---
res:
  bibo_abstract:
  - Systems for process automation become increasingly complex and also tend to be
    composed of autonomous subsystems, which is strongly driven by the progress made
    in information technology. An active field of research is the implementation of
    monitoring and control at sub-system level using cognitive approaches. In this
    paper we present a method for autonomous and sensorless condition monitoring of
    an electric drive train. Based on experiment design we measured phase currents
    of a physical demonstrator device including mechanical defects and extracted signal
    features using proper orthogonal decomposition. In favor of classification of
    different defect states we performed a linear discriminant analysis, which yields
    appropriate data for a Fuzzy-Pattern-Classification algorithm. As a result we
    were able to identify different reference defect states as well as previously
    unknown states.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Christian
      foaf_name: Bayer, Christian
      foaf_surname: Bayer
  - foaf_Person:
      foaf_givenName: Martyna
      foaf_name: Bator, Martyna
      foaf_surname: Bator
      foaf_workInfoHomepage: http://www.librecat.org/personId=46440
  - foaf_Person:
      foaf_givenName: Olaf
      foaf_name: Enge-Rosenblatt, Olaf
      foaf_surname: Enge-Rosenblatt
  - foaf_Person:
      foaf_givenName: Uwe
      foaf_name: Mönks, Uwe
      foaf_surname: Mönks
      foaf_workInfoHomepage: http://www.librecat.org/personId=1825
  - foaf_Person:
      foaf_givenName: Alexander
      foaf_name: Dicks, Alexander
      foaf_surname: Dicks
      foaf_workInfoHomepage: http://www.librecat.org/personId=1853
  - foaf_Person:
      foaf_givenName: Volker
      foaf_name: Lohweg, Volker
      foaf_surname: Lohweg
      foaf_workInfoHomepage: http://www.librecat.org/personId=1804
    orcid: 0000-0002-3325-7887
  bibo_doi: ' 10.1109/ETFA.2013.6648126'
  dct_date: 2013^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/978-1-4799-0862-2
  dct_language: eng
  dct_publisher: 18th IEEE International Conference on Emerging Technologies and Factory
    Automation (ETFA)@
  dct_title: Sensorless Drive Diagnosis Using Automated Feature Extraction, Significance
    Ranking and Reduction.@
...