Optimisation of data acquisition in wind turbines with data-driven conversion functions for sensor measurements
Financiación H2020 / H2020 Funds
Resumen: Operation and Maintenance (O&M;) is an important cost driver of modern wind turbines. Condition monitoring (CM) allows the implementation of predictive O&M; strategies helping to reduce costs. In this work a novel approach for wind turbine condition monitoring is proposed focusing on synergistic effects of coexisting sensing technologies. The main objective is to understand the predictability of signals using information from other measurements recorded at different locations of the turbine. The approach is based on a multi-step procedure to pre-process data, train a set of conversion functions and evaluate their performance. A subsequent sensitivity analysis measuring the impact of the input variables on the predicted response reveals hidden relationships between signals. The concept feasibility is tested in a case study using Supervisory Control And Data Acquisition (SCADA) data from an offshore turbine.
Idioma: Inglés
DOI: 10.1016/j.egypro.2017.10.386
Año: 2017
Publicado en: Energy procedia 137 (2017), 571-578
ISSN: 1876-6102

Factor impacto SCIMAGO:

Financiación: info:eu-repo/grantAgreement/EC/H2020/642108/EU/Advanced Wind Energy Systems Operation and Maintenance Expertise/AWESOME
Tipo y forma: Article (Published version)
Área (Departamento): Área Ingeniería Eléctrica (Dpto. Ingeniería Eléctrica)

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 Record created 2017-12-22, last modified 2019-04-26

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