Dirt and mud detection and diagnosis on a wind turbine blade employing guided waves and supervised learning classifiers-Reference-Cited by-同舟云学术

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

Published:2019-04 Issue: Volume:184 Page:2-12
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Arcos Jiménez Alfredo,Gómez Muñoz Carlos Quiterio,García Márquez Fausto Pedro

Funder

Spanish Ministerio de Economía y Competitividad

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference74 articles.

1. Big data and web intelligence for condition monitoring: a case study on wind turbines;Gómez Muñoz,2015

2. A novel approach to fault detection and diagnosis on wind turbines;Gómez Muñoz;Global Nest J,2014

3. Models for non-destructive inspection data;Simola;Reliab Eng Syst Safety,1998

4. Fatigue reliability analysis of the jacket support structure for offshore wind turbine considering the effect of corrosion and inspection;Dong;Reliab Eng Syst Safety,2012

5. Inspection and structural health monitoring techniques for concentrated solar power plants;Papaelias;Renew Energy,2016

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