Dataset Open Access
Dorst, Tanja
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.3929385</identifier> <creators> <creator> <creatorName>Dorst, Tanja</creatorName> <givenName>Tanja</givenName> <familyName>Dorst</familyName> </creator> </creators> <titles> <title>Sensor data set of 3 electromechanical cylinder at ZeMA testbed (2kHz)</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2019</publicationYear> <subjects> <subject>dynamic measurement, measurement uncertainty, sensor network, digital sensors, MEMS, machine learning, European Union (EU), Horizon 2020, EMPIR</subject> </subjects> <dates> <date dateType="Issued">2019-05-10</date> </dates> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3929385</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.2702225</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/met4fof</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p><strong>General information on the data set</strong></p> <p>The data set was generated at the ZeMA testbed. A working cycle lasts 2.8s and consists of a forward stroke, a waiting time and a return stroke. The data set does not consist of the entire working cycles. Only one second of the return stroke of each working cycle is used.</p> <p>&nbsp;</p> <p><strong>Structure of the data</strong></p> <ul> <li>data saved in three HDF5 file as a 3D-matrix, one file is for one axis</li> <li>one row represents one second of the return stroke of one working cycle<br> axis 3: 6292 cycles<br> axis 5: 6083 cycles<br> axis 7: 5732 cycles</li> <li>one column represents one datapoint of the cycle, that is resampled to 2 kHz (2000 columns)</li> <li>one page represent one sensor (11 pages: 11 sensors)</li> </ul> <p>&nbsp;</p> <p><strong>Allocation of the pages to the sensors</strong></p> <p>page 1: microphone<br> page 2: acceleration plain bearing<br> page 3: acceleration piston rod<br> page 4: acceleration ball bearing<br> page 5: axial force<br> page 6: pressure<br> page 7: velocity<br> page 8: active current<br> page 9: motor current phase 1<br> page 10: motor current phase 2<br> page 11: motor current phase 3</p> <p>&nbsp;</p> <p><strong>Remark</strong></p> <p>The datasets are not in SI units. For conversion, you can use the PDF documentation.</p> <p>&nbsp;</p> <p><strong>Further information</strong></p> <p>For an introduction and tutorial to this data, a set of Jupyter notebooks is available <a href="https://github.com/harislulic/ZeMA-machine-learning-tutorials">here</a>. These notebooks contain Python code and a documentation of example machine learning tasks and analysis of this data set. In the near future, these will be extended to also include uncertainties in the input data.</p></description> </descriptions> </resource>
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