Professor Zhongxiao Peng
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.
Research Interests
- 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
Research Collaboration
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 is an example of our strong and close collaboration with the Laboratory Vibrations and Acoustics (LVA at University of Lyon) led by Professor Jerome Antoni in the field of machine condition monitoring.
Research Facilities
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.
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PhD Projects
The group of Tribology and Machine Condition Monitoring at UNSW is a world-leading research team in the field and has many national and international collaborations. We (including , , ) are currently recruiting excellent research students to join the group as a PhD or Master鈥檚 (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听 or MPhil position: Please email z.peng@unsw.edu.auwith a copy of your CV, academic transcript(s) and/or English test results.
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- Publications
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- Teaching and Supervision
AUFRANDE 鈥 An excellent opportunity to obtain dual doctorates at INSA-Lyon (France) and UNSW Sydney (Australia)
INSA-Lyon and UNSW Sydney offer three (3) joint PhD projects in the Australia France Network of Doctoral Excellence () program. These projects in the field of machine condition monitoring, utilising state-of- the-art technologies, are excellent opportunities for outstanding researchers to pursue their studies and receive research training from world-leading experts in the field.
The titles of the 3 PhD projects are:
- Digital-twins and artificial intelligence for robust machine condition monitoring
- Industry 4.0 sensing for machine condition monitoring
- AI-Assisted Condition Monitoring (AIA-CM) based on data-driven optimal signal processing
Further information about AUFRANDE and these projects can be found on the -> .
Some information about the research environment supported by the UNSW-INSA Lyon International Laboratory can be found .
Key dates:
- Call opening: 27th November 2023
- Deadline for applications: 24th January 2024
Any technical inquiries can be directed to Professor Jerome Antoni (Jerome.antoni@insa-lyon.fr) at INSA-Lyon, Professor Zhongxiao Peng (z.peng@unsw.edu.au) or Associate Professor Pietro Borghesani (p.borghesani@unsw.edu.au) at UNSW Sydney.