Research map: CNN-self-attention framework for enhanced impedance-based damage detection under vibration and noisy environments

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  1. Learning representations by back-propagating errors · David E. Rumelhart · 1986 · 32132 citations · Cited by this paper
  2. Acoustic resonance method for the rapid and quantitative identification of bolt looseness · 2026 · Related
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  4. Heterogeneous point clouds fusion method for long-span suspension bridge cable morphology analysis · 2026 · Related
  5. Impedance-Based Health Monitoring of Civil Structural Components · Gyuhae Park · 2000 · 461 citations · Cited by this paper
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  8. Light gradient boosting machine for data augmentation optimization and model selection for one-dimensional multiclass damage detection · 2026 · Related
  9. Active vibration-based structural health monitoring system for wind turbine blade: Demonstration on an operating Vestas V27 wind turbine · Dmitri Tcherniak · 2017 · 112 citations · Cited by this paper
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  11. Dynamic structural health monitoring of a model wind turbine tower using distributed acoustic sensing (DAS) · Peter G. Hubbard · 2021 · 108 citations · Cited by this paper
  12. Machine learning-enabled probabilistic hybrid model updating of pitting corrosion with application to hydraulic steel structures: an experimental validation · 2026 · Related
  13. Vibration-based structural health monitoring of a wind turbine system Part II: Environmental/operational effects on dynamic properties · Wei-Hua Hu · 2015 · 105 citations · Cited by this paper
  14. Wideband response of MEMS resonators beyond their natural frequency for structural health monitoring applications · 2026 · Related
  15. An integrated deep neural network model combining 1D CNN and LSTM for structural health monitoring utilizing multisensor time-series data · Mohammadreza Ahmadzadeh · 2024 · 102 citations · Cited by this paper
  16. Multi-factor sensitivity analysis of dynamic response and safety assessment of reinforced concrete pipelines with different buried depths under the impact of collapse rockfalls · 2026 · Related
  17. Structural dynamic response reconstruction using self-attention enhanced generative adversarial networks · Gao Fan · 2022 · 99 citations · Cited by this paper
  18. Automatic detection of loose bolts in pipeline structures based on anti-noise mel cepstrum differential features and deep learning · 2026 · Related
  19. Damage detection in operational wind turbine blades using a new approach based on machine learning · K. Chandrasekhar · 2020 · 89 citations · Cited by this paper
  20. Condition monitoring of the Santa Chiara masonry arch bridge at Noto using observed seismic responses · 2026 · Related
  21. A method for automated bolt-loosening monitoring and assessment using impedance technique and deep learning · Thanh‐Truong Nguyen · 2023 · 82 citations · Cited by this paper
  22. Structural health monitoring of wind towers: remote damage detection using strain sensors · M. Benedetti · 2011 · 76 citations · Cited by this paper
  23. Deep learning-based autonomous damage-sensitive feature extraction for impedance-based prestress monitoring · Thanh‐Truong Nguyen · 2022 · 74 citations · Cited by this paper
  24. One-dimensional convolutional neural network-based damage detection in structural joints · Smriti Sharma · 2020 · 73 citations · Cited by this paper
  25. Impedance-based structural health monitoring using neural networks for autonomous frequency range selection · Jiyoung Min · 2010 · 71 citations · Cited by this paper
  26. A comprehensive study on Structural Health Monitoring (SHM) of wind turbine blades by instrumenting tower using machine learning methods · Meghdad Khazaee · 2022 · 71 citations · Cited by this paper
  27. Deep learning of electromechanical impedance for concrete structural damage identification using 1-D convolutional neural networks · Demi Ai · 2023 · 62 citations · Cited by this paper
  28. A Novel CNN-LSTM Hybrid Model for Prediction of Electro-Mechanical Impedance Signal Based Bond Strength Monitoring · Lukesh Parida · 2022 · 58 citations · Cited by this paper
  29. Hybrid bolt-loosening detection in wind turbine tower structures by vibration and impedance responses · Tuan-Cuong Nguyen · 2017 · 48 citations · Cited by this paper
  30. Smart Aggregate‐Based Concrete Stress Monitoring via 1D CNN Deep Learning of Raw Impedance Signals · Quoc-Bao Ta · 2024 · 38 citations · Cited by this paper
  31. Piezoelectric Impedance-Based Structural Health Monitoring of Wind Turbine Structures: Current Status and Future Perspectives · Thanh-Cao Le · 2022 · 33 citations · Cited by this paper
  32. A small sample piezoelectric impedance-based structural damage identification using Signal Reshaping-based Enhance Attention Transformer · Xian Wang · 2023 · 25 citations · Cited by this paper
  33. Structural health monitoring of wind turbine blade using piezoceremic based active sensing and impedance sensing · Jiabiao Ruan · 2014 · 18 citations · Cited by this paper
  34. Structural health monitoring of wind towers: residual fatigue life estimation · M. Benedetti · 2013 · 17 citations · Cited by this paper
  35. Failure monitoring and localization of wind turbine blades using ultrasonic guided waves and multi-index fusion imaging · Yuan Chai · 2025 · 17 citations · Cited by this paper
  36. Wind Turbine vibration based SHM system: influence of the sensors layout and noise · João Pacheco · 2017 · 10 citations · Cited by this paper
  37. Systematical vibration data recovery based on novel convolutional self-attention networks · Gao Fan · 2024 · 9 citations · Cited by this paper
  38. A State-of-the-Art Review of Structural Health Monitoring Techniques for Wind Turbine Blades · Shah Abdul Haseeb · 2025 · 8 citations · Cited by this paper
  39. A hybrid attention hierarchical network-based extreme event detection method for structural health monitoring · Qiuyue Pan · 2025 · 4 citations · Cited by this paper

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