Researchers at Queen’s University Belfast are participating in a new £7.7 million project aimed at changing how parts of the UK’s infrastructure, including bridges, telecom masts and wind turbines, are monitored and maintained.
Healthy infrastructure is critical to UK society and the economy, but monitoring and maintaining it is expensive.
The ROSEHIPS (Revolutionising Operational Safety and Economy for High-value Infrastructure using Population-based SHM) project aims to solve the infrastructure asset management problem in the UK for maintaining infrastructure, such as bridges, through new research to automate health monitoring. Instead of expensive scheduled inspections, diagnoses can be provided by permanently-installed sensors, collecting structural data continuously and interpreting it via computer algorithms.
Queen’s University experts have joined a collaborative team of researchers and will work with the University of Sheffield, University of Cambridge and the University of Exeter, as well as key industry partners including Northern Ireland’s Department for Infrastructure, Translink, Arqiva, Cellnex (UK) and Siemens Gamesa.
The researchers from Queen’s will focus on developing novel sensing – this will be customised for infrastructure and will help to overcome obstacles to the real-world implementation of the research.
The Engineering and Physical Sciences Research Council (EPSRC) project brings together expertise on bridge structural health monitoring from Dr David Hester and Professor Su Taylor from the School of Natural and Built Environment at Queen’s and sensor and embedded AI expertise from Professor Roger Woods in the School of Electronics, Electrical Engineering and Computer Science.
Dr Hester says: “Our initial work developing innovative sensing solutions and our considerable body of bridge monitoring experience has provided a critical practical platform for this project. Through cutting-edge research, experts at Queen’s are continuing to develop solutions to real world problems on our doorstop, which has a positive impact right across the globe.”
The project will extend and exploit Population Based Structural Health Monitoring (PBSHM), which allows data from one structure, where its state is known, to be used to make inferences about another structure.
“Population-Based Structural Health Monitoring is a game-changing idea, emerging in the UK very recently,” says Professor Keith Worden, from the University of Sheffield’s Department of Mechanical Engineering. “It has the potential to overcome current technological barriers and transform our ability to automatically infer the condition of a structure, or a network of structures, from sensor data.”
The project will also develop machine learning, sensing and digital twin technology for automated inference of health for structures in operation now, and drive new standards for safer, greener structures in future.
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