Diagnosis of the rotor condition in electric motors operating in mining facilities through the analysis of motor currents

Jose Antonino-Daviu, Alfredo Quijano López, Martin Rubbiolo, Vicente Climente-Alarcon

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)


Predictive maintenance of electric motors is a topic of increasing importance in many industrial applications. The mining industry is not an exception; many electric motors operating in mining facilities are critical machines and their unexpected failures may imply significant losses and can be hazardous for the users. Due to these facts, an increasing research effort has been dedicated to investigate on new techniques that are able to provide a reliable diagnostic of the motor condition. Over recent years, monitoring of electrical quantities (e.g. motor currents) has emerged as a very attractive option for determining the health of several motor parts (rotor, eccentricities, bearings) due to its very interesting advantages: possibility of remote motor monitoring, non-invasive nature, simple application, broad fault coverage The traditional methods based on analysis of motor currents during steady-state operation (MCSA) are being complemented, when not replaced, by modern approaches relying on transient analysis (ATCSA). This work presents several case studies referred to large motors operating in mining facilities. The combined application of both previous methods enables to reach reliable diagnoses of some parts of the motor, such as the rotor. The paper includes some controversial cases, where the classical methods failed due to the variable nature of the driven loads.

Original languageEnglish
Title of host publication2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
Number of pages8
ISBN (Electronic)9781509048946
Publication statusPublished - 8 Nov 2017
MoE publication typeA4 Article in a conference publication
EventIEEE Industry Applications Society Annual Meeting - Cincinnati, United States
Duration: 1 Oct 20175 Oct 2017

Publication series

NameConference record of the Industry Applications Society Annual Meeting
ISSN (Print)0197-2618


ConferenceIEEE Industry Applications Society Annual Meeting
Abbreviated titleIAS
CountryUnited States


  • Fault detection
  • Fault diagnosis
  • Induction motors
  • Mining
  • Reliability
  • Rotor
  • Transient analysis
  • Wavelet.

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