Structural Health Monitoring

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Overview

Structural Health Monitoring studies how to detect and characterize damage or deterioration in structures such as bridges, buildings, aircraft, rail systems, and wind turbines. It draws on vibration, strain, guided-wave, image, and point-cloud measurements, using signal processing and statistical models alongside machine learning methods such as convolutional networks, transformers, graph models, and physics-informed learning. These methods support tasks including anomaly detection, damage localization and severity assessment, displacement forecasting, and digital-twin or maintenance workflows. A central challenge is making reliable, calibrated models generalize across changing environments and structures when labeled field data are scarce, while remaining interpretable and efficient enough for safety-critical deployment.

Latest papers

CardsList

80 papers6 papers in the last four weeks, up 100% on the four weeks before. 0.0% of all new papers.

  1. Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing

    Apr 27, 2026Sakiko Mishima, Yoshiyuki Yajima, Noriyuki Tonami +4Structural Health MonitoringAnomaly Detection

    NEC Corporation, Tokyo, Japan

  2. Probabilistic Graphical Model using Graph Neural Networks for Bayesian Inversion of Discrete Structural Component States

    Apr 26, 2026Teng Li, Stephen Wu, Yong Huang +2Graph Neural NetworksBayesian Inverse Problems

    Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin 150090, China · Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, School of Civil Engineering, Harbin, Institute of Technology, Harbin 150090, China · The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan +2

  3. Disentangling Damage from Operational Variability: A Label-Free Self-Supervised Representation Learning Framework for Output-Only Structural Damage Identification

    Apr 21, 2026Xudong Jian, Charikleia Stoura, Simon Scandella +1Disentangled Representation LearningSelf-Supervised Time Series Representation Learning

    Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zürich, Switzerland. · Department of Mechanical Engineering, Politecnico di Milano, Italy

  4. Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring

    Apr 17, 2026Jongyeop Kim, Jinki Kim, Doyun LeeFrequency-Domain Feature LearningMultiscale Time-Series Modeling

    aDepartment of Information Technology, Georgia Southern University Statesboro, GA, USA · bDepartment of Mechanical Engineering, Georgia Southern University Statesboro, GA, USA · cDepartment of Civil Engineering and Construction, Georgia Southern University Statesboro, GA, USA

  5. MS-SSE-Net: A Multi-Scale Spatial Squeeze-and-Excitation Network for Structural Damage Detection in Civil and Geotechnical Engineering

    Apr 16, 2026Saif ur Rehman Khan, Imad Ahmed Waqar, Arooj Zaib +4Convolutional Neural NetworksStructural Health Monitoring

    Department of Computer Science, Rhineland-Palatinate Technical2026 University of Kaiserslautern-Landau, orgaddressKaiserslautern, 67663, Germany.Apr · 4BiogentX (biogentx.com, Renala Khurd, District Okara, Punjab, Pakistan. · 2German Research Center for Artificial Intelligence, Kaiserslautern, 67663, Germany. +2

  6. Towards Successful Implementation of Automated Raveling Detection: Effects of Training Data Size, Illumination Difference, and Spatial Shift

    Apr 14, 2026Xinan Zhang, Haolin Wang, Zhongyu Yang +2Distribution Shift RobustnessStructural Health Monitoring

    James · School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332 · School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332

  7. A Mamba-Based Multimodal Network for Multiscale Blast-Induced Rapid Structural Damage Assessment

    Apr 13, 2026Wanli Ma, Sivasakthy Selvakumaran, Dain G. Farrimond +2Disaster Damage AssessmentBuilding Damage Assessment

    Department of Engineering, University of Cambridge, Cambridge CB2 1TN, UK · School of Mechanical, Aerospace and Civil Engineering, University of Sheffield, Sheffield S10 2TN, UK

  8. PD-SOVNet: A Physics-Driven Second-Order Vibration Operator Network for Estimating Wheel Polygonal Roughness from Axle-Box Vibrations

    Apr 8, 2026Xiancheng Wang, Lin Wang, Rui Wang +5Structural Health MonitoringPhysics-Informed ML

    School of Ocean Engineering, Harbin Institute of Technology, West Wenhua Road, Weihai, 264209, Shandong, China · Technical Center, Bogie Development Department, CRRC Qingdao Sifang Locomotive and Rolling Stock Co., Ltd, Jinhong East Road, Qingdao, 266111, Shandong, China

  9. Transformer self-attention encoder-decoder with multimodal deep learning for response time series forecasting and digital twin support in wind structural health monitoring

    Apr 2, 2026Feiyu Zhou, Marios ImpraimakisStructural Health MonitoringDigital Twins

    Department of Mechanical Engineering, University of Bath, BA2 7AY Bath, UK · Department of Civil Engineering, Zhejiang University, Hangzhou 310058, China

  10. Physics-Informed Framework for Impact Identification in Aerospace Composites

    Mar 30, 2026Natália Ribeiro Marinho, Richard Loendersloot, Jan Willem Wiegman +2Structural Health MonitoringPhysics-Informed ML

    Engineering Technology Faculty, Department of Mechanics of Solids, Surfaces and Systems, Dynamics Based Maintenance (DBM) Group, University of Twente (UT), Enschede, NL · Department of Aerospace Vehicles Integrity and Life Cycle Support (AVIL), Royal Netherlands Aerospace Centre (NLR), Marknesse, NL

  11. Detecting the Unexpected: AI-Driven Anomaly Detection in Smart Bridge Monitoring

    Mar 30, 2026Rahul Jaiswal, Joakim Hellum, Halvor HeibergAnomaly DetectionStructural Health Monitoring

    Smart Sensor Systems AS, Oslo, Norway

  12. Event-Based Method for High-Speed 3D Deformation Measurement under Extreme Illumination Conditions

    Mar 30, 2026Banglei Guan, Yifei Bian, Zibin Liu +6Structural Health MonitoringEvent-Based Vision

    College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China. · Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation, Changsha 410073, China.

  13. Intelligent Road Condition Monitoring using 3D In-Air SONAR Sensing

    Mar 30, 2026Amber Cassimon, Robin Kerstens, Walter Daems +1Structural Health Monitoring

    All authors are with the Department of Electronics and ICT Engineering Technology, Cosys-Lab Research Group, University of Antwerp, Antwerp, Belgium Flanders Make Strategic Research Centre, Lommel, Belgium

  14. Quantized Vision-Language Models for Damage Assessment: A Comparative Study of LLaVA-1.5-7B Quantization Levels

    Mar 24, 2026Takato YasunoVLM QuantizationVLM Evaluation

  15. Transfer learning via interpolating structures

    Mar 23, 2026T. A. Dardeno, A. J. Hughes, L. A. Bull +3Transfer LearningCross-Domain Transfer Learning

    Dynamics Research Group, School of Mechanical, Aerospace and Civil Engineering, University of Sheffield, Sheffield S1 3JD, UK · School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8SQ, Scotland

  16. Synergistic Perception and Generative Recomposition: A Multi-Agent Orchestration for Expert-Level Building Inspection

    Mar 20, 2026Hui Zhong, Yichun Gao, Luyan Liu +4Image SegmentationSynthetic Data Augmentation

    The Hong Kong University of Science and Technology (Guangzhou), Systems Hub, China · Guangdong Provincial Key Lab of Integrated Communication, Sensing and Computation for Ubiquitous Internet of Things, Guangdong, China · The Hong Kong University of Science and Technology, Hongkong +1

  17. Traffic and weather driven hybrid digital twin for bridge monitoring

    Mar 14, 2026Phani Raja Bharath Balijepalli, Bulent Soykan, Veeraraghava Raju HastiStructural Health MonitoringDigital Twins

    University of Central Florida, Orlando, FL, USA

  18. StructDamage:A Large Scale Unified Crack and Surface Defect Dataset for Robust Structural Damage Detection

    Mar 11, 2026Misbah Ijaz, Saif Ur Rehman Khan, Abd Ur Rehman +3Structural Health Monitoring

    Department of Computer Science, University of Gujrat, Gujrat, 51700, Pakistan. · Department of Computer Science, Rhineland-Palatinate Technical University of Kaiserslautern-Landau, orgaddressKaiserslautern, 67663, Germany. · BiogentX (biogentx.com, Renala Khurd, District Okara, Punjab, Pakistan. +3

  19. Spatio-Temporal Forecasting of Retaining Wall Deformation: Mitigating Error Accumulation via Multi-Resolution ConvLSTM Stacking Ensemble

    Mar 11, 2026Jihoon Kim, Heejung YounSpatiotemporal ForecastingLong-Term Time Series Forecasting

    Department of Civil and Environmental Engineering, Hongik University, Seoul, Republic of Korea · Department of Civil and Environmental Engineering, Hongik University, 94, Wausan-ro, Mapo-gu, Seoul, 04066, Republic of Korea

  20. FedAvg-Based CTMC Hazard Model for Federated Bridge Deterioration Assessment

    Feb 22, 2026Takato YasunoMarkov ChainsStructural Health Monitoring

    1Yachiyo Engineering Co., Ltd., Tokyo, Japan