{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T19:41:24Z","timestamp":1772221284156,"version":"3.50.1"},"reference-count":20,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T00:00:00Z","timestamp":1727827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China Special Equipment Inspection and Research Institute","award":["2021YFF0600605"],"award-info":[{"award-number":["2021YFF0600605"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper introduces a lightweight flame detection algorithm, enhancing the accuracy and speed of gas-flame state recognition in low-pressure environments using an improved YOLOv8n model. This method effectively resolves the aforementioned problems. Firstly, GhostNet is integrated into the backbone to form the GhostConv module, reducing the model\u2019s computational parameters. Secondly, the C2f module is improved by integrating RepGhost, forming the C2f_RepGhost module, which performs deep convolution, extends feature dimensions, and simplifies the inference structure. Additionally, the CBAM attention mechanism is added to enhance the model\u2019s ability to capture fine-grained features of flames in both channel and spatial dimensions. The replacement of CIoU with WIoU improves the sensitivity and accuracy of the model\u2019s regression loss. Experimental results on a simulated dataset of the theoretical testbed indicate that compared to the original model, the proposed improvements achieve good performance in low-pressure flame state detection. The model\u2019s parameter count is reduced by 12.64%, the total floating-point operations are reduced by 12.2%, and the detection accuracy is improved by 21.2%. Although the detection frame rate slightly decreases, it still meets real-time detection requirements. The experimental results demonstrate that the feasibility and effectiveness of the proposed algorithm have been significantly improved.<\/jats:p>","DOI":"10.3390\/s24196383","type":"journal-article","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T03:57:08Z","timestamp":1727841428000},"page":"6383","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Improved YOLOv8 for Gas-Flame State Recognition under Low-Pressure Conditions"],"prefix":"10.3390","volume":"24","author":[{"given":"Qingyi","family":"Sai","sequence":"first","affiliation":[{"name":"College of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9649-1728","authenticated-orcid":false,"given":"Jin","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Degui","family":"Bi","sequence":"additional","affiliation":[{"name":"College of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingshu","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.applthermaleng.2016.09.095","article-title":"Comparative study on the combustion characteristics of an atmospheric induction stove in the plateau and plain regions of China","volume":"111","author":"Zhou","year":"2017","journal-title":"Appl. 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