• español
    • English
  • English 
    • español
    • English
  • Login
View Item 
  •   DSpace Home
  • Investigación
  • Departamento de Administración de Empresas
  • Área de Organización de Empresas
  • View Item
  •   DSpace Home
  • Investigación
  • Departamento de Administración de Empresas
  • Área de Organización de Empresas
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A New Fault Location Approach for Acoustic Emission Techniques in Wind Turbines

Thumbnail
View/Open
201513 - A new fault.pdf (1.946Mb)
Date
2016-01-12
Author
García Márquez, Fausto Pedro
Gómez Muñoz, Carlos Quiterio
Metadata
Show full item record
Abstract
The renewable energy industry is undergoing continuous improvement and development worldwide, wind energy being one of the most relevant renewable energies. This industry requires high levels of reliability, availability, maintainability and safety (RAMS) for wind turbines. The blades are critical components in wind turbines. The objective of this research work is focused on the fault detection and diagnosis (FDD) of the wind turbine blades. The FDD approach is composed of a robust condition monitoring system (CMS) and a novel signal processing method. CMS collects and analyses the data from different non-destructive tests based on acoustic emission. The acoustic emission signals are collected applying macro-fiber composite (MFC) sensors to detect and locate cracks on the surface of the blades. Three MFC sensors are set in a section of a wind turbine blade. The acoustic emission signals are generated by breaking a pencil lead in the blade surface.This method is used to simulate the acoustic emission due to a breakdown of the composite fibers. The breakdown generates a set of mechanical waves that are collected by the MFC sensors. A graphical method is employed to obtain a system of non-linear equations that will be used for locating the emission source. This work demonstrates that a fiber breakage in the wind turbine blade can be detected and located by using only three low cost sensors. It allows the detection of potential failures at an early stages, and it can also reduce corrective maintenance tasks and downtimes and increase the RAMS of the wind turbine.
URI
http://hdl.handle.net/10578/13695
Collections
  • Área de Organización de Empresas

© Universidad de Castilla-La Mancha
Rectorado
C/ Altagracia, 50 13071
Ciudad Real Tfno. 926 29 53 00
Fax: 926 29 53 01

Copyright | Documentation | Other Resources | Contact Us
Ruidera

¿RUIdeRA?

Federcc
DSpace
 

 

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister

© Universidad de Castilla-La Mancha
Rectorado
C/ Altagracia, 50 13071
Ciudad Real Tfno. 926 29 53 00
Fax: 926 29 53 01

Copyright | Documentation | Other Resources | Contact Us
Ruidera

¿RUIdeRA?

Federcc
DSpace