{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T01:25:02Z","timestamp":1781659502475,"version":"3.54.5"},"reference-count":27,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,8]],"date-time":"2025-03-08T00:00:00Z","timestamp":1741392000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["51674134"],"award-info":[{"award-number":["51674134"]}]},{"name":"National Natural Science Foundation of China","award":["LJKQZ20222448"],"award-info":[{"award-number":["LJKQZ20222448"]}]},{"name":"National Natural Science Foundation of China","award":["LJ212410144076"],"award-info":[{"award-number":["LJ212410144076"]}]},{"name":"National Natural Science Foundation of China","award":["LJ232410144074"],"award-info":[{"award-number":["LJ232410144074"]}]},{"name":"Fundamental Research Funds for the Universities of Liaoning Province","award":["51674134"],"award-info":[{"award-number":["51674134"]}]},{"name":"Fundamental Research Funds for the Universities of Liaoning Province","award":["LJKQZ20222448"],"award-info":[{"award-number":["LJKQZ20222448"]}]},{"name":"Fundamental Research Funds for the Universities of Liaoning Province","award":["LJ212410144076"],"award-info":[{"award-number":["LJ212410144076"]}]},{"name":"Fundamental Research Funds for the Universities of Liaoning Province","award":["LJ232410144074"],"award-info":[{"award-number":["LJ232410144074"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>To enhance the maintenance efficiency and operational stability of rolling bearings, this work establishes a methodology for bearing life prediction, employing digital twin systems to evaluate the remaining useful life of rolling bearings. A comprehensive digital twin-integrated model for the entire lifecycle of rolling bearings is constructed using the Modelica language. This model generates sufficient and reliable lifecycle twin data for the bearings. Due to the symmetrical physical structure of the bearings, the generated twin data also have symmetry. Based on this characteristic of bearings, a remaining useful life (RUL) prediction algorithm is developed using a recurrent neural network (RNN), specifically an improved gated recurrent unit (GRU) model. An optimization algorithm is employed to adjust the hyperparameters and determine the initial fault point of the bearing. A multi-feature dataset is constructed, effectively enhancing the precision and reliability of lifespan estimation. Based on existing measured data of the bearing\u2019s entire lifecycle, the rolling bearing\u2019s digital twin-integrated model parameters are updated. Through the parameter degradation component of the twin, the lifecycle twin data of the rolling bearing are generated. By combining twin data with actual measurement data, this method addresses the limitations of traditional approaches in situations where complete lifecycle data of bearings are scarce, providing reliable technical support for the intelligent maintenance and optimization of rolling bearings.<\/jats:p>","DOI":"10.3390\/sym17030406","type":"journal-article","created":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T08:46:41Z","timestamp":1741596401000},"page":"406","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Residual Life Prediction of Rolling Bearings Driven by Digital Twins"],"prefix":"10.3390","volume":"17","author":[{"given":"Jiayi","family":"Fan","sequence":"first","affiliation":[{"name":"School of Mechatronics Engineering, Shenyang Aerospace University, Shenyang 110136, China"},{"name":"Key Laboratory of Rapid Development & Manufacturing Technology for Aircraft, Shenyang Aerospace University, Ministry of Education, Shenyang 110136, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Liaoning Technical University, Fuxin 123000, China"},{"name":"Liaoning Provincial Key Laboratory of Large-Scale Mining Equipment, Fuxin 123000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minghao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.cirp.2008.03.026","article-title":"Degradation state model-based prognosis for proactively maintaining product performance","volume":"57","author":"Lung","year":"2008","journal-title":"CIRP Ann.-Manuf. 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