{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T11:47:45Z","timestamp":1774352865620,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T00:00:00Z","timestamp":1708905600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51975433"],"award-info":[{"award-number":["51975433"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2023DJC173"],"award-info":[{"award-number":["2023DJC173"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hubei Province science and technology plan","award":["51975433"],"award-info":[{"award-number":["51975433"]}]},{"name":"Hubei Province science and technology plan","award":["2023DJC173"],"award-info":[{"award-number":["2023DJC173"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To address the challenges faced in the prediction of rolling bearing life, where temporal signals are affected by noise, making fault feature extraction difficult and resulting in low prediction accuracy, a method based on optimal time\u2013frequency spectra and the DenseNet-ALSTM network is proposed. Firstly, a signal reconstruction method is introduced to enhance vibration signals. This involves using the CEEMDAN deconvolution method combined with the Teager energy operator for signal reconstruction, aiming to denoise the signals and highlight fault impacts. Subsequently, a method based on the snake optimizer (SO) is proposed to optimize the generalized S-transform (GST) time\u2013frequency spectra of the enhanced signals, obtaining the optimal time\u2013frequency spectra. Finally, all sample data are transformed into the optimal time\u2013frequency spectrum set and input into the DenseNet-ALSTM network for life prediction. The comparison experiment and ablation experiment show that the proposed method has high prediction accuracy and ideal prediction performance. The optimization terms used in different contexts in this paper are due to different optimization methods, specifically the CEEMDAN method.<\/jats:p>","DOI":"10.3390\/s24051497","type":"journal-article","created":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T03:34:04Z","timestamp":1708918444000},"page":"1497","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Life Prediction of Rolling Bearing Based on Optimal Time\u2013Frequency Spectrum and DenseNet-ALSTM"],"prefix":"10.3390","volume":"24","author":[{"given":"Jintao","family":"Chen","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China"}]},{"given":"Baokang","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China"}]},{"given":"Mengya","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China"}]},{"given":"Bowen","family":"Ning","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,26]]},"reference":[{"key":"ref_1","first-page":"107572","article-title":"Review on Remaining Useful Life Prediction of Rolling Bearing","volume":"42","author":"Zhang","year":"2023","journal-title":"Mech. 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