Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the sixth volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Health Monitoring, including papers on:
- Novel Techniques
- Optical Methods,
- Scanning LDV Methods
- Photogrammetry & DIC
- Rotating Machinery
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.
Dario Di Maio, University of Twente, Netherlands; Javad Baqersad, Kettering University, MI, USA.
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