{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T16:20:43Z","timestamp":1784996443765,"version":"3.55.0"},"reference-count":31,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T00:00:00Z","timestamp":1713830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2023JBZX006"],"award-info":[{"award-number":["2023JBZX006"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2022YJS155"],"award-info":[{"award-number":["2022YJS155"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["242102241053"],"award-info":[{"award-number":["242102241053"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific and Technological Research Projects, Henan Province","award":["2023JBZX006"],"award-info":[{"award-number":["2023JBZX006"]}]},{"name":"Scientific and Technological Research Projects, Henan Province","award":["2022YJS155"],"award-info":[{"award-number":["2022YJS155"]}]},{"name":"Scientific and Technological Research Projects, Henan Province","award":["242102241053"],"award-info":[{"award-number":["242102241053"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In recent years, most research on bearing fault diagnosis has assumed that the source domain and target domain data come from the same machine. The differences in equipment lead to a decrease in diagnostic accuracy. To address this issue, unsupervised domain adaptation techniques have been introduced. However, most cross-device fault diagnosis models overlook the discriminative information under the marginal distribution, which restricts the performance of the models. In this paper, we propose a bearing fault diagnosis method based on envelope spectrum and conditional metric learning. First, envelope spectral analysis is used to extract frequency domain features. Then, to fully utilize the discriminative information from the label distribution, we construct a deep Siamese convolutional neural network based on conditional metric learning to eliminate the data distribution differences and extract common features from the source and target domain data. Finally, dynamic weighting factors are employed to improve the convergence performance of the model and optimize the training process. Experimental analysis is conducted on 12 cross-device tasks and compared with other relevant methods. The results show that the proposed method achieves the best performance on all three evaluation metrics.<\/jats:p>","DOI":"10.3390\/s24092674","type":"journal-article","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T10:34:05Z","timestamp":1713868445000},"page":"2674","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A New Method for Bearing Fault Diagnosis across Machines Based on Envelope Spectrum and Conditional Metric Learning"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9891-5967","authenticated-orcid":false,"given":"Xu","family":"Yang","sequence":"first","affiliation":[{"name":"School of Intelligent Manufacturing, Nanyang Institute of Technology, Nanyang 473004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfeng","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yupeng","family":"Jin","sequence":"additional","affiliation":[{"name":"School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW 2050, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6958-5292","authenticated-orcid":false,"given":"Zhongchao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing, Nanyang Institute of Technology, Nanyang 473004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.mechmachtheory.2019.03.008","article-title":"Load distribution and friction torque in four-point contact slewing bearings considering manufacturing errors and ring flexibility","volume":"137","author":"Heras","year":"2019","journal-title":"Mech. 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