Advanced analytics for detection and diagnosis of false alarms and faults: A real case study-Reference-Cited by-同舟云学术

Advanced analytics for detection and diagnosis of false alarms and faults: A real case study

Published:2019-07-23 Issue:11 Volume:22 Page:1622-1635
ISSN:1095-4244
Container-title:Wind Energy
language:en
Short-container-title:Wind Energy

Author:

Pliego Marugán Alberto¹^ORCID,García Márquez Fausto Pedro²^ORCID

Affiliation:

1. CUNEF‐Ingenium, Colegio Universitario de Estudios Financieros de Madrid Madrid Spain

2. Ingenium Research Group, Universidad Castilla‐La Mancha 13071 Ciudad Real Spain

Funder

Spanish Ministerio de Economía y Competitividad

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2393

Reference61 articles.

1. Global wind report annual market update2014. Accessed on: December 2015.http://Http://www.Gwec.Net/wp-content/uploads/2015/03/gwec_global_wind_2014_report_lr.Pdf.

2. Offshore Wind Turbines: Reliability, availability and maintenance

3. Dirt and mud detection and diagnosis on a wind turbine blade employing guided waves and supervised learning classifiers

4. Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis

5. Structural health monitoring for delamination detection and location in wind turbine blades employing guided waves

Cited by 49 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. K-nearest neighbour and K-fold cross-validation used in wind turbines for false alarm detection;Sustainable Futures;2023-12

2. Nonstationarity in correlation matrices for wind turbine SCADA‐data;Wind Energy;2023-06-13

3. False alarm detection in wind turbine by classification models;Advances in Engineering Software;2023-03

4. False Alarm Detection with K-NN Algorithm for Wind Turbine Maintenance Management;Lecture Notes on Data Engineering and Communications Technologies;2023

5. Automated Identification of Photovoltaic Panels with Hot Spots by Using Convolutional Neural Networks;Lecture Notes on Data Engineering and Communications Technologies;2023