Fault diagnostics of electrical motor using magnetic flux sensor

Induction motor is inherently reliable and requires minimum maintenance. However, many companies are still faced with unexpected system failure and reduced induction motor lifetime. This gives rise to the need for maintenance strategy based on condition monitoring, which can be addressed by monitoring and analysing the real-time signals of the induction motor. Different faults of induction motors are generally classified as either electrical or mechanical faults. Also, different types of condition monitoring using vibration and electrical signals have been implemented. However, these methods are still immature enough for accurate diagnosis. Therefore, the fault diagnosis problem of electrical motor is still as open area for research. Magnetic flux sensor is a potential solution for detection and diagnosis of electrical faults because it is very sensitive to electromagnetic field. 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...