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' SENsing SKIN' for Monitoring-Based Maintenance of the Transport Infrastructure (SENSKIN)

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Skin-like sensing enables structural monitoring of transport infrastructure

Structural Health Monitoring diagnoses structural parts, along with their full assembly. With more frequent extreme weather and ever-increasing pressures on transport systems, analysis of the state of our infrastructure is more vital than ever.

Transport and Mobility

While Structural Health Monitoring (SHM) is expected to play an ever-greater role in transport infrastructure, current techniques continue to rely on point-based, as opposed to spatial, sensing. This requires a dense network of point-sensors, which considerably increases the monitoring cost. Expense is not the only drawback; current strain sensors cannot measure strains beyond 1 % to 2 % so they are not able to provide an alert in the face of an imminent catastrophe. The SENSKIN project took an innovative approach to surmounting these issues. It developed an easy-to-install, low cost dielectric-elastomer strain sensor that can transmit its measurements wirelessly and with low power needs. “The Sensor itself is passive, but the node is powered by a photovoltaic panel that charges a 3 000 mAh 18650 Li-On battery,” explains Dr Angelos Amditis, Research Director of ICCS, SENSKIN coordinator. The resulting sensors are not only cheaper, but also able to sense a range of strains, from very small to extremely large. As the communication between sensor and concentrator is wireless, the installation is far simpler and much faster. The silicon itself is also a less expensive material to use in the manufacturing of the sensors.

Delay-tolerant networking

Their approach uses delay-tolerant networking, or DTN, the general idea being to have the measurements available at any time, whatever the conditions. DTN allows measurements to be buffered during lost connectivity, making them available when the connection is re-established. DTN’s asynchronous, ‘store-and-forward’ data delivery model addresses the problems of interruptions and lack of infrastructure, as the architecture supports the development of sophisticated approaches to routing. The system can use intermediate nodes in order to route the sensor measurements in the case of a node not having direct connectivity to the gateway. “Should an extreme event trigger an emergency, the output will be preserved through (so-called) ‘panic communication protocols’ and forwarded to the processing station without loss of availability or accuracy,” explains Dr Amditis. The team also developed a decision support system to facilitate proactive, condition-based, structural intervention under operating loads and after extreme events. “The measurements from the sensors indicate the condition of the infrastructure (for example, a bridge) with colour coding: blue for OK, yellow for damage, red for critical. Additionally, the life-cycle cost and life-cycle analysis modules provide suggestions for maintenance and prediction of the cost of maintenance over the years to come,” Dr Amditis adds. SENSKIN partners have been trying their system out. The initial pilot took place on the 1st Bosporus bridge in Istanbul where they tested the telecommunication part of the system and integration aspects. The 2nd, and main pilot, took place from September 2018 to May 2019 on the G4 bridge in Krystalopigi Greece. “We made a number of significant improvements as we performed extensive testing on the sensor and the telecommunications, which worked well. The sensor shows some weaknesses in measuring very low strains, but on the other hand, it can measure extremely large strains compared to conventional sensors,” says Dr Amditis. It was a complex project involving an innovative approach to the application of existing technologies. “What I am personally most proud of is the way that this consortium came together every time there were seemingly unsurpassable obstacles, doubled down and provided solutions in order to further the research and achieve a positive result,” concludes Dr Amditis.

Keywords

Structural Health Monitoring, skin-like sensors, infrastructure, decision support system, delay-tolerant networking

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