Crack Detection and Diagnosis for Wind Turbines Using Naive

International Journal of Emerging Technology and Innovative Engineering Volume 5, Issue 5, May 2019

6 Pages Posted: 22 Apr 2019

See all articles by Nageswari S

Nageswari S

Bharath Niketan Engineering College

Pallavi M. Goel

Galgotias University

Divya P

CMS College of Engineering

Date Written: April 19, 2019

Abstract

Wind control is depicting the procedure by which wind is utilized to create electricity. It is a renewable source of energy that helps to cut down the pollution. The drawback in wind energy generation is the high maintenance costs associated with mechanical faults. Keeping in mind the end goal to decrease these effects have been incorporated blame discovery framework in wind turbines known as Fault identification and Diagnosis framework. The proposed strategy is a Naive Bayes classifier identification framework to recognize the wind turbine's split exactness. This framework depends on probabilistic classifier with solid impedance presumption of each blame case. The fundamental thought is to utilize a specific number of Bayes classifiers to manages diverse kinds of shortcomings influencing the wind turbine. The distinctive process was researched to recognize the breaks in the breeze turbine. The recreation comes about to demonstrate the best exhibitions of the proposed approach.

Keywords: Wind Turbine, Naive Baye's Classifier

Suggested Citation

S, Nageswari and Goel, Pallavi M. and P, Divya, Crack Detection and Diagnosis for Wind Turbines Using Naive (April 19, 2019). International Journal of Emerging Technology and Innovative Engineering Volume 5, Issue 5, May 2019 , Available at SSRN: https://ssrn.com/abstract=3375197

Nageswari S (Contact Author)

Bharath Niketan Engineering College ( email )

Pallavi M. Goel

Galgotias University ( email )

Plot No.2, Sector 17-A
Yamuna Expressway
Greater Noida, UT Uttar Pradesh 201306
India

Divya P

CMS College of Engineering ( email )

5A/2 EXTENSION NO 1,
Rasipuram
Namakkal, Tamil Nadu 637408
India

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