Attend the Virtual Global Study Fair | Register Now Attend the Virtual Global Study Fair | Register Now

PhD (iCASE) “IoT and Machine Learning Technology for Condition Monitoring in Variable Speed Motor Drives” - (ENG 1670)


   Faculty of Engineering

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof Mark Sumner, Dr Minglei You  No more applications being accepted  Competition Funded PhD Project (UK Students Only)

About the Project

PhD (iCASE) “IoT and Machine Learning Technology for Condition Monitoring in Variable Speed Motor Drives”

The Power Electronics, Machines and Control Group at the University of Nottingham is offering a fully funded PhD studentship with Siemens as part of their recently awarded Industrial Cooperative Award in Science & Technology (iCASE). This award will provide the successful candidate with high-quality research training in advanced variable speed motor drive systems.

Variable speed drives are used in many industrial or commercial applications where process downtime can result in loss of income or penalties. Therefore, forecasting the remaining lifetime of a drive or prognosing potential failure can have 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 (ML) and Internet of Things (IoT) technologies for prognosing and diagnosing electrical faults and degradation within a variable speed drive. The project will initially evaluate different Machine Learning approaches for characterising the degradation of the drive based on internal measurements made. It will then investigate how linking together different drives can improve the accuracy of the condition monitoring system and provide additional benefits for prognostics and diagnostics. A proof-of-concept demonstrator will be used to assess the performance of the developed technology.

The successful applicant will hold a First or Upper Second-Class Honours degree in Electrical and Electronic Engineering and will understand ML and IoT technologies. They will be able to demonstrate the typical attributes of successful researchers (creativity, 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 UK students only. The successful candidate must be able to start before 1st October 2023.

Applicants are welcome to contact Dr Minglei You [Email Address Removed] or Professor Mark Sumner [Email Address Removed] directly for more information about the projects.

To apply, will need to email your CV and a personal statement to Professor Mark Sumner. Please ensure you state in your email that you are applying for a IoT iCASE Award with Siemens.


Funding Notes

EPSRC iCASE studentships are fully funded (fees and maintenance) for UK students only.

How good is research at University of Nottingham in Engineering?


Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities
Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.

PhD saved successfully
View saved PhDs