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Accurate wear prediction for self-lubricating bearings is crucial for ensuring reliability and safety. However, achieving both physical interpretability and high accuracy in predictive models remains a challenge, as these bearings typically operate under varying load conditions and in high-noise environments. In this article, a hybrid physical damage neural network is proposed for wear prediction. First, a \u201cphysics neuron operator\u201d based on the Archard wear model is designed and embedded into the network to directly compute wear depth. Second, a cumulative damage law is introduced into this operator to quantify the degradation path of the bearing during operation. Finally, the evolution law of wear stages is encoded as a physical constraint in the loss function to compel the network's learning process to follow the true degradation mechanism. To validate the model, a dedicated test platform was built, and a full life cycle degradation dataset for self-lubricating bearings was collected. Experimental results show that the proposed model significantly outperforms existing methods in prediction accuracy. Furthermore, this article provides an in-depth analysis of the model's physical interpretability, revealing its internal working mechanism and significantly enhancing its credibility and generalization ability.<\/jats:p>","DOI":"10.1115\/1.4071182","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T17:28:37Z","timestamp":1771522117000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":35,"title":["A Hybrid Physical Damage Neural Network for Wear Prediction of Self-Lubricating Bearings"],"prefix":"10.1115","volume":"26","author":[{"given":"Shuo","family":"Wang","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0220qvk04","id-type":"ROR","asserted-by":"publisher"}],"name":"Shanghai Jiao Tong University National Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, , \u00a0 ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shichang","family":"Du","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0220qvk04","id-type":"ROR","asserted-by":"publisher"}],"name":"Shanghai Jiao Tong University National Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, , \u00a0 ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Yan","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0220qvk04","id-type":"ROR","asserted-by":"publisher"}],"name":"Shanghai Jiao Tong University National Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, , \u00a0 ,","place":["Shanghai, China, 200240"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Li","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Strength and Structural Integrity, Xian, Shaanxi\u00a0710065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianmin","family":"Chen","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Strength and Structural Integrity, Xian, Shaanxi\u00a0710065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"33","published-online":{"date-parts":[[2026,5,12]]},"reference":[{"issue":"2","key":"2026051213243267000_CIT0001","doi-asserted-by":"publisher","first-page":"021404","DOI":"10.1115\/1.4068914","article-title":"Research on the Influence of Microscale Aspheric Surface on the Contact and Wear Performances of Self-Lubricating Spherical Plain Bearing","volume":"148","author":"Xue","year":"2026","journal-title":"ASME J. 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