Intelligent fault diagnosis and prognosis solution for rotating machinery

Rotating machinery has a fundamental role in many industries. Therefore, there is a need for a Condition-based maintenance (CBM) which holds the promise of predicting machinery maintenance requirements based on process performance measurements. Diagnostics and Prognostics are essential parts of CBM. Therefore, diagnostics and prognostics of rotating machinery can help to reduce machine downtime and cost. Many techniques such as vibration analysis, current signature analysis, acoustic emission analysis, wear and oil analysis,…,etc. have been used, through condition monitoring of the rotating machinery, to diagnose and prognosis  different faults such as, bearing, crack shaft, gearbox, belt drive, reciprocating mechanism, mechanical rub, induction motor, pump, compressor, and fan. The student will have the opportunity to work with experts in the prognostics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University. About the host University/Centre Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81% of Cranfield’s research as world leading or internationally excellent in its quality. Every year Cranfield graduates the highest number of postgraduates in engineering and technology in the UK (Source: Higher Education Statistics Agency Ltd). Cranfield Manufacturing is one of eight major themes at Cranfield University. The manufacturing capability is world leading and combines a multi-disciplinary approach that integrates design, technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Integrated Vehicle Health Management (IVHM) Centre is a major collaborative venture at Cranfield,...