{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T16:56:52Z","timestamp":1774803412449,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T00:00:00Z","timestamp":1667347200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020B090927002"],"award-info":[{"award-number":["2020B090927002"]}]},{"name":"Key-Area Research and Development Program of Guangdong Province","award":["52205103"],"award-info":[{"award-number":["52205103"]}]},{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020YFB1709800"],"award-info":[{"award-number":["2020YFB1709800"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2020B090927002"],"award-info":[{"award-number":["2020B090927002"]}],"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":["52205103"],"award-info":[{"award-number":["52205103"]}],"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":["2020YFB1709800"],"award-info":[{"award-number":["2020YFB1709800"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020B090927002"],"award-info":[{"award-number":["2020B090927002"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["52205103"],"award-info":[{"award-number":["52205103"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFB1709800"],"award-info":[{"award-number":["2020YFB1709800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Cutting tool wear state assessment during the manufacturing process is extremely significant. The primary purpose of this study is to monitor tool wear to ensure timely tool change and avoid excessive tool wear or sudden tool breakage, which causes workpiece waste and could even damage the machine. Therefore, an intelligent system, that is efficient and precise, needs to be designed for addressing these problems. In our study, an end-to-end improved fine-grained image classification method is employed for workpiece surface-based tool wear monitoring, which is named efficient channel attention destruction and construction learning (ECADCL). The proposed method uses a feature extraction module to extract features from the input image and its corrupted images, and adversarial learning is used to avoid learning noise from corrupted images while extracting semantic features by reconstructing the corrupted images. Finally, a decision module predicts the label based on the learned features. Moreover, the feature extraction module combines a local cross-channel interaction attention mechanism without dimensionality reduction to characterize representative information. A milling dataset is conducted based on the machined surface images for monitoring tool wear conditions. The experimental results indicated that the proposed system can effectively assess the wear state of the tool.<\/jats:p>","DOI":"10.3390\/s22218416","type":"journal-article","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T03:44:17Z","timestamp":1667360657000},"page":"8416","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Tool Wear Monitoring in Milling Based on Fine-Grained Image Classification of Machined Surface Images"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2157-3003","authenticated-orcid":false,"given":"Jing","family":"Yang","sequence":"first","affiliation":[{"name":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]},{"given":"Jian","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]},{"given":"Tianxiang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]},{"given":"Cheng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7422-714X","authenticated-orcid":false,"given":"Jianqiang","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6977-9700","authenticated-orcid":false,"given":"Tielin","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.worlddev.2016.12.013","article-title":"The Importance of Manufacturing in Economic Development: Has This Changed?","volume":"93","author":"Haraguchi","year":"2017","journal-title":"World Dev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.promfg.2018.07.046","article-title":"Trade-off Analysis of Tool Wear, Machining Quality and Energy Efficiency of Alloy Cast Iron Milling Process","volume":"26","author":"Luan","year":"2018","journal-title":"Procedia Manuf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.asoc.2015.06.023","article-title":"Incremental Learning for Online Tool Condition Monitoring Using Ellipsoid ARTMAP Network Model","volume":"35","author":"Liu","year":"2015","journal-title":"Appl. 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