Design of a Nested Inductive Wear Particle Sensor

Design of a Nested Inductive Wear Particle Sensor | 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 Design of a Nested Inductive Wear Particle Sensor Kai LI, Jinzhe WANG, Ruiqing BIAN, Xinqiang LIU, Wenhui JIA, Yuan LI, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6351292/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 Lubricating oil contains abundant information reflecting equipment status. This study proposes a nested inductive sensor to address the need for wear particle detection in lubricants. A mathematical model of the sensor was established based on the electromagnetic induction principle. From the perspective of coil mutual inductance, the sensitivity advantage of the nested configuration was analyzed. Transient electromagnetic simulations validated the theoretical findings. Experimental verification using a prototype system successfully identified 71-µm ferromagnetic and 373-µm non-ferromagnetic particles within a 6-mm flow channel, with feature extraction converting signals into identifiable pulse waveforms. To enhance signal clarity, an OVMD-ICR algorithm (Optimizing Variational Mode Decomposition Combined with Independent Component Reconstruction) was integrated, outperforming conventional denoising methods. This advancement enables real-time monitoring of lubrication systems, providing a foundation for predictive maintenance strategies. A sensor system was constructed, the detection performance for different wear particles was tested, and an OVMD-ICR noise reduction algorithm was proposed. The sensor detected 71-µm ferromagnetic and 373-µm non-ferromagnetic particles, within a 6-mm channel, as experimentally verified. This provides support for developing integrated online wear particle detection systems. It is also significant for wear particle detection in lubrication systems. Wear Particle Detection Inductive Sensors Variational Mode Decomposition Wavelet Transform 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. 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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-6351292","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449216544,"identity":"1aeb6be1-6467-44b5-aacc-60436697de74","order_by":0,"name":"Kai LI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYBACPmY2BoaECghHgigtbGAtZ0jSAoQMjG0kaWFnS/zwcN6dxP4G5oO3eRjs8ohx2GGJxG3PEmccYEu25mFILiZCC3sDUMvhxA0MPGbSPAwHEhuI0NL8I3EOSAv/N2K1sB2TSGwA28JGtJY0i4Rjh41nHGYztpxjkExYCz//MeObP2oOy/a3Nz+88abCjrAWBGAGEQbEqx8Fo2AUjIJRgAcAAIpiM+YnkHXfAAAAAElFTkSuQmCC","orcid":"","institution":"North University of China","correspondingAuthor":true,"prefix":"","firstName":"Kai","middleName":"","lastName":"LI","suffix":""},{"id":449216545,"identity":"f0a49f8d-1dfd-4ff1-bb9e-31c05ae2042b","order_by":1,"name":"Jinzhe WANG","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Jinzhe","middleName":"","lastName":"WANG","suffix":""},{"id":449216546,"identity":"7c6d6b62-887a-40fb-99a4-cae61fd5fcf4","order_by":2,"name":"Ruiqing BIAN","email":"","orcid":"","institution":"The 33 RD Research Institute Of China Electronics Technology Group Corporation","correspondingAuthor":false,"prefix":"","firstName":"Ruiqing","middleName":"","lastName":"BIAN","suffix":""},{"id":449216547,"identity":"0977a06e-c0da-4006-b2e8-1d90b7a321fe","order_by":3,"name":"Xinqiang LIU","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Xinqiang","middleName":"","lastName":"LIU","suffix":""},{"id":449216548,"identity":"4a2267da-d942-456f-bb04-80ce020515b7","order_by":4,"name":"Wenhui JIA","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Wenhui","middleName":"","lastName":"JIA","suffix":""},{"id":449216549,"identity":"7fb631b8-d63f-465d-8bca-52137218af0a","order_by":5,"name":"Yuan LI","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"LI","suffix":""},{"id":449216551,"identity":"1a063c23-10d1-471b-8564-6a3a9590dd7f","order_by":6,"name":"Xuanqi WU","email":"","orcid":"","institution":"North University of China","correspondingAuthor":false,"prefix":"","firstName":"Xuanqi","middleName":"","lastName":"WU","suffix":""}],"badges":[],"createdAt":"2025-04-01 08:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6351292/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6351292/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83853303,"identity":"f228e443-a3dc-4fe6-ac45-e1513fc3a425","added_by":"auto","created_at":"2025-06-03 16:46:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1833043,"visible":true,"origin":"","legend":"","description":"","filename":"DesignofaNestedInductiveWearParticleSensor.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6351292/v1_covered_38503e8c-2733-479c-865f-3b034248a5dd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Design of a Nested Inductive Wear Particle Sensor","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":"Wear Particle Detection, Inductive Sensors, Variational Mode Decomposition, Wavelet Transform","lastPublishedDoi":"10.21203/rs.3.rs-6351292/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6351292/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLubricating oil contains abundant information reflecting equipment status. This study proposes a nested inductive sensor to address the need for wear particle detection in lubricants. A mathematical model of the sensor was established based on the electromagnetic induction principle. From the perspective of coil mutual inductance, the sensitivity advantage of the nested configuration was analyzed. Transient electromagnetic simulations validated the theoretical findings. Experimental verification using a prototype system successfully identified 71-\u0026micro;m ferromagnetic and 373-\u0026micro;m non-ferromagnetic particles within a 6-mm flow channel, with feature extraction converting signals into identifiable pulse waveforms. To enhance signal clarity, an OVMD-ICR algorithm (Optimizing Variational Mode Decomposition Combined with Independent Component Reconstruction) was integrated, outperforming conventional denoising methods. This advancement enables real-time monitoring of lubrication systems, providing a foundation for predictive maintenance strategies. 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