Data Science in Engineering, Volume 9 : Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021 / / edited by Ramin Madarshahian, Francois Hemez |
Autore | Madarshahian Ramin |
Edizione | [1st ed. 2022.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
Descrizione fisica | 1 online resource (287 pages) |
Disciplina | 620.00151 |
Collana | Conference Proceedings of the Society for Experimental Mechanics Series |
Soggetto topico |
Engineering mathematics
Engineering - Data processing Artificial intelligence - Data processing Civil engineering Mechanical engineering Mathematical and Computational Engineering Applications Data Science Civil Engineering Mechanical Engineering |
ISBN | 3-030-76004-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1. Towards a Population-based Structural Health Monitoring, Part V: Networks and Databases -- Chapter 2. Active Learning of Post-Earthquake Structural Damage with Co-Optimal Information Gain and Reconnaissance Cost -- Chapter 3. Uncertainty-Quantified Damage Identification for High-Rate Dynamic Systems -- Chapter 4. Real-time Machine Learning of Vibration Signals -- Chapter 5. Data-Driven Identification of Mistuning in Blisks -- Chapter 6. On Generating Parametrised Structural Data Using Conditional Generative Adversarial Networks -- Chapter 7. Best Paper: On an Application of Graph Neural Networks in Population Based SHM -- Chapter 8. Estimation of Elastic Band Gaps Using Data-Driven Model -- Chapter 9. Damage Localization on Lightweight Structures with Non-Destructive Testing and Machine Learning Techniques -- Chapter 10. Challenges for SHM from Structural Repairs: An Outlier-informed Domain Adaptation Approach -- Chapter 11. On the Application of Heterogeneous Transfer Learning to Population-based Structural Health Monitoring -- Chapter 12. An Unsupervised Deep Auto-Encoder with One-Class Support Vector Machine for Damage Detection -- Chapter 13. Identifying Operations- and Environmental-Insensitive Damage Features -- Chapter 14. Hybrid Concrete Crack Segmentation and Quantification Across Complex Backgrounds without Big Training Dataset -- Chapter 15. Digital Stroboscopy using Event-Driven Imagery -- Chapter 16. Managing System Inspections for Health Monitoring: A Probability of Query Approach -- Chapter 17. Parameter Estimation for Dynamical Systems Under Continuous and Discontinuous Gaussian Noise Using Data Assimilation Techniques -- Chapter 18. Model Reduction of Geometrically Nonlinear Structures via Physics-Informed Autoencoders -- Chapter 19. Techniques to Improve Robustness of Video-Based Sensor Networks -- Chapter 20. Grey-Box Modelling via Gaussian Process Mean Functions for Mechanical Systems -- Chapter 21. On Topological Data Analysis for SHM; An Introduction to Persistent Homology -- Chapter 22. Heteroscedastic Gaussian Processes for Localising Acoustic Emission -- Chapter 23. Transferring Damage Detectors Between Tailplane Experiments -- Chapter 24. High-Rate Structural Health Monitoring and Prognostics: An Overview -- Chapter 25. One Versus All: Best Practices in Combining Multi-Hazard Damage Imagery Training Datasets for Damage Detection for a Deep Learning Neural Network -- Chapter 26. High-Rate Damage Classification and Lifecycle Prediction via Deep Learning -- Chapter 27. A Generalized Technique for Full-field Blind Identification of Travelling Waves and Complex Modes from Video Measurements with Hilbert Transform -- Chapter 28. Privacy-Preserving Structural Dynamics -- Chapter 29. Abnormal Behavior Detection of the Indian River Inlet Bridge through Cross Correlation Analysis of Truck Induced Strains -- Chapter 30. A Video-Based Crack Detection in Concrete Surfaces -- Chapter 31. Bayesian Graph Neural Networks for Strain-Based Crack Localization -- Chapter 32. Routing of Public and Electric Transportation Systems Using Reinforcement Learning -- Chapter 33. Vibration based Damage Detection and Identification in a CFRP Truss with Deep Learning and Finite Element Generated Data -- Chapter 34. Parametric Amplification in a Stochastic Nonlinear Piezoelectric Energy Harvester via Machine Learning. |
Record Nr. | UNINA-9910522921503321 |
Madarshahian Ramin
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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Data Science in Engineering, Volume 9 : Proceedings of the 39th IMAC, a Conference and Exposition on Structural Dynamics 2021 |
Autore | Madarshahian Ramin |
Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2021 |
Descrizione fisica | 1 online resource (287 pages) |
Altri autori (Persone) | HemezFrancois |
Collana | Conference Proceedings of the Society for Experimental Mechanics Ser. |
Soggetto genere / forma | Electronic books. |
ISBN | 3-030-76004-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910502646903321 |
Madarshahian Ramin
![]() |
||
Cham : , : Springer International Publishing AG, , 2021 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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Data Science in Engineering, Volume 9 : Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022 / / edited by Ramin Madarshahian, Francois Hemez |
Edizione | [1st ed. 2022.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
Descrizione fisica | 1 online resource (158 pages) |
Disciplina |
624.17102854
620.00285574 |
Collana | Conference Proceedings of the Society for Experimental Mechanics Series |
Soggetto topico |
Engineering - Data processing
Quantitative research Statics Buildings - Design and construction Multibody systems Vibration Mechanics, Applied Data Engineering Data Analysis and Big Data Mechanical Statics and Structures Building Construction and Design Multibody Systems and Mechanical Vibrations |
ISBN | 3-031-04122-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1. Model Updating for Nonlinear Dynamic Digital Twins Using Data-Based Inverse Mapping Models -- Chapter 2. Deep Reinforcement Learning for Active Structure Stabilization -- Chapter 3. Estimation of Structural Vibration Modal Properties Using a Spike-Based Computing Paradigm -- Chapter 4. Environmental-Insensitive Damage Features Based on Transmissibility Coherence -- Chapter 5. Transmittance Anomalies for Model-Based Damage Detection with Finite Element Generated Data and Deep Learning -- Chapter 6. Machine Learning based Condition Monitoring with Multibody Dynamics Models for Gear Transmission Faults -- Chapter 7. Structural Damage Detection Framework Using Metaheuristic Algorithms and Optimal Finite Element Modeling -- Chapter 8. On Aspects of Geometry in SHM and Population-Based SHM -- Chapter 9. A Robust PCA-based Framework for Long-Term Condition Monitoring of Civil Infrastructures -- Chapter 10. Data-Driven Parameter Identification for Turbomachinery Blisks -- Chapter 11. Classification of Rail Irregularities from Axle Box Accelerations using Random Forests and Convolutional Neural Networks -- Chapter 12. Development of a Surrogate Model for Structural Health Monitoring of a UAV Wing Spar -- Chapter 13. On a Description of Aeroplanes and Aeroplane Components using Irreducible Element Models -- Chapter 14. Input Estimation of Four-DOF Nonlinear Building Using Probabilistic Recurrent Neural Network -- Chapter 15. Simulation-Based Damage Detection for Composite Structures with Machine Learning Techniques -- Chapter 16. Synthesizing Dynamic Time-series Data for Structures Under Shock Using Generative Adversarial Networks -- Chapter 17. Multi-Layer Input Deep Learning Applied to Ultrasonic Wavefield Measurements. |
Record Nr. | UNINA-9910580138803321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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