Resumen: Wind turbine failure and downtime can often compromise the profitability of a wind farm due to their high impact on the operation and maintenance (O&M;) costs. Early detection of failures can facilitate the changeover from corrective maintenance towards a pre- dictive approach. This paper presents a cost-effective methodology to combine various alarm analysis techniques, using data from the Supervisory Control and Data Acquisition (SCADA) system, in order to detect component failures. The approach categorises the alarms according to a reviewed taxonomy, turning overwhelming data into valuable information to assess component status. Then, different alarms analysis techniques are applied for two purposes: the evaluation of the SCADA alarm system capability to detect failures, and the investigation of the relation between components faults being followed by failure occurrences in others. Various case studies are presented and discussed. The study highlights the relationship between faulty behaviour in different components and between failures and adverse environmental conditions. Idioma: Inglés DOI: 10.1088/1742-6596/753/7/072019 Año: 2016 Publicado en: Journal of physics. Conference series 753 (2016), 072019 [10 pp.] ISSN: 1742-6588 Factor impacto SCIMAGO: 0.24 - Physics and Astronomy (miscellaneous) (Q3)