Remote Sensing and Noise Processing Methods for Rock Mass Vibration Information in Complex Tunnel Environment

Remote Sensing and Noise Processing Methods for Rock Mass Vibration Information in Complex Tunnel Environment | 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 Remote Sensing and Noise Processing Methods for Rock Mass Vibration Information in Complex Tunnel Environment Chuanyi Ma, Xuefeng Han, Ning Zhang, Hongliang Liu, Guangyu Yang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9308153/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract During tunnel construction, the surface of surrounding rock is often unstable, making traditional contact sensors (e.g., accelerometers) difficult to install reliably and highly susceptible to detachment or damage. Although scanning laser Doppler vibrometers (SLDVs) offer advantages such as non-contact measurement, high precision, and full-field monitoring, their application for non-contact vibration monitoring in tunnels is subject to numerous constraints. These constraints stem from the specific complexities of tunnel construction environments and the inherent limitations of laser vibrometry technology. To address the challenges of acquiring valid vibration information using laser vibrometers, this chapter presents breakthroughs in both hardware and algorithms. In terms of hardware, an adaptive vibration-damping and noise-reducing carrier platform was developed. This platform mitigates noise interference through physical passive isolation and active control technologies. Furthermore, based on the characteristics of tunnel environments, the scanning laser vibrometry monitoring equipment was optimized for complex tunnel conditions. In terms of algorithms, a hybrid noise reduction method integrating AVMD and K-SVD was proposed. By leveraging complementary enhancement, multi-dimensional analysis, and robustness improvement, this method achieves noise separation and signal enhancement, thereby significantly improving the signal-to-noise ratio (SNR) and accuracy of micro-vibration measurements. The effectiveness of this noise reduction approach was verified through the analysis of simulated signals and measured data, successfully enabling the extraction of valid vibration information from rock masses. Physical sciences/Engineering Physical sciences/Physics Complex tunnel environment Vibration information Remote sensing Vibration damping and noise reduction Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 08 May, 2026 Reviews received at journal 04 May, 2026 Reviews received at journal 20 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 14 Apr, 2026 Editor invited by journal 14 Apr, 2026 Submission checks completed at journal 08 Apr, 2026 First submitted to journal 08 Apr, 2026 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-9308153","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":626207053,"identity":"0353c459-0c54-495c-8d69-9eb861449b40","order_by":0,"name":"Chuanyi Ma","email":"","orcid":"","institution":"Shandong High Speed Group Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Chuanyi","middleName":"","lastName":"Ma","suffix":""},{"id":626207054,"identity":"a8c14d39-31ae-4efa-a409-c41da2d831d2","order_by":1,"name":"Xuefeng Han","email":"","orcid":"","institution":"Shandong 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In terms of algorithms, a hybrid noise reduction method integrating AVMD and K-SVD was proposed. By leveraging complementary enhancement, multi-dimensional analysis, and robustness improvement, this method achieves noise separation and signal enhancement, thereby significantly improving the signal-to-noise ratio (SNR) and accuracy of micro-vibration measurements. 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