Browse by Supervisor

Vallely, Patrick (2020). A holistic approach to remote condition monitoring for the accurate evaluation of railway infrastructure and rolling stock. University of Birmingham. Ph.D.

Giannouli, Eleni (2021). Advanced signal processing of wayside condition monitoring of railway wheelsets. University of Birmingham. Ph.D.

Uyanik, Mehmet Emin (2019). An investigation of non-destructive testing techniques for concrete structures. University of Birmingham. M.Sc.

Angelopoulos, Nikolaos (2017). Damage detection and damage evolution monitoring of composite materials for naval applications using acoustic emission testing. University of Birmingham. Ph.D.

Jantara Junior, Valter Luiz (2019). Damage mechanics and condition monitoring of wind turbine gearbox materials. University of Birmingham. Ph.D.

Meng, Xing (2019). Development of an acoustic emission monitoring system for crack detection during arc welding. University of Birmingham. Ph.D.

Hamarat, Mehmet Zahid (2023). Dynamic behaviours and fragility modelling of railway turnouts. University of Birmingham. Ph.D.

Shi, Shengrun (2015). Evaluating the structural integrity of high strength low alloy steels considered for shipbuilding using acoustic emission. University of Birmingham. M.Res.

Nieves Bogonez, Francisco Daniel (2014). Fibre spreading and impregnation monitoring. University of Birmingham. M.Res.

King, David Gareth (2018). Fibre-optic sensor development for process monitoring of epoxy resins. University of Birmingham. Ph.D.

Oliveira de Melo, Andre Luis ORCID: https://orcid.org/0000-0002-1186-6403 (2023). Hybrid numerical-analytical approach for predicting the vertical levelling loss of track geometry in a heavy-haul railway. University of Birmingham. Ph.D.

Hajiabady, Siavash (2018). Integrated condition monitoring of industrial wind turbines. University of Birmingham. Ph.D.

Huang, Zheng (2017). Integrated railway remote condition monitoring. University of Birmingham. Ph.D.

Culwick, Richard (2023). Intelligent real-time monitoring of critical rail infrastructure. University of Birmingham. Ph.D.

Zhou, Jun (2017). Investigation of surface engineering and monitoring for reliable wind turbine gearboxes. University of Birmingham. Ph.D.

Nieves Bogonez, Francisco Daniel (2017). Manufacturing and characterisation of a fibre optic acoustic emission sensor. University of Birmingham. Ph.D.

Roshanmanesh, Sanaz (2019). Methods and tools for optimisation of operational reliability and condition monitoring of large-scale industrial wind and tidal turbines. University of Birmingham. Ph.D.

Cheputeh, Ni-Asri (2023). On modelling of the structural integrity of rails and crossings. University of Birmingham. Ph.D.

Amini, Arash (2016). Online condition monitoring of railway wheelsets. University of Birmingham. Ph.D.

Payne, Jessica (2023). Qualitative condition monitoring of rail steel. University of Birmingham. M.Sc.

Krusuansombat, Panukorn (2023). Quantifying the damage of in-service rolling stock wheelsets using remote condition monitoring. University of Birmingham. Ph.D.

Kongpuang, Manwika (2022). Reliability-base monitoring and maintenance of urban railway turnout using acoustic emission. University of Birmingham. Ph.D.

Shi, Shengrun (2019). Remote condition monitoring of structural integrity of rails and crossings using acoustic emission technique. University of Birmingham. Ph.D.

Ning, Weili (2015). Structural health condition monitoring of carbon-fibre based composite materials using acoustic emission techniques. University of Birmingham. M.Sc.

Yilmazer, Pinar (2013). Structural health condition monitoring of rails using acoustic emission techniques. University of Birmingham. M.Res.

Willberry, James Owen (2022). The development of fibre-optic acoustic emission sensors for structural health monitoring. University of Birmingham. Ph.D.

Khan, Inam Ur Rahman ORCID: https://orcid.org/0000-0001-8836-1465 (2020). The fractionation, carbonisation and characterisation of electro-spun lignin fibres. University of Birmingham. Ph.D.

Bacioiu, Daniel (2019). Vision-based Monitoring System for High Quality TIG Welding. University of Birmingham. Ph.D.