{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:17:16Z","timestamp":1760059036216,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T00:00:00Z","timestamp":1747353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Economic Affairs, Innovation, Digital and Energy (MWIDE)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>In practical machine learning (ML) applications, covariate shifts and dependencies can significantly impact model robustness and prediction quality, leading to performance degradation under distribution shifts. In industrial settings, it is crucial to account for covariates during the design of experiments to ensure reliable generalization. The presented dataset of undamaged and artificially damaged cylindrical roller bearings is designed to address the lack of data resources for targeting domain and distribution shifts in this field. The dataset considers multiple key covariates, including mounting position, load, and rotational speed. Each covariate consists of multiple levels optimized for group-based cross-validation. This allows the user to exclude specific groups in the training to validate and test the algorithm. Using this approach, algorithms can be evaluated for their robustness and the effect on the model caused by distribution shifts, allowing their generalization capabilities to be studied under realistic conditions.<\/jats:p>","DOI":"10.3390\/data10050077","type":"journal-article","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T06:57:28Z","timestamp":1747378648000},"page":"77","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Machine Learning Dataset of Artificial Inner Ring Damage on Cylindrical Roller Bearings Measured Under Varying Cross-Influences"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6844-0382","authenticated-orcid":false,"given":"Christopher","family":"Schnur","sequence":"first","affiliation":[{"name":"Lab for Measurement Technology, Saarland University, 66123 Saarbr\u00fccken, Germany"},{"name":"Centre for Mechatronics and Automation Technology gGmbH, 66121 Saarbr\u00fccken, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3937-1752","authenticated-orcid":false,"given":"Payman","family":"Goodarzi","sequence":"additional","affiliation":[{"name":"Lab for Measurement Technology, Saarland University, 66123 Saarbr\u00fccken, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6558-6554","authenticated-orcid":false,"given":"Yannick","family":"Robin","sequence":"additional","affiliation":[{"name":"Lab for Measurement Technology, Saarland University, 66123 Saarbr\u00fccken, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2830-1166","authenticated-orcid":false,"given":"Julian","family":"Schauer","sequence":"additional","affiliation":[{"name":"Lab for Measurement Technology, Saarland University, 66123 Saarbr\u00fccken, Germany"},{"name":"Centre for Mechatronics and Automation Technology gGmbH, 66121 Saarbr\u00fccken, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3060-5177","authenticated-orcid":false,"given":"Andreas","family":"Sch\u00fctze","sequence":"additional","affiliation":[{"name":"Lab for Measurement Technology, Saarland University, 66123 Saarbr\u00fccken, Germany"},{"name":"Centre for Mechatronics and Automation Technology gGmbH, 66121 Saarbr\u00fccken, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,16]]},"reference":[{"key":"ref_1","unstructured":"(2017). 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Rolling Bearing Damage\u2014Recognition of Damage and Bearing Inspection. Available online: https:\/\/www.schaeffler.com\/remotemedien\/media\/_shared_media\/08_media_library\/01_publications\/schaeffler_2\/publication\/downloads_18\/wl_82102_3_de_en.pdf."},{"key":"ref_18","unstructured":"Schaeffler Technologies AG & Co. KG (2025, February 24). Pendelkugellager 1206-TVH. Available online: https:\/\/medias.schaeffler.de\/de\/produkt\/rotary\/waelz\u2013und-gleitlager\/kugellager\/pendelkugellager\/1206-tvh\/p\/365837,."},{"key":"ref_19","unstructured":"Schaeffler Technologies AG & Co. KG (2025, February 24). Zylinderrollenlager NU207-E-XL-TVP2. Available online: https:\/\/medias.schaeffler.de\/en\/product\/rotary\/rolling-and-plain-bearings\/roller-bearings\/cylindrical-roller-bearings\/nu207-e-xl-tvp2\/p\/368768."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/10\/5\/77\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:33:43Z","timestamp":1760031223000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/10\/5\/77"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,16]]},"references-count":19,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,5]]}},"alternative-id":["data10050077"],"URL":"https:\/\/doi.org\/10.3390\/data10050077","relation":{},"ISSN":["2306-5729"],"issn-type":[{"type":"electronic","value":"2306-5729"}],"subject":[],"published":{"date-parts":[[2025,5,16]]}}}