{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T22:57:02Z","timestamp":1768085822413,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T00:00:00Z","timestamp":1696464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Technology Fund Project of Guizhou Provincial Science and Technology Department","award":["LH Zi (2014) 7452"],"award-info":[{"award-number":["LH Zi (2014) 7452"]}]},{"name":"Technology Fund Project of Guizhou Provincial Science and Technology Department","award":["KY (2020) 117"],"award-info":[{"award-number":["KY (2020) 117"]}]},{"name":"Technology Fund Project of Guizhou Provincial Science and Technology Department","award":["52020-2022-PT-02"],"award-info":[{"award-number":["52020-2022-PT-02"]}]},{"name":"Technology Fund Project of Guizhou Provincial Science and Technology Department","award":["LPSSYKYJJ202310"],"award-info":[{"award-number":["LPSSYKYJJ202310"]}]},{"name":"Guizhou Provincial Department of Education","award":["LH Zi (2014) 7452"],"award-info":[{"award-number":["LH Zi (2014) 7452"]}]},{"name":"Guizhou Provincial Department of Education","award":["KY (2020) 117"],"award-info":[{"award-number":["KY (2020) 117"]}]},{"name":"Guizhou Provincial Department of Education","award":["52020-2022-PT-02"],"award-info":[{"award-number":["52020-2022-PT-02"]}]},{"name":"Guizhou Provincial Department of Education","award":["LPSSYKYJJ202310"],"award-info":[{"award-number":["LPSSYKYJJ202310"]}]},{"name":"Liupanshui Science and Technology Bureau","award":["LH Zi (2014) 7452"],"award-info":[{"award-number":["LH Zi (2014) 7452"]}]},{"name":"Liupanshui Science and Technology Bureau","award":["KY (2020) 117"],"award-info":[{"award-number":["KY (2020) 117"]}]},{"name":"Liupanshui Science and Technology Bureau","award":["52020-2022-PT-02"],"award-info":[{"award-number":["52020-2022-PT-02"]}]},{"name":"Liupanshui Science and Technology Bureau","award":["LPSSYKYJJ202310"],"award-info":[{"award-number":["LPSSYKYJJ202310"]}]},{"name":"High level Talent Research Project of Liupanshui Normal University","award":["LH Zi (2014) 7452"],"award-info":[{"award-number":["LH Zi (2014) 7452"]}]},{"name":"High level Talent Research Project of Liupanshui Normal University","award":["KY (2020) 117"],"award-info":[{"award-number":["KY (2020) 117"]}]},{"name":"High level Talent Research Project of Liupanshui Normal University","award":["52020-2022-PT-02"],"award-info":[{"award-number":["52020-2022-PT-02"]}]},{"name":"High level Talent Research Project of Liupanshui Normal University","award":["LPSSYKYJJ202310"],"award-info":[{"award-number":["LPSSYKYJJ202310"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In the existing bearing remaining useful life (RUL)-prediction model based on deep learning, the advantages and disadvantages of the extracted features are evaluated by the prediction accuracy; thus, the analytical ability of the features is poor. At the same time, the change of working conditions has a great influence on prediction accuracy. To overcome these limitations, a prediction method of bearing RUL based on feature evaluation and deep transfer learning is proposed. The proposed model can solve the above problems: (1) a method of feature evaluation and selection for bearing life prediction based on trend consistency index was designed. (2) In this study, a domain adversarial transfer model based on feature condition mapping is proposed to overcome the second limitation. Experimental results show that this method is superior to the existing bearing evaluation and prediction methods.<\/jats:p>","DOI":"10.3390\/s23198254","type":"journal-article","created":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T09:14:22Z","timestamp":1696497262000},"page":"8254","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Transfer Prediction Method of Bearing Remaining Useful Life Based on Deep Feature Evaluation under Different Working Conditions"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2376-5124","authenticated-orcid":false,"given":"Yongzhi","family":"Liu","sequence":"first","affiliation":[{"name":"School of Mining and Mechanical Engineering, Liupanshui Normal University, Liupanshui 553004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yisheng","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 610031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3615-5616","authenticated-orcid":false,"given":"Kai","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1016\/j.ymssp.2017.11.016","article-title":"Machinery health prognostics: A systematic review from data acquisition to RUL prediction","volume":"104","author":"Lei","year":"2017","journal-title":"Mech. 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