NDLI: Automated on-line fault prognosis for wind turbine pitch systems using supervisory control and data acquisition

Content Provider	IET Digital Library
Author	Chen, Bindi Matthews, Peter C. Tavner, Peter J.
Abstract	Current wind turbine (WT) studies focus on improving their reliability and reducing the cost of energy, particularly when WTs are operated offshore. A supervisory control and data acquisition (SCADA) system is a standard installation on larger WTs, monitoring all major WT sub-assemblies and providing important information. Ideally, a WT's health condition or state of the components can be deduced through rigorous analysis of SCADA data. Several programmes have been made for that purposes; however, the resulting cost savings are limited because of the data complexity and relatively low number of failures that can be easily detected in early stages. This study proposes a new method for analysing WT SCADA data by using an a priori knowledge-based adaptive neuro-fuzzy inference system with the aim to achieve automated detection of significant pitch faults. The proposed approach has been applied to the pitch data of two different designs of 26 variable pitch, variable speed and 22 variable pitch, fixed speed WTs, with two different types of SCADA system, demonstrating the adaptability of the approach for application to a variety of techniques. Results are evaluated using confusion matrix analysis and a comparison study of the two tests is addressed to draw conclusions.
Starting Page	503
Ending Page	513
Page Count	11
ISSN	17521416
Volume Number	9
e-ISSN	17521424
Issue Number	Issue 5, Jul (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/9/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2014.0181
Journal	IET Renewable Power Generation
Publisher Date	2015-02-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	A Priori Knowledge-based Adaptive Neuro-fuzzy Inference System Automated Online Fault Prognosis Confusion Matrix Analysis Cost Savings Data Complexity Energy Cost Reduction Failure Analysis Fuzzy Neural Nets Fuzzy Reasoning Knowledge Engineering Technique Neural Computing Technique Pitch Fault Automated Detection Power Engineering Computing Power Generation Fault Power Generation Reliability Power System Economics Power System Managemen Power System Operation Reliability SCADA System Supervisory Control And Data Acquisition System Wind Power Plant Wind Turbine Wind Turbine Pitch System WT Health Condition WT SCADA Data Analysis WT Sub-assemblies
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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