Prediction of tool wear on workpiece surface quality based on milling topography analysis

Prediction of tool wear on workpiece surface quality based on milling topography analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prediction of tool wear on workpiece surface quality based on milling topography analysis Wei Zhang, Lei Zhang, Minli Zheng, Kangning Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1472910/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract The surface quality of the workpiece has a great impact on the performance of the product. It has always been a key issue of the manufacturing discipline. The different wear levels of cutting tools determine the surface quality of the workpiece. Therefore, the work of this article is to establish a model for calculate the surface quality of the workpiece after milling. First, by defining the tool wear area S and the wear position angle ψ , the cutting edge line model of the tool is determined. Based on the tool motion trajectory and roughness calculation principle, a milling topography simulation roughness model considering tool wear is obtained. Secondly, the tool wear parameters were calibrated with the help of image detection methods, and the predicted values obtained by the model were compared with the experimental values. The law of the influence of the tool wear area S and the wear position angle ψ on the roughness parameters was obtained. Finally, the least squares support vector machine LS-SVM was used to verify the error of the roughness model of the milling topography simulation, and the result showed that the average error of the model was 8.68%. wear topography simulation roughness least square support vector machine Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 22 Mar, 2022 Reviewers invited by journal 22 Mar, 2022 Editor assigned by journal 22 Mar, 2022 First submitted to journal 21 Mar, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1472910","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":92718349,"identity":"d8aef2c0-081c-4988-91dc-d489dd54f12c","order_by":0,"name":"Wei Zhang","email":"data:image/png;base64,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","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""},{"id":92718347,"identity":"c9922073-080e-490b-8872-3d6400640adf","order_by":1,"name":"Lei Zhang","email":"","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Zhang","suffix":""},{"id":92718348,"identity":"d027056a-a295-4e93-b273-5c10588297f0","order_by":2,"name":"Minli Zheng","email":"","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minli","middleName":"","lastName":"Zheng","suffix":""},{"id":92718350,"identity":"26660e79-6f6d-4988-b23a-596330016cc5","order_by":3,"name":"Kangning Li","email":"","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kangning","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2022-03-21 08:35:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1472910/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1472910/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19536368,"identity":"69c734b4-03d8-43ed-b827-225f7a2059e2","added_by":"auto","created_at":"2022-03-23 15:42:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1572034,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1472910/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"Prediction of tool wear on workpiece surface quality based on milling topography analysis","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1472910/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-international-journal-of-advanced-manufacturing-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jamt","sideBox":"Learn more about [The International Journal of Advanced Manufacturing Technology](https://www.springer.com/journal/170)","snPcode":"170","submissionUrl":"https://submission.nature.com/new-submission/170/3","title":"The International Journal of Advanced Manufacturing Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"wear, topography simulation, roughness, least square support vector machine","lastPublishedDoi":"10.21203/rs.3.rs-1472910/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1472910/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The surface quality of the workpiece has a great impact on the performance of the product. 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