Proposal ID: 635844-2
ICCS project ID: 63092300
Role: Coordinator
Acronym: SENSKIN
Topic: MG-8.1a-2014
Type of action: RIA
Call identifier: H2020-MG-2014_TwoStages

SENSKIN : SENsing SKIN for Monitoring-Based Maintenance of the Transport Infrastructure

Duration in months: 36
Fixed keyword 1: Multi-modal and infrastructure
Fixed keyword 2: Road infrastructure
Fixed keyword 3: Airport infrastructure
Fixed keyword 4: Rail infrastructure
Free keywords: Strain sensors for large strain, strain sensors for spatial sensing, skin-like sensors, LCA for bridges, bridge structural monitoring, decision support for bridge maintenance

Structural Health Monitoring (SHM) is expected to play a predominant role in the management of the transport infrastructure. Yet, SHM techniques continue to rely on point-based, as opposed to spatial, sensing requiring a dense network of these point-sensors increasing considerably the monitoring cost. Additionally, commercially available, strain sensors cannot measure strains beyond 1% to 2% and, thus, are not able to provide an alarm for an imminent catastrophe. SENSKIN aims to: (a) develop a dielectric-elastomer and micro-electronics-based skin-like sensing solution for the structural monitoring of the transport infrastructure that will offer spatial sensing of reversible (repeated) strains in the range of 0.012% to more than 10%, that requires little power to operate, is easy to install on an irregular surface, is low cost compared to existing sensors, allows simple signal processing and includes the ability of self-monitoring and self-reporting. (b) use the new and emerging technology of Delay Tolerant Network to secure that strain measurements acquired through the ‘sensing skin’ will reach the base station even under extreme environmental conditions and natural disaster events such as, high winds or an earthquake, where some communication networks could become inoperable.  (c) develop a Decision-Support-System for proactive condition-based structural intervention under operating loads and intervention after extreme events. It will be based on an accurate structural assessment based on input from the strain sensors in (a) above and will examine the life-cycle economic, social and environmental implications of the feasible rehabilitation options and the resilience of the infrastructure to future changes in traffic demand that these options offer. (d) implement the above in the case of bridges and test, refine, evaluate and benchmark  the monitoring system (integrated a and b) and package (integrated a, b and c) on actual bridges.

Lab URL: http://