Sensors and Connectivity series: What will self-sensing infrastructure mean for rail operations?

Self-sensing infrastructure monitors and detect changes within itself using embedded sensors that relay the data to a computer. This information is collected in real-time and can be used for Structural Health Monitoring to streamline inspection and make maintenance more targeted.

Latest update: February 2020


What is Self-Sensing Infrastructure? 

Self-sensing infrastructure (SSI) constantly measures its own internal, physical changes without the need for external instruments. The sensors within the structure respond to inputs such as strain or temperature and convey data to an outside receiver via wireless technology. This makes the monitoring of a structure less time-consuming and requires less manual intervention. 
SSI currently comes in two main forms:

  • Fibre optic sensing (FOS) uses optical fibres that run within the construction material. The measured signal alters due to the flexing of the fibres, as a result of strain. 
  • Smart fillers are mixed into a range of composite materials such as concrete, clay bricks, and carbon fibre composites. These change the electrical properties of a material when stress is experienced. The change can be measured. Examples include carbon nanotubes and nickel powder. 

In particular, SSI can be used to detect the formation of cracks within concrete structures before it becomes unstable. Currently, cracks are only noticeable once they have reached the surface of a structure, by which time the damage is significant and requires immediate repairs

Self Sensing
Smart Infrastructure and Construction engineers from the University of Cambridge deploying fibre optics to monitor sprayed concrete tunnel lining.

Photo sourced from Flickr:

What industries use Self-Sensing Infrastructure?

FOS technology is widely used in the oil and gas industry. According to Future Market Insights, in 2015 this accounted for 60.9% of the global FOS market. The technology can resist up to 300 °C and has the ability to monitor pipes and detect leaks in real time. This makes FOS a valuable resource where conditions are in inaccessible or inhospitable and maintenance is costly or hazardous. 

Fibre optic sensors are also used in mining to ensure that tailings dams are stable by monitoring long-term deformation or creeping. Smart fillers are not yet commercially deployed. SSI for civil engineering is still in development and not yet widely used. However, a number of trials have been conducted over the last decade. The technology naturally lends itself to Structural Health Monitoring for its ability to provide live data about structures. 

How could it impact the rail industry?

Supporting infrastructure, such as bridges, will be better maintained as there will be improvements in predicting failure. In addition, shorter maintenance periods will be required benefiting rail users by reducing disruption to services. Another benefit of SSI is that it can be retrofitted to existing structures. Therefore, minor works will enable self-sensing components to be installed on an already-existing construction.

Furthermore, SSI can be combined with other technologies to develop a holistic approach to maintenance. The data generated by SSI can improve remote condition monitoring as the data received will be live. This could make digital twins more accurate which would allow maintenance to be more effective. 

Concrete sleepers with FOS could allow train operators to more precisely determine the location of rolling stock by detecting strain in rails as trains pass. This data could also indicate the speed and weight of rolling stock without the need for further instrumentation. Fibre optic sensors are already used by weigh-in-motion bridges, but not embedded within the concrete.

If deployed in station floors SSI could be used to measure footfall in real time. This would help in developing robust models to predict crowd movement, especially on platforms at risk of crowding. The station could also respond to these variations instantly, with reactions such as reversing ticket barriers to reduce the threat of harm caused by crowding.

What uncertainties remain?

There is a lack of robust models for processing signals into useful data, as several parameters can affect the signal generated by smart fillers and the magnitude of these changes is unique to the particular structure. Furthermore, the accuracy of the data can drift over time, requiring frequent recalibration.

Practical application of SSI has been limited and tests have been mostly in-lab or on trials. The reluctance to adopt SSI—perhaps due to the risks of implementing a new technology—has limited its impact to date. The slow uptake has also kept costs high, but it is likely that these costs will decrease as the technology becomes widespread.

Although fibre optic sensors can last for decades, as they are embedded within the structure the fibres are not easily accessed if they become defective. This would require the extraction of the fibres by destroying the affected part of the structure. This is also significant for smart fillers, as the sensors and transmitters are internal and will also likely degrade with time, leading to more excavations. Additional research is necessary to understand how these issues may arise and what can be done to avoid or mitigate potential issues. Furthermore, the maintenance periods between repairing sensors is not clear. Fibre optics used for telecommunications last up to 30 years while bridges can be expected to last 5 times as long. As such, the benefits of being able to monitor infrastructure and potentially collect secondary data (such as the weight of rolling stock) must be weighed against the cost of maintaining the sensing system. 

What is the current state of R&D?

FOS is now well-understood and in the trial and development phase for use in SSI, while smart fillers are still undergoing lab-based studies. In 2018, researchers at Iowa State University successfully demonstrated the capabilities of clay bricks doped with carbon nanotube fibres to return to a baseline electrical resistance after experiencing strain. This shows that it will be possible for reliable models to be created.

The Cambridge Centre for Smart Infrastructure and Construction (CSIC) has conducted several projects dedicated to bringing SSI into demonstrations and trials. Within the Crossrail project, CSIC used FOS to map strain distribution through tunnels in the excavation, allowing safety margins to be more accurately determined, thus reducing material and labour costs. 

In 2016, FOS was incorporated into two railway bridges as part of the Stafford Area Improvements Programme. As a result of this, the Structural Health Monitoring of these bridges can be delivered in real time and in more detail, which is providing engineers with a more advanced insight into the behaviour of the bridge in response to strain caused by trains on the bridge.

What should the rail industry do?

Following work delivered by CSIC, rail could continue to work with academia to integrate SSI across its assets. Models tailored for rail could be generated using the data harvested, which would benefit maintenance works by better predicting failures earlier and making infrastructure management more acutely targeted.

The rail industry could pave the way to make SSI common across the civil engineering sector. Several structures such across the rail network can benefit from the installation of SSI including bridges, retaining walls and tunnels. The data generated can be harvested remotely, rather than from on-site inspections. This would reduce the risk of harm to trackside workers as the measurements can be conducted remotely and limit the labour required to carry out a more effective maintenance. 



Emerging Technology Analysis: Self Sensing - 2020 Edition
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