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Study of Feature-Selection-Algorithms with powerful 3D insights for Wind Turbine Failure Prediction using SCADA Data

Juan José Cárdenas Araujo ITESTIT S.L., Spain STUDY OF FEATURE-SELECTION-ALGORITHMS WITH POWERFUL 3D INSIGHTS FOR WIND TURBINE FAILURE PREDICTION USING SCADA DATA Abstract ID: 368  Poster code: PO.066 | Download poster: PDF file (0.45 MB) | Download full paper: PDF (1.00 MB)

Presenter's biography

Biographies are supplied directly by presenters at WindEurope 2016 and are published here unedited

Juan José Cárdenas A. is PhD from “Universitat Politècnica de Catalunya” and Electronic Engineer from “Universidad del Valle”. He is a data scientist with wide experience in using data mining techniques together with statistic while applied to energy sector. He has carried out research in energy efficiency enhancement for buildings and smart cities from a data-driven perspective. Nowadays, he is Researcher and Data Scientist in SmartIve, where he is looking for improving predictive algorithms for early fault detection and diagnosis of wind turbines.

Abstract

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