Application of machine learning in condition monitoring

About this project

Condition monitoring of industrial machinery is gaining importance due to the need to increase machine reliability and decrease the possible loss of production due to machine breakdown. In this work we adapt an efficient machine learning based approach to detect faults of an industrial oil pump using wavelet transform and genetic algorithm. This work has been done in collaboration with a local oil refinery.

Lead researcher

Dr Saeed Shiry Ghidary


I hold a Ph.D. in Robotics from Kobe University. With 20 years of teaching experience in AI and Robotics, I have published numerous papers. My research interests include Robotics, AI, machine learning, telerobotics, mobile robots, and theoretical ML

Saeed's profile
in the UK for Quality Education

Sustainable Development Goal 4, Times Higher Education Impact Rankings 2023

for Career Prospects

Whatuni Student Choice Awards 2023

for Facilities

Whatuni Student Choice Awards 2023

for Social Inclusion

The Times and The Sunday Times Good University Guide 2023

of Research Impact is ‘Outstanding’ or ‘Very Considerable’

Research Excellence Framework 2021

of Research is “Internationally Excellent” or “World Leading”

Research Excellence Framework 2021

Four Star Rating

QS Star Ratings 2021