Research on Diagnosis of Milling Chatter in Thin-walled Parts Based on Improved Hilbert-Huang Transform

Research on Diagnosis of Milling Chatter in Thin-walled Parts Based on Improved Hilbert-Huang Transform | 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 Research on Diagnosis of Milling Chatter in Thin-walled Parts Based on Improved Hilbert-Huang Transform Xiang Li, Yadong Gong, Jibin Zhao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4508928/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In order to achieve stable milling machining of thin-walled parts and improve the milling surface machining quality, a chatter diagnosis strategy based on the improved algorithm of Hilbert-Huang Transform (HHT) is proposed. Firstly, the largest Lyapunov exponent and the approximate entropy exponent of the dynamic force time-domain signals collected from the milling experiments of thin-walled parts were calculated to complete the evaluation of the nonlinear characteristics of the milling process. Secondly, optimization improvements are made to address the problems of modal confusion and spurious intrinsic mode functions in the HHT. Based on the statistical characteristics of the frequency components in the Hilbert spectrum extracted by the improved algorithm, a new chatter identification criterion is proposed and a diagnostic model is built from it. Finally, the reliability of the model prediction results was verified by using the actual measured surface profile correlation coefficients. The results show that the new diagnostic model has good versatility and accuracy for chatter identification compared to conventional methods. Hilbert-Huang Transform. Thin-walled parts. Milling. Chatter Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4508928","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313325882,"identity":"96491106-6be2-4faa-966f-97b5b51b44e0","order_by":0,"name":"Xiang Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYDACdgYGxgYGCyCjsfHhB6K0MIO1SDAw8BxuNpYgTYtEepsADzE6+JuZnz2cwSAhxy/5sA2o005Ot4GAFonDbOaGGxgkjCVnJ7Y9KGBINjY7QECLATODmeQDBonEDbcT2w0kGA4kbiOshf0bSEv9/psH2yR4iNPCYyYJdFiCgQQjkVokDvOUSQK9bzjjTCIwkA2I8At/e/s2yR4GG3n+9uMPH36osJMjqAUMGP/B3UmM8lEwCkbBKBgFBAEAq3M5bqlIQT4AAAAASUVORK5CYII=","orcid":"","institution":"Northeastern University","correspondingAuthor":true,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Li","suffix":""},{"id":313325883,"identity":"87019f26-18b1-43da-a2c9-14e76f438d22","order_by":1,"name":"Yadong Gong","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Yadong","middleName":"","lastName":"Gong","suffix":""},{"id":313325884,"identity":"a873a31b-7303-41e8-9db1-adf32fdb205e","order_by":2,"name":"Jibin Zhao","email":"","orcid":"","institution":"Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jibin","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2024-05-31 12:26:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4508928/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4508928/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75809580,"identity":"f22698af-ac4f-48c1-bbe3-1f2abdce1672","added_by":"auto","created_at":"2025-02-08 20:46:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1014277,"visible":true,"origin":"","legend":"","description":"","filename":"TheManuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4508928/v1_covered_415bcda7-6546-4aee-8bfa-5ed7209bcdca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on Diagnosis of Milling Chatter in Thin-walled Parts Based on Improved Hilbert-Huang Transform","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hilbert-Huang Transform. Thin-walled parts. Milling. Chatter","lastPublishedDoi":"10.21203/rs.3.rs-4508928/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4508928/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn order to achieve stable milling machining of thin-walled parts and improve the milling surface machining quality, a chatter diagnosis strategy based on the improved algorithm of Hilbert-Huang Transform (HHT) is proposed. Firstly, the largest Lyapunov exponent and the approximate entropy exponent of the dynamic force time-domain signals collected from the milling experiments of thin-walled parts were calculated to complete the evaluation of the nonlinear characteristics of the milling process. Secondly, optimization improvements are made to address the problems of modal confusion and spurious intrinsic mode functions in the HHT. 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