{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T04:53:51Z","timestamp":1781758431394,"version":"3.54.5"},"reference-count":43,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T00:00:00Z","timestamp":1697760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004862","name":"Zhejiang Sci-Tech University","doi-asserted-by":"publisher","award":["11133132612005"],"award-info":[{"award-number":["11133132612005"]}],"id":[{"id":"10.13039\/501100004862","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004862","name":"Zhejiang Sci-Tech University","doi-asserted-by":"publisher","award":["LGYJY2021005"],"award-info":[{"award-number":["LGYJY2021005"]}],"id":[{"id":"10.13039\/501100004862","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004862","name":"Zhejiang Sci-Tech University","doi-asserted-by":"publisher","award":["11130531282004"],"award-info":[{"award-number":["11130531282004"]}],"id":[{"id":"10.13039\/501100004862","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Applied Fundamental Project from Longgang Institute of Zhejiang Sci-Tech University","award":["11133132612005"],"award-info":[{"award-number":["11133132612005"]}]},{"name":"Applied Fundamental Project from Longgang Institute of Zhejiang Sci-Tech University","award":["LGYJY2021005"],"award-info":[{"award-number":["LGYJY2021005"]}]},{"name":"Applied Fundamental Project from Longgang Institute of Zhejiang Sci-Tech University","award":["11130531282004"],"award-info":[{"award-number":["11130531282004"]}]},{"DOI":"10.13039\/501100004862","name":"\u201cYoung Talent\u201d Support Project","doi-asserted-by":"publisher","award":["11133132612005"],"award-info":[{"award-number":["11133132612005"]}],"id":[{"id":"10.13039\/501100004862","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004862","name":"\u201cYoung Talent\u201d Support Project","doi-asserted-by":"publisher","award":["LGYJY2021005"],"award-info":[{"award-number":["LGYJY2021005"]}],"id":[{"id":"10.13039\/501100004862","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004862","name":"\u201cYoung Talent\u201d Support Project","doi-asserted-by":"publisher","award":["11130531282004"],"award-info":[{"award-number":["11130531282004"]}],"id":[{"id":"10.13039\/501100004862","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Tool wear condition significantly influences equipment downtime and machining precision, necessitating the exploration of a more accurate tool wear state identification technique. In this paper, the wavelet packet thresholding denoising method is used to process the acquired multi-source signals and extract several signal features. The set of features most relevant to the tool wear state is screened out by the support vector machine recursive feature elimination (SVM-RFE). Utilizing these selected features, we propose a tool wear state identification model, which utilizes an improved northern goshawk optimization (INGO) algorithm to optimize the support vector machine (SVM), hereby referred to as INGO-SVM. The simulation tests reveal that INGO demonstrates superior convergence efficacy and stability. Furthermore, a milling wear experiment confirms that this approach outperforms five other methods in terms of recognition accuracy, achieving a remarkable accuracy rate of 97.9%.<\/jats:p>","DOI":"10.3390\/s23208591","type":"journal-article","created":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T07:25:22Z","timestamp":1697786722000},"page":"8591","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Tool Wear State Identification Based on SVM Optimized by the Improved Northern Goshawk Optimization"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8446-2933","authenticated-orcid":false,"given":"Jiaqi","family":"Wang","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3046-6170","authenticated-orcid":false,"given":"Zhong","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"},{"name":"Longgang Institute of Zhejiang Sci-Tech University, Wenzhou 325802, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2135-1814","authenticated-orcid":false,"given":"Ji","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenqi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/S0166-3615(96)00075-9","article-title":"A review of machine vision sensors for tool condition monitoring","volume":"34","author":"Kurada","year":"1997","journal-title":"Comput. 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