A hybrid prognostic methodology for tidal turbine gearboxes

Date

2017-07-24

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Publisher

Elsevier

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Article

ISSN

0960-1481

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Citation

Faris Elasha, David Mba, Michael Togneri, Ian Masters, Joao Amaral Teixeira, A hybrid prognostic methodology for tidal turbine gearboxes, Renewable Energy, Volume 114, 2017, Pages 1051-1061

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 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.

Description

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Github

Keywords

Tidal turbines, Prognosis, Gearbox, Life prediction, Diagnosis, Health management

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Attribution 4.0 International (CC BY 4.0) You are free to: Share — copy and redistribute the material in any medium or format Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

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