Dr Zhongxiao Peng’s research focus has been wear analysis and machine condition monitoring. Her main research interests include 3D image acquisition, processing and quantitative analysis of wear in mechanical and bio-engineering systems; development and application of artificial intelligent techniques for prediction of the performance and remaining useful life of mechanical systems; integration of multiple techniques (wear analysis, vibration and acoustic emission) for machine health monitoring.
Fields of Research (FoR)Tribology, Dynamics, vibration and vibration control, Artificial intelligence, Image processing, Biomechanical engineering
Dr Zhongxiao Peng completed her PhD degree in Mechanical Engineering from the University of Western Australia in 2000. She joined James Cook University (JCU) as a lecturer in August 1999 and worked at JCU for 12 years. She led the Mechanical Engineering discipline over the period from 2008 to early 2011. Dr Peng joined the School of Mechanical and Manufacturing Engineering at UNSW Sydney in August 2011. She leads the Tribology and Machine...view more
Dr Zhongxiao Peng completed her PhD degree in Mechanical Engineering from the University of Western Australia in 2000. She joined James Cook University (JCU) as a lecturer in August 1999 and worked at JCU for 12 years. She led the Mechanical Engineering discipline over the period from 2008 to early 2011. Dr Peng joined the School of Mechanical and Manufacturing Engineering at UNSW Sydney in August 2011. She leads the Tribology and Machine Condition Monitoring research group at UNSW Sydney and works closely with EmProf. Robert (Bob) Randall, Dr Pietro Borghesani and Dr Wade Smith on a number of projects in the field of machine condition monitoring.
- Wear analysis of mechanical and bio-engineering systems
- 3D image acquisition, processing and quantitative characterisation of worn surfaces and wear debris at nano- and micro-scale
- Wear debris and vibration-based techniques for fault detection, diagnostics and prognostics of machinery
- Development and application of artificial intelligent techniques for simulating and analysing the degradation process of mechanical systems/components
Dr Peng and the Tribology and Machine Condition Monitoring group collaborate with many researchers within and outside Australia on a range of fundamental and application-orientated projects in the field of tribology and machine condition monitoring.
The Tribology and Machine Condition Monitoring group has a wide range of research facilities for wear testing, wear analysis and machine condition monitoring. They include two gearboxes, a rolling-sliding rig, a tribometer, high quality microscopes (optical and laser scanning microscopes), a number of quantitative image analysis packages, and extensive vibration instrumentation (including for acoustic emissions) and advanced signal processing packages developed in-house.
UNSW has many state-of-the-art image acquisition and examination facilities including laser scanning confocal microscopes, scanning electron microscopes, atomic force microscopes.
The group of Tribology and Machine Condition Monitoring at UNSW is a world-leading research team in the fields and has many national and international collaborations. We (including A/Prof. Pietro Borghesani, Dr Wade Smith, Em/Prof. Bob Randall and myself) are currently recruiting excellent research students to join the group as a PhD or Master’s (MPhil) student. If you have good grades and are keen to gain deep knowledge and many useful experimental and analytical skills in the fields of tribology (wear) and vibration for machine condition monitoring, you are welcome to approach us for a chat and/or discussion. Our current research topics include:
- AI enabled machine condition monitoring (multiple projects)
- Development of advanced condition monitoring techniques for wind turbines
- Wear monitoring in a contaminated lubrication condition
- Integration of multiple techniques for fault detection, diagnostics and prognostics
- Characterisation of 3D printed mechanical components
- Signal processing of bio-signals for human health monitoring
- Understanding and development of advanced meta-acoustic materials for marine application
Applying for a PhD or MPhil position: Please email email@example.com a copy of your CV, academic transcript(s) and/or English test results.
My Research Supervision
Areas of supervision
- Tribology and bio-tribology
- Machine condition monitoring
- Advanced acoustic materials for marine applications