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Health Monitoring and Diagnostics
The availability of machines and plants is an essential requirement for productivity. In order to minimise unplanned downtimes, it is necessary to detect the sources of error at an early stage. Our research is focused on developing algorithms and techniques that continuously monitor complex systems to detect/predict abnormal system behaviour. We specially develop model-based and AI-based algorithms for condition monitoring of industrial gas turbines to enable condition-based maintenance scheduling as well as prediction of emerging faults.
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Lincoln School of Engineering and Physical Sciences
University of Lincoln
Brayford Pool Campus
Lincoln
LN6 7TS