures but equally means that a residual level of risk will still exist for exceptional weather events (e.g. flooding in 2015 in Cumbria, northern England ) . Therefore, a need exists to design a cost-effective portable system, which can be rapidly deployed and easily installed to at-risk bridge infrastructure. This DAQ logger can assess how a structure performs both during routine day-to-day environmental conditions, but that can also be used to target vulnerable but not ordinarily high-risk structures during these extreme weather events.
The ability of the built environment to withstand these extreme and multi-hazard events is crucial for the safety of the infrastructure network. There are a several scour depth monitoring techniques available [4, 10], but these devices can often struggle to detect evidence of scour; due to water turbidity, impact from debris to the device itself or backfill to the scour hole. Recently, scour monitoring using structural health monitoring (SHM) has been proposed as an alternative to traditional scour measurement devices. SHM offers an alternative method for estimating the integrity of a structure during periods of flooding to infer scour, though suitable analysis of in situ parameters . The use of SHM reduces the reliance on visual inspections of bridges, which can often fail to find evidence of any damage to the structure, e.g. a visual inspection did not find any evidence of the visible scour at the Malahide Viaduct three days before it failed . A 2001 study by the FHWA revealed that ‘at least 56% of the average Condition Ratings were incorrect with a 95% probability from the visual inspection’ .
There are a number of forms of SHM, with varying levels of complexity and reliability of results, ranging from anomaly detection through to damage detection . A number of studies propose using changes in the dynamic properties of the structure to identify the presence of scour, where a decrease in the natural frequencies can be used to identify the presence of scour [15, 16]. Although bridge monitoring techniques using natural frequencies of the structures have been proven to be useful for confirming the presence of scour, there is a limited number of studies in the literature on their use in actual field studies [17, 18]. Both of these studies have required testing of bridges which are known to already be undermined by scour and were used to test initially scoured and then unscoured conditions, i.e. to prove the proposed method in reverse. From an extensive literature review, there has been little evidence of a study which has managed to identify scour in unknown conditions.
Resilience can be defined as ‘the capacity to recover quickly from difficulties’, or from an engineering perspective, ‘the ability to return to a stable steady state’. Studies have shown there is a need to integrate SHM into structures to allow for a rapid condition assessment to quantify the condition and safety of the structure following an extreme event (e.g. earthquake). Reducing time spent inspecting the structure to inform decisions on returning the structure to normal operation after an event represents improvement in resilient recovery . This report will discuss a stand-alone portable SHM system which can be used to target vulnerable structures where installation of a permanent SHM system is impractical.
Rotation-based structural health monitoring
Rotation is an important parameter for SHM. It reflects a significant trauma to the bridge, resulting in either transient or permanent deformation, i.e. damage. Recent studies have developed various rotation-based damage detection techniques for bridge monitoring systems, including vision-based methods and measurement data from inertial sensors [20,21,22,23]. Damage detection techniques are still relatively unproven for monitoring of bridges during scour events and also require an undamaged model of the bridge. Therefore, to be able to target the most at risk bridges during a flood event, a robust stand-alone system is required; one which does not rely on previous undamaged knowledge of the structure.
This article will discuss use of rotational measurements and will propose a rotation-based condition monitoring system as an alternative SHM system for bridges. By targeting bridges most at risk during a storm event and monitoring select parameters (e.g. the quasi-static behaviour of the bridge using rotation and deflection measurements) the condition of the bridge can be readily assessed allowing for a quicker assessment. The purpose will be to monitor the structure over an extended period to establish the effects of any environmental loading on the structure.
SHM of bridges has proven to be a useful tool for engineers to assess the condition of the structure. Accelerometers and gyroscopes can both be used to obtain rotational measurements, with each sensor having their own individual strengths and weakness. Accelerometers have proven themselves as a useful tool for monitoring bridges, capable of measuring both the dynamic properties of the structure (modal properties, etc.) and the quasi-static behaviour (rotation, deflection etc.). Gyroscopes, a proven technology for positioning for other applications, have had limited use in SHM to date [24, 25].
A review of available literature has identified a lack of studies using rotational measurements for SHM purposes. Therefore, the purpose of this study is to use gyroscopes to provide more accurate rotational measurements than traditional rotation sensors allow. Section 2 of this paper will review the properties of accelerometers and their role in SHM of bridges, focussing on quasi-static behaviour. It will further introduce gyroscopes as a complimentary sensor which can be deployed alongside accelerometers to refine rotational measurements obtained at the structure.
Rotation data can be obtained from both accelerometers and gyroscopes. Section 3 will introduce the derivation process for rotation from both sensors and propose the use of sensor fusion techniques to obtain the best available rotation data. Sensor fusion uses the strengths of each sensor to provide an improved estimate of the true parameter value (e.g. position, rotation, etc.). The Kalman filter is a popular form of sensor fusion techniques. It applies measured values to an estimate of the system state to propose the best estimate of the state in its next iteration and will be used to demonstrate the benefits of sensor fusion.
The following sections will then introduce experiments performed to trial the methodology proposed in the earlier sections, with rotation measurements obtained using a series of accelerometers and gyroscopes. Initially, the methodology was trialled on a scaled model of a bridge in the laboratory. The set-up and results of the laboratory tests are discussed in Sects. 5 and 6, respectively. Following the successful laboratory test results, the tests were repeated on a railway bridge which forms part of a heritage railway in the UK. The test set-up and results of fieldwork performed on this bridge are discussed in Sects. 7 and 8, respectively.