Dataset Open Access

Dataset for Sensorless Drive Diagnosis


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  <identifier identifierType="DOI">10.5281/zenodo.35577</identifier>
      <affiliation>inIT – Institute Industrial ITOstwestfalen-Lippe University of Applied Sciences</affiliation>
    <title>Dataset for Sensorless Drive Diagnosis</title>
    <subject>current drive signals</subject>
    <date dateType="Issued">2015-12-21</date>
  <resourceType resourceTypeGeneral="Dataset"/>
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    <rights rightsURI="">Creative Commons Zero v1.0 Universal</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;Electric current drive signals are measured. The drive has intact and defective components. This results in 11 different classes with different conditions. Each condition has been measured several times by different operating conditions, this means by different speeds, load moments and load forces. The current signals are measured with a current probe and an oscilloscope on two phases.&lt;/p&gt;</description>
    <description descriptionType="Other">Relevant paper:

[1]	F. Paschke, C. Bayer, M. Bator, U. Mönks, A. Dicks, O. Enge-Rosenblatt, and V. Lohweg, “Sensorlose Zustandsüberwachung an Synchronmotoren,” in Proceedings 23. Workshop Computational Intelligence, Karlsruhe: KIT Scientific Publishing, 2013, pp. 211–225.
[2]	C. Bayer, M. Bator, U. Mönks, A. Dicks, O. Enge-Rosenblatt, and V. Lohweg, “Sensorless Drive Diagnosis Using Automated Feature Extraction, Significance Ranking and Reduction,” in 18th IEEE Int. Conf. on Emerging Technologies and Factory Automation (ETFA 2013): IEEE, 2013, pp. 1–4.</description>
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