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A hybrid prognostic methodology for tidal turbine gearboxes

© 2017 Elsevier Ltd 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.
- Swansea University United Kingdom
- Coventry University United Kingdom
- De Montfort University United Kingdom
- London South Bank University United Kingdom
- Coventry University United Kingdom
690, Gearbox, Life prediction, Prognosis, Health management, Diagnosis, Tidal turbines
690, Gearbox, Life prediction, Prognosis, Health management, Diagnosis, Tidal turbines
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).24 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
