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Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics
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Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!
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| Chapter 1. Introduction to Multipath Doppler Vibrometry (MDV) for Validating Complex Models Accurately and Without Contact.- Chapter 2. DIC Using Low Speed Cameras on a Scaled Wind Turbine Blade.- Chapter 3. Data Challenges for Structural Health Monitoring of Electrical Machines.- Chapter 4. Neuromorphic Data Processing for Event-Driven Imagery for Acoustic Measurements.- Chapter 5. Template Matching and Particle Filtering for Structural Identification of High and Low Frequency Vibration.- Chapter 6. Multi-Sensor Collaborative Sampling Schemes to Reconstruct Undersampled Mechanical System Signals for Machinery Fault Detection.- Chapter 7. Regime Sorting for Multiscale Vibrations and Phase-Based Motion Extraction.- Chapter 8. Digital Image Correlation with a Neuromorphic Event-based Imager.- Chapter 9. Monitoring the Response of Electrical Components during Environmental Vibration Tests Using a Scanning Laser Doppler Vibrometer.- Chapter 10. Advanced Mesh Reconstruction with Low BudgetRGBD-Hardware for Modal Analysis with the Software WaveImage.- Chapter 11. Stereoscopic High Speed Camera Based Operational Modal Analysis using a One-camera Setup.- Chapter 12. In-plane Vibration Measurement of an Aluminum Plate Using a Three-dimensional Continuously Scanning Laser Doppler Vibrometer System.- Chapter 13. Measuring Full-Field Deformation in Ultra-High-Performance Concrete Structural Components using Tag-Based Robotic Vision.- Chapter 14. Dynamic Behaviour and Magneto-Mechanical Efficiency of a Contactless Magnetic Transmission.- Chapter 15. Structural Damage Identification for Plate-Like Structures Using Two-dimensional Teager Energy Operator-Wavelet Transform.- Chapter 16. A Vision-based Quantification Approach for Reinforced Concrete Tunnel Liner Delamination.- Chapter 17. An Optical Temporal and Spatial Vibration-Based Damage Detection Using Convolutional Neural Networks and Long Short-Term Memory.- Chapter 18. A Hybrid-Attention-LSTM-Based Deep Convolutional NeuralNetwork to Extract Modal Frequencies from Limited Dataset Using Transfer Learning.- Chapter 19. Detecting and Reconstructing the 3D Geometry of Subsurface Structural Damage Using Full-Field Image-Based Sensing and Topology Optimization.- Chapter 20. Optimal Kernel Design for the Extraction of Subtle Motions Using Convolutional Neural Network. |
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i.d.R. innert 7-14 Tagen versandfertig
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