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Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020 de Dario Di Maio

Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020: Conference Proceedings of the Society for Experimental Mechanics Series

Editat de Dario Di Maio, Javad Baqersad
en Limba Engleză Hardback – 24 sep 2020
Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020, the sixth volume of eight 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
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Specificații

ISBN-13: 9783030477202
ISBN-10: 3030477207
Pagini: 163
Ilustrații: VIII, 163 p. 143 illus.
Dimensiuni: 210 x 279 mm
Greutate: 0.64 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Conference Proceedings of the Society for Experimental Mechanics Series

Locul publicării:Cham, Switzerland

Notă biografică

D. Di Maio, University of Bristol, Bristol, UK; J. Baqersad, Kettering University, MI, USA.

Textul de pe ultima copertă

Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020, the sixth volume of eight 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

Cuprins

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.