Artificial Intelligence (AI) and the Internet of Things (IoT) is rapidly expanding and can revolutionise condition monitoring, prognostics and diagnostics for many different technologies. Variable speed electric motor drives underpin many industrial and commercial processes such as conveyors, hoists and machine tools, and process downtime can result in loss of income or financial penalties. Forecasting the remaining lifetime of a drive or prognosing potential failure can therefore provide significant commercial benefit. This PhD project will expand previous collaborative research between the University of Nottingham and Siemens PLC into condition monitoring of variable speed motor drives, and its main aim is to demonstrate Machine Learning technologies for prognosing and diagnosing electrical faults within an AC motor drive system.
The Power Electronics, Machines and Control Group at the University of Nottingham is offering a fully funded PhD studentship with Siemens (DI MC – Competence Centre for Power Electronics) as part of their Industrial Cooperative Award in Science & Technology (iCASE). This award will provide the successful candidate with high-quality research training in advanced industrial motor drive systems and AI technologies with the aim of creating a proof-of-concept demonstrator to validate the researched technologies.
The successful applicant will hold a First or Upper Second-Class Honours degree in Electrical and Electronic Engineering and will have experience of working with variable speed drives and/or power electronics systems, together with an awareness of IoT and AI technologies. They will be able to demonstrate the typical attributes of successful researchers (creativity, innovation mindset ability to work independently as well as in a team) and will have excellent computing skills. We will also consider applicants from diverse backgrounds that have provided them with the equivalent and relevant experience and knowledge.
EPSRC iCASE studentships are fully funded (fees and maintenance) for eligible UK students. International (including EU) students may be considered for partial funding (home-level fees and maintenance).
How to apply:
Applicants are welcome to contact Professor Mark Sumner [email protected] or Dr. Minglei You [email protected] directly for more information about the project.
Applications should email their CV to Professor Mark Sumner and include a covering letter which states why they are interested in this specific position and provides details of significant project work they have undertaken. Please ensure you state in your email that you are applying for the iCASE PhD - SMART Inverter using Power Electronics as IoT access point.