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A health condition model for wind turbine monitoring through neural networks and proportional hazard models
Mazidi, Peyman; Du, Mian; Bertling Tjemberg, Lina; Sanz Bobi, Miguel Ángel (2017-10-01)In this paper, a parametric model for health condition monitoring of wind turbines (HCWT) is developed. The study is based on the assumption that a wind turbine’s (WT) health condition can be modeled through three features: ... -
A performance and maintenance evaluation framework for wind turbines
Mazidi, Peyman; Du, Mian; Bertling Tjemberg, Lina; Sanz Bobi, Miguel ÁngelIn this paper, a data driven framework for performance and maintenance evaluation (PAME) of wind turbines (WT) is proposed. To develop the framework, SCADA data of WTs are adopted and several parameters are carefully ... -
On advancements and challenges in asset management for HVDC systems: a machine learning perspective
Rajora, GopaL Lal; Bertling Tjemberg, Lina; Sanz Bobi, Miguel ÁngelIn the context of global climate goals and the transition to sustainable energy, modern energy transportation and distribution systems play a crucial role. Electricity transportation and distribution systems would not ... -
Performance analysis and anomaly detection in wind turbines based on neural networks and principal component analysis
Mazidi, Peyman; Bertling Tjemberg, Lina; Sanz Bobi, Miguel ÁngelThis paper proposes an approach for maintenance management of wind turbines based on their life. The proposed approach uses performance analysis and anomaly detection (PAAD) which can detect anomalies and point out the ... -
Wind turbine prognostics and maintenance management based on a hybrid approach of neural networks and proportional hazards model
Mazidi, Peyman; Bertling Tjemberg, Lina; Sanz Bobi, Miguel Ángel (2017-04-01)This paper proposes an approach for stress condition monitoring and maintenance assessment in wind turbines (WT) through large amounts of collected data from supervisory control and data acquisition (SCADA) system. The ...