Prof Robert Wood
No more applications being accepted
About the Project
Micro and nano- electrostatic array sensors will be developed with embedded electronics that will allow far better spatial and temporal resolution of tribological contact decay (surface and lubricant) in machines. Data outputs would be fed into Machine Learning algorithms for robust trend recognition and machine life prediction. Smart intelligent localised sensor technology for wear and contact degradation detection of bearings and if coupled to alleviation strategies this would improve their reliability. The sensor would give more time to react and detect unusual and non-linear wear trends. Work at Schaeffler is envisaged for testing the new sensors in their labs to show benefits of sensors to understanding distress of components/lubricant under test.
The studentship will be part of much larger £1m EPSRC funded programme to conduct research with the following objectives:
(1) miniaturise existing electrostatic sensor Condition Monitoring, nano stress devices and chemical sensing technology
(2) produce them as arrays
(3) embed electronics, and
(4) use machine leaning to understand outputs and develop predictive tools from training data.
Student background: A good first degree in electronics, electrical or mechanical engineering. Physics or related backgrounds will be considered. Tribology background and/or sensor development desirable.
If you wish to discuss any details of the project informally, please contact Professor Robert Wood FREng, nCATS research group, Email: [Email Address Removed], Tel: +44 (0) 2380 59 4881.
Funding Notes
This 3 year studentship covers UK/EU level tuition fees and provides an annual tax-free stipend. The stipend will be a minimum of £14,777 (pro-rated) for 2018/19 and may be enhanced for an excellent candidate.
Continue with Facebook
