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A hybrid prognostic methodology for tidal turbine gearboxes

Faris Elasha, David Mba, Michael Togneri Orcid Logo, Ian Masters Orcid Logo, Joao Amaral Teixeira

Renewable Energy, Volume: 114, Issue: Part B, Pages: 1051 - 1061

Swansea University Authors: Michael Togneri Orcid Logo, Ian Masters Orcid Logo

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DOI (Published version): 10.1016/j.renene.2017.07.093

Abstract

Tidal energy is one of promising solutions for reducing greenhouse gas emissions and it is estimated that 100 TWh of electricity could be produced every year from suitable sites around the world. Although premature gearbox failures have plagued the wind turbine industry, and considerable research ef...

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Published in: Renewable Energy
ISSN: 0960-1481
Published: 2017
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa34753
first_indexed 2017-07-26T14:30:01Z
last_indexed 2021-01-15T03:54:28Z
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spelling 2021-01-14T12:45:42.2615432 v2 34753 2017-07-26 A hybrid prognostic methodology for tidal turbine gearboxes 7032d5a521c181cea18dbb759e1ffdeb 0000-0002-6820-1680 Michael Togneri Michael Togneri true false 6fa19551092853928cde0e6d5fac48a1 0000-0001-7667-6670 Ian Masters Ian Masters true false 2017-07-26 ACEM Tidal energy is one of promising solutions for reducing greenhouse gas emissions and it is estimated that 100 TWh of electricity could be produced every year from suitable sites around the world. Although premature gearbox failures have plagued the wind turbine industry, and considerable research efforts continue to address this challenge, tidal turbine gearboxes are expected to experience higher mechanical failure rates given they will experience higher torque and thrust forces. In order to minimize the maintenance cost and prevent unexpected failures there exists a fundamental need for prognostic tools that can reliably estimate the current health and predict the future condition of the gearbox.This paper presents a life assessment methodology for tidal turbine gearboxes which was developed with synthetic data generated using a blade element momentum theory (BEMT) model. The latter has been used extensively for performance and load modelling of tidal turbines. The prognostic model developed was validated using experimental data. Journal Article Renewable Energy 114 Part B 1051 1061 0960-1481 Tidal Turbines; Prognosis; Gearbox; Life Prediction; Diagnosis; Health management 1 12 2017 2017-12-01 10.1016/j.renene.2017.07.093 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2021-01-14T12:45:42.2615432 2017-07-26T10:49:29.9746831 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Faris Elasha 1 David Mba 2 Michael Togneri 0000-0002-6820-1680 3 Ian Masters 0000-0001-7667-6670 4 Joao Amaral Teixeira 5 34753__17562__5acf427fd1d944b380ad438f3f290dfe.pdf 34753.pdf 2020-06-23T10:38:19.6522682 Output 2329014 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution License (CC-BY). true eng http://creativecommons.org/licenses/by/4.0/
title A hybrid prognostic methodology for tidal turbine gearboxes
spellingShingle A hybrid prognostic methodology for tidal turbine gearboxes
Michael Togneri
Ian Masters
title_short A hybrid prognostic methodology for tidal turbine gearboxes
title_full A hybrid prognostic methodology for tidal turbine gearboxes
title_fullStr A hybrid prognostic methodology for tidal turbine gearboxes
title_full_unstemmed A hybrid prognostic methodology for tidal turbine gearboxes
title_sort A hybrid prognostic methodology for tidal turbine gearboxes
author_id_str_mv 7032d5a521c181cea18dbb759e1ffdeb
6fa19551092853928cde0e6d5fac48a1
author_id_fullname_str_mv 7032d5a521c181cea18dbb759e1ffdeb_***_Michael Togneri
6fa19551092853928cde0e6d5fac48a1_***_Ian Masters
author Michael Togneri
Ian Masters
author2 Faris Elasha
David Mba
Michael Togneri
Ian Masters
Joao Amaral Teixeira
format Journal article
container_title Renewable Energy
container_volume 114
container_issue Part B
container_start_page 1051
publishDate 2017
institution Swansea University
issn 0960-1481
doi_str_mv 10.1016/j.renene.2017.07.093
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 1
active_str 0
description Tidal energy is one of promising solutions for reducing greenhouse gas emissions and it is estimated that 100 TWh of electricity could be produced every year from suitable sites around the world. Although premature gearbox failures have plagued the wind turbine industry, and considerable research efforts continue to address this challenge, tidal turbine gearboxes are expected to experience higher mechanical failure rates given they will experience higher torque and thrust forces. In order to minimize the maintenance cost and prevent unexpected failures there exists a fundamental need for prognostic tools that can reliably estimate the current health and predict the future condition of the gearbox.This paper presents a life assessment methodology for tidal turbine gearboxes which was developed with synthetic data generated using a blade element momentum theory (BEMT) model. The latter has been used extensively for performance and load modelling of tidal turbines. The prognostic model developed was validated using experimental data.
published_date 2017-12-01T07:12:26Z
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score 11.133746

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