Cost-Effective Non-Invasive Vibration Measurement Using UWB Radar and RDWT for Outer and Inner Race Fault Diagnosis in BLDC Motors

Cost-Effective Non-Invasive Vibration Measurement Using UWB Radar and RDWT for Outer and Inner Race Fault Diagnosis in BLDC Motors | 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 Cost-Effective Non-Invasive Vibration Measurement Using UWB Radar and RDWT for Outer and Inner Race Fault Diagnosis in BLDC Motors Raja Shekhar P, Meganathan D This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7733864/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 Detecting electrical and mechanical faults in brushless direct current (BLDC) motors is essential for ensuring the reliability and performance of electric vehicles. Vibration monitoring plays a key role in fault identification and can be implemented through invasive or non-invasive methods. However, existing techniques often involve high costs, complex hardware, or limited sensitivity. This study proposes a low-cost, non-invasive vibration measurement approach that integrates a handheld ultra-wideband (UWB) radar, a data recording unit, and advanced signal processing for diagnosing outer- and inner-race bearing faults. In this method, the UWB radar generates a high-frequency signal projected onto the motor, and the reflected response is recorded via SIGVIEW software. The captured data are processed using a software phase-locked loop (SPLL) with low-pass filtering, followed by Rational Dilation Wavelet Transform (RDWT) analysis. Energy distributions of RDWT sub-bands, evaluated in MATLAB R2022b, are compared under normal and faulty conditions. Results demonstrate that as bearing faults increase, RDWT sub-band energy at level-4 rises by 4.57%–5.15%, while level-5 shows an increase of 6.27%–16.56%. The proposed method enables early fault detection in BLDC motors, supporting predictive maintenance and minimizing unexpected failures in electric vehicles. BLDC motor Outer-Inner race faults RDWT UWB radar Software PLL Full Text Additional Declarations The authors declare no competing interests. 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-7733864","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":549605937,"identity":"dde51106-b286-4d73-aef1-5f419cb4465b","order_by":0,"name":"Raja Shekhar 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Motors\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Anna University, Chennai","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":"BLDC motor, Outer-Inner race faults, RDWT, UWB radar, Software PLL","lastPublishedDoi":"10.21203/rs.3.rs-7733864/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7733864/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDetecting electrical and mechanical faults in brushless direct current (BLDC) motors is essential for ensuring the reliability and performance of electric vehicles. Vibration monitoring plays a key role in fault identification and can be implemented through invasive or non-invasive methods. However, existing techniques often involve high costs, complex hardware, or limited sensitivity. This study proposes a low-cost, non-invasive vibration measurement approach that integrates a handheld ultra-wideband (UWB) radar, a data recording unit, and advanced signal processing for diagnosing outer- and inner-race bearing faults. In this method, the UWB radar generates a high-frequency signal projected onto the motor, and the reflected response is recorded via SIGVIEW software. The captured data are processed using a software phase-locked loop (SPLL) with low-pass filtering, followed by Rational Dilation Wavelet Transform (RDWT) analysis. Energy distributions of RDWT sub-bands, evaluated in MATLAB R2022b, are compared under normal and faulty conditions. Results demonstrate that as bearing faults increase, RDWT sub-band energy at level-4 rises by 4.57%\u0026ndash;5.15%, while level-5 shows an increase of 6.27%\u0026ndash;16.56%. The proposed method enables early fault detection in BLDC motors, supporting predictive maintenance and minimizing unexpected failures in electric vehicles.\u003c/p\u003e","manuscriptTitle":"Cost-Effective Non-Invasive Vibration Measurement Using UWB Radar and RDWT for Outer and Inner Race Fault Diagnosis in BLDC Motors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-25 10:57:26","doi":"10.21203/rs.3.rs-7733864/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"dd3314fc-491a-42a8-ac0a-f051ac5197de","owner":[],"postedDate":"November 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-25T10:57:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-25 10:57:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7733864","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7733864","identity":"rs-7733864","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}