Faris Elasha

Dr

    Calculated based on number of publications stored in Pure and citations from Scopus
    20142022

    Research activity per year

    Personal profile

    Biography

     

    Faris Elasha is Senior Lecturer in Dynamics, he Joined Coventry University on September 2015. Previously he was Research Fellow at Cranfield University. Faris has over 10 years experience as a Mechanical Engineer in Power Generation Industry, through his previous career, he has participated in, and headed, many teams for Power stations maintenance and overhauls management. Faris has First class degree in Mechanical Engineering from Sudan University of Science and Technology (BSc), MSc (Distinction) in Mechanical Engineering Design from The University of Manchester and a Ph.D. in Mechanical Engineering from Cranfield University. Faris research area is rotating machines diagnosis and prognosis. Recent involvement in the renewables area includes contributions towards the design of the first condition monitoring system for tidal turbines.

     

    Research:

     

    Condition monitoring, diagnosis, prognosis, and intelligent health management are effective means to reducing the downtime and maintenance cost and improving the reliability of machines. These important issues have drawn more and more attention during the last decade and significant research effort is being taken by both academia and industry to advance the technologies for condition monitoring, diagnosis, prognosis, and health management of rotating machines.

    Dr Elasha research Goal is to undertake applied research and development with the aim of advancing the scope and the sensitivity of machinery fault detection, diagnosis, prognosis, performance and emissions monitoring. His current research investigates Machine diagnostics and prognostics; Asset integrity and management; Gearbox dynamics and design.

     

    Area of Expertise:

     

    • Health Monitoring Techniques for Rotating Machinery
    • Finite Element (FE) modelling
    • Condition Monitoring and Aging Management of Structures
    • Vibration-based diagnosis for rotating machines
    • Advance Signal Processing

    Research Interests

    Rotating Equipment; Dynamics and Vibration; Asset integrity and management; Reliability and Failure analysis; Condition Monitoring and Prognosis

    Expertise related to UN Sustainable Development Goals

    In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

    • SDG 7 - Affordable and Clean Energy

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