Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

Model based wind turbine gearbox fault detection on SCADA data

Qiu, Yingning and Infield, David and Feng, Yanhui and Yang, Wenxian and Cao, Mengnan and Sun, Juan and Wang, Hao (2014) Model based wind turbine gearbox fault detection on SCADA data. In: Proceedings of IET Renewable Power Generation conference, 2014. IET.

[img]
Preview
Text (Qiu-etal-IET2014-model-based-wind-turbine-gearbox-fault-detection-on-scada-data)
Qiu_etal_IET2014_model_based_wind_turbine_gearbox_fault_detection_on_scada_data.pdf - Accepted Author Manuscript

Download (341kB) | Preview

Abstract

Developing effective wind turbine fault detection algorithm is not only meaningful for improving wind turbine reliability but also crucial for future intelligent wind farm operation and management. Typical wind turbine gearbox condition monitoring is based on vibration signals, which is effective to detect failures with high frequency signal range. But it may not be effective on low speed components which have low frequency signal characteristic of different failure modes. SCADA system collecting multiple low frequency signals provides a cost-effective way to monitor wind turbines health and performance, while its capability on fault detection is still an open issue. To systematic understand wind turbine systems, this paper presents research results of model based wind turbine gearbox fault detection. Through a detail analysis of thermodynamic process of gearbox lubrication system, a wind turbine drive train model which considers heat transferring mechanism in gearbox lubrication system is built to derive robust relationships between transmission efficiency, temperature, and rotational speed signals of wind turbine gearbox and suggest useful information for lubrication system design and optimization. The result obtained in this work is useful for wind turbine gearbox design and effective algorithm development of fault detection.