{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:40:52Z","timestamp":1776811252480,"version":"3.51.2"},"reference-count":19,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"4","license":[{"start":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T00:00:00Z","timestamp":1741651200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Science and Technology Project of Zhejiang Provincial Energy Group Company LTD","award":["ZNKJ-2022-030"],"award-info":[{"award-number":["ZNKJ-2022-030"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational Methods in Sciences and Engineering"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:p>As coal-fired power transitions from a primary energy source to a fundamental and system-regulating source, utility boilers are increasingly required to operate under more flexible conditions. This shift inevitably introduces risks of expansion failure in water walls. This paper proposes a dictionary learning (DL)-based expansion warning model to address this issue. To mitigate the impact of the randomly selected initial dictionary, kernel principal component analysis (KPCA) is integrated into DL to create a deterministic approach for optimizing the initial dictionary. Additionally, a three-grade warning framework is established using multiple reconstruction error thresholds to improve the accuracy of expansion warning. A 300\u00a0MW power unit is used as a study case for warning model validation. The model is built with 25 operational variables, including three expansions in the X, Y, and Z directions and other operational parameters of the utility boiler, respectively. The results demonstrate that the warning rates of the three-grade warning model align well with actual offset values, confirming the effectiveness of the DL-based graded expansion warning model.<\/jats:p>","DOI":"10.1177\/14727978251324142","type":"journal-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T02:59:52Z","timestamp":1741748392000},"page":"3751-3762","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Dictionary learning-based graded warning of water wall expansion of utility boilers"],"prefix":"10.66113","volume":"25","author":[{"given":"Leya","family":"Zhou","sequence":"first","affiliation":[{"name":"Zhejiang Zheneng Zhenhai Power Generation Co.,Ltd., Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3404-6603","authenticated-orcid":false,"given":"Fan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang Energy R&amp;D Institute Co.,Ltd., Hangzhou, China"},{"name":"Zhejiang Key Laboratory of Energy Conservation&amp;Pollutant Control Technology for Thermal Power, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shi","family":"He","sequence":"additional","affiliation":[{"name":"Zhejiang Zheneng Zhenhai Power Generation Co.,Ltd., Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ningning","family":"Zhao","sequence":"additional","affiliation":[{"name":"Zhejiang Energy R&amp;D Institute Co.,Ltd., Hangzhou, China"},{"name":"Zhejiang Key Laboratory of Energy Conservation&amp;Pollutant Control Technology for Thermal Power, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Lou","sequence":"additional","affiliation":[{"name":"Zhejiang Zheneng Zhenhai Power Generation Co.,Ltd., Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yimin","family":"Cui","sequence":"additional","affiliation":[{"name":"Zhejiang Energy R&amp;D Institute Co.,Ltd., Hangzhou, China"},{"name":"Zhejiang Key Laboratory of Energy Conservation&amp;Pollutant Control Technology for Thermal Power, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","published-online":{"date-parts":[[2025,3,11]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eiar.2023.107313"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.gloei.2023.04.004"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2024.130977"},{"key":"e_1_3_4_5_2","volume-title":"Blue book on the development of new power systems","author":"Nea","year":"2023","unstructured":"Nea. 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