{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T23:22:25Z","timestamp":1783552945771,"version":"3.55.0"},"reference-count":23,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T00:00:00Z","timestamp":1714348800000},"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":["U1830133"],"award-info":[{"award-number":["U1830133"]}],"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":["JSGG20220831101402005"],"award-info":[{"award-number":["JSGG20220831101402005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Plan Project","award":["U1830133"],"award-info":[{"award-number":["U1830133"]}]},{"name":"Shenzhen Science and Technology Plan Project","award":["JSGG20220831101402005"],"award-info":[{"award-number":["JSGG20220831101402005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The remaining useful life (RUL) prediction of RF circuits is an important tool for circuit reliability. Data-driven-based approaches do not require knowledge of the failure mechanism and reduce the dependence on knowledge of complex circuits, and thus can effectively realize RUL prediction. This manuscript proposes a novel RUL prediction method based on a gated recurrent unit\u2013convolutional neural network (GRU-CNN). Firstly, the data are normalized to improve the efficiency of the algorithm; secondly, the degradation of the circuit is evaluated using the hybrid health score based on the Euclidean and Manhattan distances; then, the life cycle of the RF circuits is segmented based on the hybrid health scores; and finally, an RUL prediction is carried out for the circuits at each stage using the GRU-CNN model. The results show that the RMSE of the GRU-CNN model in the normal operation stage is only 3\/5 of that of the GRU and CNN models, while the prediction uncertainty is minimized.<\/jats:p>","DOI":"10.3390\/s24092841","type":"journal-article","created":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T10:33:36Z","timestamp":1714386816000},"page":"2841","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Novel Method for Remaining Useful Life Prediction of RF Circuits Based on the Gated Recurrent Unit\u2013Convolutional Neural Network Model"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4215-6201","authenticated-orcid":false,"given":"Wanyu","family":"Yang","sequence":"first","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China"},{"name":"Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China (UESTC), Shenzhen 518000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kunping","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Long","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shulin","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1109\/TETC.2017.2737320","article-title":"In-Field Recovery of RF Circuits from Wearout Based Performance Degradation","volume":"8","author":"Chang","year":"2020","journal-title":"IEEE Trans. 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