Dataset Open Access

Dataset for Sensorless Drive Diagnosis

Martyna,Bator


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        <foaf:name>Martyna,Bator</foaf:name>
        <foaf:givenName>Bator</foaf:givenName>
        <foaf:familyName>Martyna</foaf:familyName>
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            <foaf:name>inIT – Institute Industrial ITOstwestfalen-Lippe University of Applied Sciences</foaf:name>
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    <dct:title>Dataset for Sensorless Drive Diagnosis</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2015</dct:issued>
    <dcat:keyword>current drive signals</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2015-12-21</dct:issued>
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    <dct:description>&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;</dct:description>
    <dct:description>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.</dct:description>
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