School of
Information Technology and Electrical Engineering

Speaker: Dr Hui Ma
Seminar Date: Mon, 20/11/2017 - 14:00
Venue: 67-342 (Priestley bldg)
Host: Prof Tapan Saha

Seminar Type:  ITEE Research Seminar

Abstract: 

Power transformer is one of the most important and expensive equipment in a power system. Its condition needs to be continuously monitored and assessed for an informed operation and maintenance decision-making. During the past five years, I have applied a variety of signal processing and machine learning techniques to online condition monitoring and diagnosis of power transformer. In this talk I will present a number of these techniques. They are: (1) signal processing for reliable data acquisition to provide visibility of the condition of power transformer; (2) machine learning for mining large volumes of data, extracting representative characteristics (features) regarding transformer condition, separating multiple types of faults, and identifying the type of each individual fault inside power transformer; and (3) data fusion for integrating data and information obtained from different online and offline measurements as well as historic records to make condition assessment of power transformer.

Biography: 

Dr. Hui Ma received his PhD degree in electrical and electronic engineering from the University of Adelaide in 2008. Then he joined the School of ITEE of the University of Queensland as a research fellow working on monitoring, diagnosis and health management of power transformers, switchgears and other electrical equipment. Dr. Ma’s research outcomes are well recognized by both academic and industry communities. During the past five years, Dr. Ma has published 25 journal papers, most are in IEEE transactions and in IET journals. In June 2016, Dr. Ma was invited by IEEE Smart Grid to deliver a webinar on condition monitoring of high voltage equipment in smart grid. Dr. Ma have established a closed relationship with Australian power utility companies to develop new techniques of condition assessment for their assets.

Prior to joining the University of Queensland, Dr. Ma has worked as an engineer in industry for six years. His research interests include high voltage engineering and electrical insulation, signal processing and machine learning application in power systems, power systems, industrial informatics, wireless sensor networks, and sensor signal processing. Dr. Ma is a Senior Member of IEEE.