Research on an Industrial Liquid Level Detection Method Based on an Improved SSD

Research on an Industrial Liquid Level Detection Method Based on an Improved SSD | 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 Article Research on an Industrial Liquid Level Detection Method Based on an Improved SSD Xinyu Qi, Lishan Jia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6767643/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract To resolve the challenge of balancing computational efficiency and accuracy in liquid level detection models within industrial environments, this study proposes a lightweight SSD algorithm tailored for edge devices. The proposed algorithm facilitates real-time liquid level monitoring and anomaly early warning, thereby mitigating the risk of production incidents. The algorithm first builds a lightweight feature extraction network based on MobileNetV2 and substantially reduces model complexity and computational energy consumption. We propose a Multi-Scale Dilated Inverted Residual Block (MS-DIRB) to mitigate finegrained information loss during downsampling. By integrating multi-dilated convolutions and a hierarchical feature reuse strategy, the module enhances multi-scale representational capacity while maintaining computational efficiency. Furthermore, a Triplet Attention mechanism is embedded into critical bottleneck structures, establishing a three-dimensional dynamic feature calibration framework that improves discriminative feature learning while maintaining model compactness. Experimental results demonstrate that the proposed algorithm achieves 96.65% mAP, representing a 3.57 percentage-point improvement over the baseline SSD architecture, while reducing model parameters by 81.58%. These experimental outcomes demonstrate the effectiveness of the improved algorithm and its suitability as a real-time detection model in industrial edge computing applications. Physical sciences/Engineering Physical sciences/Mathematics and computing Object detection SSD algorithm Multi-Scale Dilated Inverted Residual Block Triplet Attention Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 23 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 19 Sep, 2025 Reviews received at journal 18 Sep, 2025 Reviewers agreed at journal 23 Aug, 2025 Reviews received at journal 02 Jul, 2025 Reviewers agreed at journal 27 Jun, 2025 Reviewers invited by journal 24 Jun, 2025 Editor assigned by journal 10 Jun, 2025 Submission checks completed at journal 08 Jun, 2025 First submitted to journal 08 Jun, 2025 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-6767643","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":475814145,"identity":"a5727dad-e573-4278-998e-1294587491b5","order_by":0,"name":"Xinyu Qi","email":"","orcid":"","institution":"Civil Aviation University of China","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Qi","suffix":""},{"id":475814146,"identity":"92a23bad-2717-47c3-a4c9-19ceb9061c57","order_by":1,"name":"Lishan Jia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYBACPgaGhAMMFVAeDzFa2MBazpCohYGBsY0kLfwHHh74Oc9O3uD4AcYHb9sY5M0JapFISDjYuy3ZcMOZBGbDuW0MhjsbCGoB+oV32wHGDTcY2KR52xgSDA4QdljCwb9zDtgDtbD/Jk4LQ0LCYd6GA4kgW5iJ0wL0y2GZY8nJM88kNkvOOSdhuIGQFn7+M8kf39TY2fYdP3zww5syG3mCtgDjIgHKYGwAEhIE1QMBO2FTR8EoGAWjYIQDAN3DQE2ut7K7AAAAAElFTkSuQmCC","orcid":"","institution":"Civil Aviation University of China","correspondingAuthor":true,"prefix":"","firstName":"Lishan","middleName":"","lastName":"Jia","suffix":""}],"badges":[],"createdAt":"2025-05-28 11:38:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6767643/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6767643/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-29277-8","type":"published","date":"2025-11-23T15:57:56+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96650294,"identity":"65f687be-b26f-4297-a675-9783aac05958","added_by":"auto","created_at":"2025-11-24 16:10:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2907057,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchonanIndustrialLiquidLevelDetectionMethodBasedonanImprovedSSD.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6767643/v1_covered_76818abc-7c73-4960-8d7b-141b9c78d344.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on an Industrial Liquid Level Detection Method Based on an Improved SSD","fulltext":[],"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":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Object detection, SSD algorithm, Multi-Scale Dilated Inverted Residual Block, Triplet Attention","lastPublishedDoi":"10.21203/rs.3.rs-6767643/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6767643/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo resolve the challenge of balancing computational efficiency and accuracy in liquid level detection models within industrial environments, this study proposes a lightweight SSD algorithm tailored for edge devices. 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