SCADA data based condition monitoring of wind turbines

  • Ke-Sheng Wang Vishal S. Sharma Zhen-You Zhang
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  • 1. Department of Production and Quality Engineering, Norwegian
    University and Science and Technology, Trondheim, Norway
    2. Department of Industrial and Production Engineering, Dr. B .R.
    Ambedkar National Institute of Technology, Jalandhar, Punjab,
    India

Received date: 2014-01-14

  Online published: 2014-02-17

Abstract

Wind turbines (WTs) are quite expensive pieces of equipment in power industry. Maintenance and repair is a critical activity which also consumes lots of time
and effort, hence making it a costly affair. Carefully planning the maintenance based upon condition of the equipment would make the process reasonable. Mostly the WTs are equipped with some kind of condition monitoring device/system, which provides the information about the device to the central data base i.e., supervisory control and data acquisition (SCADA) data base. These devices/systems make use of data processing techniques/methods in order to detect and predict faults. The information provided by condition monitoring equipments keeps on recoding in the SCADA data base. This paper dwells upon the techniques methods/algorithms developed, to carry out diagnosis and prognosis of the faults, based upon SCADA data. Subsequently data driven approaching for SCADA data interpretation has been reviewed and an artificial intelligence (AI) based framework for fault diagnosis and prognosis of WTs using SCADA data is proposed.

Cite this article

Ke-Sheng Wang Vishal S. Sharma Zhen-You Zhang . SCADA data based condition monitoring of wind turbines[J]. Advances in Manufacturing, 2014 , 2(1) : 61 -69 . DOI: DOI10.1007/s40436-014-0067-0

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