Motion-powered Autonomous Sensing sysTems (MAST)
Self-powered smart sensing provides a solution for the urgent, unmet need of real-time, continuous and long-term condition monitoring of critical infrastructure and machines.
MAST aims to develop innovate motion-powered autonomous sensing devices for condition monitoring and fault detection. Energy sources from machines and infrastrucure will be employed and converted into electricity using micro-electromechanical systems (MEMS) for energizing embedded wireless sensing devices to obtain real-time, continuous and robust operation with the feature of energy autonomy. It builds on the strengths of the Dynamics & Tribology Research Group, including non-linear dynamics, harvester design and signal processing. The project is focused on delivering the next generation embedded wireless sensing solutions with the capability of self-powered operation.
In collaboration with our industry partners, MAST will develop novel motion-powered autonomous devices using microfabrication and low-power flexible electronics to enable the large-scale application and robust operation of wireless sensing devices. MAST has the potential for very significant impact for condition-based maintenance of machines with reduced maintenance costs and operation downtime. The industrial sectors, including transport and manufacturing, will benefit from this research. The scientific community will benefit from developing capacity in an emerging field of global importance. The methodology developed will be of translational benefit to other scientific disciplines.
The project will utilise a variety of facilities housed within the School of Mechanical, Electrical and Manufacturing Engineering, including CAD and FEA software, system motion simulation facilities, suite of 3D-printers, laser machines and electronic testing facilities, to develop novel motion-powered autonomous sensing devices.
The team has already made great progress in the design, fabrication and testing of energy harvesting devices and low-power sensing systems, which is a key element of the project. A list of relevant publications can be downloaded from the Loughborough University repository.
Dr Hailing Fu - Lecturer in Electromechanical Systems
"The beauty of MAST is the utilization of machines motions to energize embedded sensing devices in realizing energy autonomy. Main challenges will be in how to integrate the latest advances in materials, dynamics, electronics and advanced signal processing technologies to fulfil such an ambitious goal."