Associate Professor Pietro Borghesani
Associate Professor

Associate Professor Pietro Borghesani

Engineering
Mechanical and Manufacturing Engineering

After a 1.5 year experience at McKinsey and Co. as a business analyst consultant, I have obtained a PhD in Mechanical Engineering at Politecnico di Milano (Italy, 2013) with a thesis on “Tools for the automated condition monitoring of rotating machines”. During my PhD and in a brief post-doctoral activity at Politecnico di Milano I have worked on a series of industrial projects related to the health monitoring and system identification for a wide range of mechanical systems, including bridges, large rotating machines, road and rail vehicles and industrial coolers.

My research activity has continued at QUT since December 2013 until the end of 2017, with a focus on asset health optimisation in power generation and process industries.

At UNSW I continue working in asset health monitoring and management, including vibration sensing, signal processing, machine learning, and maintenance optimisation. I currently collaborate with Australian and international companies in the fields of aerospace and rail.

I am an Editorial Board Member for Mechanical Systems and Signal Processing (MSSP) and a Member of the International Society for Engineering Asset Management (ISEAM).

  • Journal articles | 2023
    Lu R; Borghesani P; Randall RB; Smith WA; Peng Z, 2023, 'Removal of transfer function effects from gear vibration signals under constant and variable speed conditions', Mechanical Systems and Signal Processing, vol. 184, http://dx.doi.org/10.1016/j.ymssp.2022.109714
    Journal articles | 2022
    Lu R; Shahriar MR; Borghesani P; Randall RB; Peng Z, 2022, 'Removal of transfer function effects from transmission error measurements using cepstrum-based operational modal analysis', Mechanical Systems and Signal Processing, vol. 165, http://dx.doi.org/10.1016/j.ymssp.2021.108324
    Journal articles | 2021
    Chang H; Borghesani P; Peng Z, 2021, 'Investigation on the relationship between macropits and wear particles in a gear fatigue process', Wear, vol. 484-485, pp. 203724 - 203724, http://dx.doi.org/10.1016/j.wear.2021.203724

LP150100545 - Condition-based maintenance optimisation for Australian sugar industry

DP160103501 - A new role for vibration analysis in gear wear modelling and prediction

LP180101161 - Vibration-based health monitoring of aero-engine bearings

DP190103231 - Cepstral methods of operational modal analysis to separate multiple sources

LP200100382 - Condition-based maintenance optimisation for Queensland’s railways