<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">10.21979/N9/UCIK2K</identifier><creators><creator><creatorName nameType="Personal">Ragab, Mohamed</creatorName><givenName>Mohamed</givenName><familyName>Ragab</familyName><nameIdentifier nameIdentifierScheme="ORCID">0000-0002-2138-4395</nameIdentifier><affiliation>Nanyang Technological University</affiliation></creator></creators><titles><title>Paderborn Domain Generalization Version</title></titles><publisher>DR-NTU (Data)</publisher><publicationYear>2022</publicationYear><subjects><subject>Engineering</subject><subject>Domain Generalization, Fault Diagnosis</subject></subjects><contributors><contributor contributorType="ContactPerson"><contributorName nameType="Personal">Ragab, Mohamed</contributorName><givenName>Mohamed</givenName><familyName>Ragab</familyName><affiliation>Nanyang Technological University</affiliation></contributor></contributors><dates><date dateType="Submitted">2022-03-06</date><date dateType="Updated">2022-10-07</date></dates><resourceType resourceTypeGeneral="Dataset">Time series</resourceType><relatedIdentifiers><relatedIdentifier relationType="IsCitedBy" relatedIdentifierType="DOI">10.1109/TIM.2022.3154000</relatedIdentifier></relatedIdentifiers><sizes><size>252822409</size><size>7016</size><size>252822409</size><size>252822409</size><size>451</size><size>2188</size><size>3379</size><size>12838</size><size>13442</size><size>2660</size><size>279456809</size><size>279456809</size><size>797</size><size>3422</size><size>279456809</size><size>4092</size><size>3023</size><size>2580</size></sizes><formats><format>application/octet-stream</format><format>application/x-ipynb+json</format><format>application/octet-stream</format><format>application/octet-stream</format><format>text/x-matlab</format><format>text/x-matlab</format><format>text/x-matlab</format><format>application/x-ipynb+json</format><format>application/x-ipynb+json</format><format>application/x-ipynb+json</format><format>application/octet-stream</format><format>application/octet-stream</format><format>text/x-matlab</format><format>text/x-matlab</format><format>application/octet-stream</format><format>text/x-matlab</format><format>text/x-matlab</format><format>text/x-matlab</format></formats><version>1.0</version><rightsList><rights rightsURI="info:eu-repo/semantics/openAccess"/><rights rightsURI="http://creativecommons.org/licenses/by-nc/4.0">CC BY-NC 4.0</rights></rightsList><descriptions><description descriptionType="Abstract">This dataset is generated the KAT data center in Paderborn University with the sampling rate of 64 KHz (Lessmeier et al. 2016). The damages
were generated using both artificial and natural ways. More
specifically, an electric discharge machine (EDM), a drilling,
and an electric engraving were used to manually produce
the artificial faults. While the natural damages were caused
by using accelerated run-to-failure tests. The data collection
process for both types of damages, i.e., artificial and real,
was exposed under working conditions with different operating
parameters such as loading torque, rotational speed and
radial force. In total, the Paderborn datasets was collect under
6 different operating conditions including 3 conditions with
artificial damages (denoted as domains I, J and K) and 3 conditions
with real damages (denoted as domains L, M, and N).
For example, the loading torque varies from 0.1 to 0.7 Nm
and the radial force varies from 400 to 1000 N, while the
rotational speed is fixed at 1500 RPM. Each operating condition
(i.e., domain) contains three classes, namely, healthy
class, inner fault (IF) class, and outer fault (OF) class. To
prepare the data samples for the Paderborn dataset, we adopted
sliding windows with a fixed length of 5,120 and a shifting
size of 4,096 (Ragab et al. 2021). As such, we generated
12,340 for each artificial domain (i.e., I, J, and K) and 13,640
samples for each real domain (i.e., L, Mand N) respectively.</description></descriptions><geoLocations/><fundingReferences><fundingReference><funderName>Agency for Science, Technology and Research (A*STAR)</funderName><awardNumber>AME Programmatic Funds (Grant No. A20H6b0151)</awardNumber></fundingReference><fundingReference><funderName>Agency for Science, Technology and Research (A*STAR)</funderName><awardNumber>Career Development Award (Grant No. C210112046)</awardNumber></fundingReference></fundingReferences></resource>