Machine Learning-Driven Predictive Maintenance Framework for Anomaly Detection and Prognostics in Wind Farm Operations-Reference-Cited by-同舟云学术

Machine Learning-Driven Predictive Maintenance Framework for Anomaly Detection and Prognostics in Wind Farm Operations

Author:

Nuvvula Ramakrishna S S¹,Kumar Polamarasetty P²,S Theetchenya³,Ahammed Syed Riyaz⁴,R Hushein⁵,J M Babu⁶,Ali Ahmed⁷

Affiliation:

1. NMAM Institute of Technology, NITTE Deemed to be University),Department of Electrical and Electronics Engineering,Karnataka,India

2. GMR Institute of Technology,Department of Electrical and Electronics Engineering,Rajam,India

3. Sona College of Technology,Department of Computer Science and Engineering,Salem,Tamilnadu,India

4. NMAM Institute of Technology, NITTE Deemed to be University),Department of Electronics & Communication Engineering,Karnataka,India

5. Vel Tech RanagarajanDr.Sagunthala R&D Institute of Science and Technology,Department of Electronics and Communication,Chennai,India

6. Vel Tech RanagarajanDr.Sagunthala R&D Institute of Science and Technology,Department of Mechanical Engineering,Chennai,India

7. University of Johannesburg,Department of Electrical and Electronic Engineering Technology,South Africa

Publisher

IEEE

Link

Reference12 articles.

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2. Wind turbine control systems: principles, modelling and gain scheduling design;Bossanyi,2003

3. Wind Turbine Operation and Maintenance: A Review of Current Technologies;Sheng;Energies,2019

4. Wind Turbine Reliability and Maintainability: A Practitioner’s Approach;Rabinovici,2018