Electrical fault detection using mechanical signals

Christopher J. Crabtree, Donatella Zappalá, Peter J. Tavner, Simon I. Hogg

Research output: Contribution to conferencePaperScientificpeer-review

Abstract

Wind turbine condition monitoring is gaining in importance as operators and developers move towards larger, further offshore, less accessible wind farms. However, condition monitoring is made highly challenging by the variable speed, variable load nature of wind turbines. Electrical faults, in the form of brush gear or slip ring damage contribute significantly to downtime yet operators have little experience of detecting these faults in the field. This paper subjects a physical test rig to rotor electrical unbalances and applies a frequency tracking algorithm to mechanical and electrical monitoring signals to compare the sensitivity of the various signals. The results shows that the total electrical power signal gives the clearest response to rotor electrical unbalance, as expected, but that torque measurements could be a viable alternative. Speed signal analysis showed much lower sensitivity to unbalance than torque or power measurements.

Original languageEnglish
Publication statusPublished - 1 Jan 2014
Externally publishedYes
EventEuropean Wind Energy Association Conference and Exhibition 2014, EWEA 2014 - Barcelona, Spain
Duration: 10 Mar 201413 Mar 2014

Conference

ConferenceEuropean Wind Energy Association Conference and Exhibition 2014, EWEA 2014
CountrySpain
CityBarcelona
Period10/03/1413/03/14

Keywords

  • Condition monitoring
  • Frequency tracking
  • Generator faults
  • Wind

Fingerprint Dive into the research topics of 'Electrical fault detection using mechanical signals'. Together they form a unique fingerprint.

Cite this