[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124868-en":3,"doc-seo-124868-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124868,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals - Abstract","The lack of anomaly detection methods during mechanized tunnelling can cause financial loss and drilling-time deficits. On-site excavation must recognize hard obstacles before drilling to prevent damage to the tunnel boring machine and to adjust seismic wave propagation velocity. An intelligent optimization and machine learning workflow improves structural anomaly detection efficiency. The approach identifies anomalies by comparing experimental structural vibration measurements with numerical simulations using parameter-estimation methods.","arXiv :2401 . 10355v1 [ ee ss . SP] 18 Jan 2024  \nIntelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals  \nMaximilian Trappa,∗, Can Bogoclub , Tamara Nestorovi´ca , Dirk Roosb  \naAG Mechanics of Adaptive Systems, Ruhr-University Bochum, Building ICFW 03-725, Universit¨atsstraße 150, 44801 Bochum, Germany  \nb Institute of Modeling and High-Performance Computing, Niederrhein University, Reinarzstraße 49,  \n47797 Krefeld, Germany  \nAbstract  \nThe lack of anomaly detection methods during mechanized tunnelling can cause financial loss and deficits in drilling time. On-site excavation requires hard obstacles to be recognized prior to drilling in order to avoid damaging the tunnel boring machine and to adjust the propagation velocity. The efficiency of the structural anomaly detection can be increased with intelligent optimization techniques and machine learning. In this research, the anomaly in a simple structure is detected by comparing the experimental measurements of the structural vibrations with numerical simulations using parameter estimation methods.  \nKeywords: structural anomaly detection; Kalman filter; unscented hybrid simulated annealing; Gaussian processes; deep Gaussian covariance network; inverse problem  \n1. Introduction  \nDrilling into unknown soil bears a large economical risk. Possible unfavourable scenarios span from excess water inflow or a damaging of the Tunnel Boring Machine (TBM) to a total collapse of the tunnel [1] . To avoid potential risks, the imaging of voids, faults, fluid areas, erratic boulders or other changes in material is essential. Exploratory drillings only provide an image of the geological parameters in the near-field of the borehole and lack in showing the detailed geological structure. Thus, acoustic analysis is a better choice as it offers the opportunity to obtain a detailed image of the soil with the help of seismic waves. Propagating through the ground, seismic waves are reflected, refracted, scattered and converted; resulting in a detailed fingerprint of the actual structure.  \nMost of the techniques used nowadays for the detection of anomalies rely on travel time measurements and migration techniques, considering only compressional waves. Therefore,  \n∗ I am the corresponding author. Interested readers may contact me regarding structural anomaly detection and unscented hybrid simulated annealing and C. Bogoclu regarding machine learning.  \nEmail addresses: [Maximilian.Trapp@rub.de](Maximilian.Trapp@rub.de) (Maximilian Trapp), Can.Bogoclu@hs-niederrhein.de (Can Bogoclu), [Tamara.Nestorovic@rub.de](Tamara.Nestorovic@rub.de) (Tamara Nestorovi´c), Dirk.Roos@hs-niederrhein.de (Dirk Roos)  \nPreprint submitted to Mechanical Systems and Signal Processing January 22, 2024  \ntypical state-of-the-art systems like Tunnel Seismic Prediction (TSP) [2], Sonic Softground Probing (SSP) [3], True Reflection Tomography (TRT) [4] or Integrated Seismic Imaging System (ISIS) [5] lack accuracy in describing a detailed image of the subsoil. Aiming at full exploitation of the information coming from seismic waves, full waveform inversion (FWI) techniques [6] offer promising opportunities for reconnaissance in mechanized tunneling. Musayev et al. [7] propose an algorithm for forward modeling and inversion of seismic waves in frequency domain for 2D and 3D tunnel models. Bretaudeau et al. use an iterative conjugate-gradient approach in frequency domain for 2D models, which was already tested on experimental data [8, 9] . Also, the structural composition of rocks was investigated on the microscale in relation with detection and prediction of failure and deterioration [10] . A nodal discontinuous Galerkin method implemented into an adjoint approach is used by Lamert & Friederich [11] to achieve FWI in time domain for 2D models.  \nNguyen & Nestorovic [12] propose unscented hybrid simulated annealing (UHSA) for FWI in time domain. Here, the unscented Kalman ","cbCaieloUmv3SGOE","https://ap.wps.com/l/cbCaieloUmv3SGOE","pdf",4566368,1,23,"English","en",105,"# Introduction\n## Seismic-wave based imaging for tunnelling\n## Full waveform inversion and existing methods\n## Parameter estimation and hybrid optimization\n## Machine learning for inverse problems","[{\"question\":\"Why is structural anomaly detection important during mechanized tunnelling?\",\"answer\":\"Because missing anomalies can lead to financial losses, drilling-time deficits, and damage to the tunnel boring machine. Early recognition also supports adjusting propagation velocity during excavation.\"},{\"question\":\"How does the research detect structural anomalies?\",\"answer\":\"It detects anomalies by comparing experimental measurements of structural vibrations with numerical simulations using parameter-estimation methods.\"},{\"question\":\"What is the role of unscented hybrid simulated annealing in this work?\",\"answer\":\"It combines the unscented Kalman filter with simulated annealing to achieve fast minimization of the misfit function and to reduce sensitivity to local minima.\"}]","Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals - Abstract | PDF",1785895129,58,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"intelligent-optimization-and-machine-learning-algorithms-for-structural-anomaly-detection-using-seismic-signals-abstract","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/intelligent-optimization-and-machine-learning-algorithms-for-structural-anomaly-detection-using-seismic-signals-abstract/124868/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is structural anomaly detection important during mechanized tunnelling?","Question",{"text":75,"@type":76},"Because missing anomalies can lead to financial losses, drilling-time deficits, and damage to the tunnel boring machine. Early recognition also supports adjusting propagation velocity during excavation.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the research detect structural anomalies?",{"text":80,"@type":76},"It detects anomalies by comparing experimental measurements of structural vibrations with numerical simulations using parameter-estimation methods.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the role of unscented hybrid simulated annealing in this work?",{"text":84,"@type":76},"It combines the unscented Kalman filter with simulated annealing to achieve fast minimization of the misfit function and to reduce sensitivity to local minima.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]