Tyndall National Institute is one of Europe's leading research centres, specialising in Information and Communications Technology (ICT) hardware. Tyndall has a critical mass of over 360 researchers, engineers, students and support staff placing a particular emphasis on quality, accomplishment and the delivery to Ireland of value from research. Tyndall’s areas of expertise range from micro-nanolectronics, microsystems, and photonics to theory modeling supported by a central fabrication facility.
(Institute of Electrical and Electronics Engineers (IEEE), 2019-09) Walsh, Michael; Abbruzzo, Giovanni; Hickey, Séamus; Ramirez-Garcia, Sonia; O'Flynn, Brendan; Torres, Javier; Horizon 2020; Electronic Components and Systems for European Leadership
Transport systems incorporating linear synchronous motors (LSMs) enable linear motion at high speed for emerging factory automation applications. The goal of this work is to determine the feasibility of harvesting energy directly from an operational LSM transport system employed in high volume manufacturing. Microelectromechanical (MEMs) based sensor technology, deployed as part of a wireless cyber physical system (CPS), perform near real-time magnetic field measurement for a mobile LSM vehicle. The vehicle under study is purposed for mobile factory automation and is not wired for communications nor does it have an onboard power source. A series of experiments were designed and conducted to establish the magnetic profile of the system. Empirical data capture was conducted on a cycled LSM test-bed comprising of 2 shuttles and 2 x 3 meter lengths of LSM track (MagneMotion QuickStick®100). Varying vehicle speeds were incorporated in the experimental regime to determine how changes in velocity would impact the magnetic profile of the vehicle. The recorded magnetic field data was analysed and a relationship between LSM vehicle speed and magnetic field frequency was established. The study highlights the potential to employ a single receiving coil to enable energy recovery which in turn could power a cyber-physical system (CPS) tasked with performing condition based monitoring of the LSM transport vehicles. This in turn can form the basis for the development of a predictive maintenance system, deployed to an LSM based transport layer in high volume manufacturing environments.