Low Cost Journal,International Peer Reviewed and Refereed Journals,Fast Paper Publication approved journal IJEDR(ISSN 2321-9939) apply for ugc care approved journal, UGC Approved Journal, ugc approved journal, ugc approved list of journal, ugc care journal, care journal, UGC-CARE list, New UGC-CARE Reference List, UGC CARE Journals, ugc care list of journal, ugc care list 2020, ugc care approved journal, ugc care list 2020, new ugc approved journal in 2020, Low cost research journal, Online international research journal, Peer-reviewed, and Refereed Journals, scholarly journals, impact factor 7.37 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool)
INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

Current Issue

Call For Papers
July 2022

Volume 10 | Issue 3
Last Date : 29 July 2022
Review Results: Within 12-20 Days

For Authors

Archives

Indexing Partner

Research Area

LICENSE

Paper Details
Paper Title
A decision Tree Based Approach for Data Analysis and Fault Prediction For Wind Turbine Using SCADA dataset
Authors
  Roheela Amin,  Sushma Gupta,  Muheet Ahmed Butt,  Majid Zaman

Abstract
The main objective of Supervisory Control and Data Acquisition (SCADA) is to give a means to the human operator to control and to command a highly automated process. Supervisory control and data acquisition systems (SCADA) are widely used in industries for supervisory control and data acquisition of industrial processes. It has also revolutionized the field of data sciences in a much inevitable manner. The communication between the control centre of SCADA and the remote station takes place by various communication channels such as optical fibre cables, microwave technology and power line carrier communication. The presence of such an efficient system give rise to certain faults results in malfunction of such systems. As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine fault before they reach a catastrophic stage is critical to reduce the operational and maintenance cost due to unnecessary scheduled maintenance. To this end, it is important to be able to perform maintenance before it’s needed. Instead, by performing complex analysis of existing data from turbine’s supervisory control and data acquisition system (SCADA) system, valuable insights into turbine performance can be obtained at a much lower cost. This paper proposes a methodology of fault prediction for wind turbine based on stored SCADA data set using decision tree approach. Fault analysis and diagnosis of faults help in protecting both hardware and software of devices employed in SCADA based systems. On the basis of information received, the SCADA operator is in a position to take important decision related to smooth and faultless generation, transmission and distribution of power. The proposed research provides insight analysis for relationship ships of various attributes like rotor speed, turbine speed, wind speed, power and output of the dataset and also provides fault analysis using Decision Tree Data Mining approach on the said dataset care of various parameters.

Keywords- SCADA System, Wind Turbine, Decision Tree Algorithm
Publication Details
Unique Identification Number - IJEDR1804091
Page Number(s) - 509-518
Pubished in - Volume 6 | Issue 4 | December 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Roheela Amin,  Sushma Gupta,  Muheet Ahmed Butt,  Majid Zaman,   "A decision Tree Based Approach for Data Analysis and Fault Prediction For Wind Turbine Using SCADA dataset", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.509-518, December 2018, Available at :http://www.ijedr.org/papers/IJEDR1804091.pdf
Share This Article


Article Preview

ISSN Details




DOI Details



Providing A digital object identifier by DOI
How to get DOI?

For Reviewer /Referral (RMS)

Important Links

NEWS & Conference

Digital Library

Our Social Link

© Copyright 2022 IJEDR.ORG All rights reserved