{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T18:28:33Z","timestamp":1772735313083,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,11,28]],"date-time":"2020-11-28T00:00:00Z","timestamp":1606521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan","award":["2016YFC0600908"],"award-info":[{"award-number":["2016YFC0600908"]}]},{"name":"Shanxi Talent Special (Outstanding Talents Science and Technology Innovation) Project","award":["201605D211007"],"award-info":[{"award-number":["201605D211007"]}]},{"name":"Shanxi Natural Science Foundation","award":["201801D121177"],"award-info":[{"award-number":["201801D121177"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The mine hoist sheave bearing is a large heavy-duty bearing, located in a derrick of tens of meters. Aiming at the difficulty of sheave bearing fault diagnosis, a combined fault-diagnosis method based on the improved complete ensemble EMD (ICEEMDAN) energy entropy and support vector machine (SVM) optimized by artificial fish swarm algorithm (AFSA) was proposed. Different location of the bearing defect will result in different frequency components and different amplitude energy of the frequency. According to this feature, the position of the bearing defect can be determined by calculating the ICEEMDAN energy entropy of different vibration signals. In view of the difficulty in selecting the penalty factor and radial basis kernel parameter in the SVM model, the AFSA was used to optimize them. The experimental results show that the accuracy rate of the optimized fault-diagnosis model is improved by 10% and the diagnostic accuracy rate is 97.5%.<\/jats:p>","DOI":"10.3390\/e22121347","type":"journal-article","created":{"date-parts":[[2020,11,29]],"date-time":"2020-11-29T21:00:57Z","timestamp":1606683657000},"page":"1347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Application of ICEEMDAN Energy Entropy and AFSA-SVM for Fault Diagnosis of Hoist Sheave Bearing"],"prefix":"10.3390","volume":"22","author":[{"given":"Ziming","family":"Kou","sequence":"first","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fen","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, North University of China, Taiyuan 030051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6648-6419","authenticated-orcid":false,"given":"Tengyu","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.measurement.2017.02.033","article-title":"Rolling element bearing fault diagnosis under slow speed operation using wavelet de-noising","volume":"103","author":"Mishra","year":"2017","journal-title":"Measurement"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1016\/j.ymssp.2011.08.002","article-title":"Early fault diagnosis of rotating machinery based on wavelet packets\u2014Empirical mode decomposition feature extraction and neural network","volume":"27","author":"Bin","year":"2012","journal-title":"Mech. 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