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mcanyesilli/WPT_EEMD_ML_Machining v1.3

Melih C. Yesilli; Firas A. Khasawneh


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  <identifier identifierType="DOI">10.5281/zenodo.3706729</identifier>
  <creators>
    <creator>
      <creatorName>Melih C. Yesilli</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8224-7397</nameIdentifier>
      <affiliation>Michigan State University</affiliation>
    </creator>
    <creator>
      <creatorName>Firas A. Khasawneh</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7817-7445</nameIdentifier>
      <affiliation>Michigan State University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>mcanyesilli/WPT_EEMD_ML_Machining v1.3</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>machine learning, transfer learning, chatter detection, wavelet packet transform, empirical mode decomposition</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-03-11</date>
  </dates>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3706729</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsSupplementTo">https://github.com/mcanyesilli/WPT_EEMD_ML_Machining/tree/v1.3</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3455845</relatedIdentifier>
  </relatedIdentifiers>
  <version>v1.3</version>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This repository includes the documentation for the Python codes that extract features by using Wavelet Packet Transform (WPT) and Ensemble Empirical Mode Decomposition (EEMD) and diagnose chatter in turning process for different cutting configurations. Algorithms are based on the methods explained in&amp;nbsp;&lt;a href="https://doi.org/10.1016/j.cirpj.2019.11.003"&gt;this paper&lt;/a&gt;&amp;nbsp;The experimental data in both raw and processed format can be found in&amp;nbsp;&lt;a href="http://dx.doi.org/10.17632/hvm4wh3jzx.1"&gt;Mendeley repository&lt;/a&gt;.&lt;/p&gt;</description>
  </descriptions>
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