Data Science in Engineering, Volume 9 Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022 /

Data Science in Engineering, Volume 9 Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022 /

書誌詳細
団体著者: SpringerLink (Online service)
その他の著者: Madarshahian, Ramin (編集者), Hemez, Francois (編集者)
要約:VIII, 156 p. 124 illus., 109 illus. in color.
text
言語:英語
出版事項: Cham : Springer International Publishing : Imprint: Springer, 2022.
版:1st ed. 2022.
シリーズ:Conference Proceedings of the Society for Experimental Mechanics Series,
主題:
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.
オンライン･アクセス:https://doi.org/10.1007/978-3-031-04122-8
フォーマット: 電子媒体 eBook
目次:
  • 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.

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