Winding Fault Diagnosis and Failure Prognosis Technique for Brushless Synchronous Generator

Abstract

Winding fault diagnosis and failure prognosis technique has been developed based on d-q model of brushless synchronous generator (BLSG) considering actual winding insulation degradation curve of machine in inter-turn fault, damper bar and field currents for various severities of inter-turn winding faults have been estimated using extended Kalman filter. For validation of damper bar currents, 2 D transient electromagnetic analyses using finite element method have been done, and 2^nd harmonic component of damper bar currents for various severities of inter-turn fault in stator windings have been computed by Fourier transformation. The winding insulation degradation curve of machine has been determined by accelerated life test, and used for estimation of remaining useful life of machine under inter-turn fault, assuming a pre-defined failure threshold. Actual and predicted life of the BLSG has been compared. Wireless sensors using rotor telemetry system have been mounted on the rotor of BLSG for experimental validation of field currents under winding faults. The 2^nd harmonic of damper bar currents increase with increase in severities of winding faults and do not get affected by diode failures in rotating rectifier, hence this can be used as a robust fault indicator for diagnosis and prognosis of inter-turn winding fault in BLSG.

Keywords:

• accelerated life test
• brushless synchronous generator
• damper bar current
• d-q model
• extended Kalman filter
• finite element method
• inter-turn fault
• remaining useful life
• second harmonic
• and wireless sensor

Additional information

Funding

This work was supported by the National Research Foundation (NRF), Singapore, under the Corporate Lab@University Scheme.

Notes on contributors

Vinay Jaiswal

Vinay Jaiswal received his Ph.D. degree from University of Quebec, Canada in collaboration with McGill University, Montreal, Quebec, Canada, in electrical engineering. He has worked for Cognizant Technology Solutions, USA, as a Senior Engineer from October 1999 to August 2001, Hydro-Quebec Chair, Canada, as a Research Engineer from August 2001 to December 2005, and Global R&D Center, Crompton Greaves Limited, as a Senior Technology Manager (Electrical Machines & Drives) from December 2005 to July 2016. Presently, he is working with Rolls-Royce Corporate Lab, Singapore, as a Senior Research Scientist (Electrical Machines & Drives) since July 2016. He has authored 14 papers in refereed international journals & conferences, and applied for 2 patents. His research interests include electromagnetic & thermal design, fault diagnosis and prognosis of rotating machines, actuators, transformers & switchgears, numerical and analytical methods in electromagnetics, computer-aided design of electromagnetic devices, the finite element method and software engineering.

Danwei Wang

Danwei Wang received his Ph.D and MSE degrees from the University of Michigan, Ann Arbor in 1989 and 1984, respectively. He received his B.E degree from the South China University of Technology, China in 1982. Since 1989, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore. Currently, he is a professor and the director, ST Engineering NTU Corporate Laboratory. He is an associate editor for the International Journal of Humanoid Robotics and served as an associate editor of Conference Editorial Boards for many IEEE international conferences. He was a recipient of Alexander von Humboldt fellowship, Germany. He has published widely in technical areas of iterative learning control, repetitive control, robust control and adaptive control systems, manipulator/mobile robot dynamics, path planning, and control, as well as model-based fault diagnosis, and satellite formation flying. His research interests include robotics, control theory and applications.

Padmanabhan Sampath Kumar

Padmanabhan Sampath Kumar received the B.E. degree in electronics and communication engineering from the College of Engineering, Guindy, Anna University, Chennai, India, in 2011, and the M.Sc. degree in computer control and automation and Ph.D. degree in electrical and electronic engineering from Nanyang Technological University (NTU), Singapore, in 2013 and 2019, respectively. He was previously working as a Researcher with Rolls-Royce@NTU Corporate Lab affiliated with School of EEE, NTU. He is currently working as a Scientist with Delta Research Center, Delta Electronics, Singapore. His research interests include wireless sensors, condition monitoring and sensor arrays.