Rotating Machinery, Optical Methods and Scanning LDV Methods, Volume 6: Proceedings of the 40th IMAC, a Conference and Exposition on Structural Dynamics 2022

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 Preface Contents 1 Introduction to Multipath Doppler Vibrometry (MDV) for Validating Complex Models Accurately and Without Contact 1.1 Introduction 1.2 MDV for Real-World Applications 1.3 MDV: A Novel Approach 1.4 Quantifying Performance 1.5 Applications for Visible Laser-Based Vibrometer 1.6 Test Setup for Modal Analysis 1.7 Excitation Methods 1.8 Application Example 1: Characterization of Biological Tissue 1.9 Application Example 2: Modal Test on a Composite Panel 1.10 Application Example 3: Noncontact Strain Monitoring 1.11 Conclusion References 2 DIC Using Low Speed Cameras on a Scaled Wind Turbine Blade 2.1 Introduction 2.2 Background 2.3 Experimental Setup and Results 2.3.1 DIC Results 2.3.2 Accelerometers Results 2.3.3 Comparison Between Accelerometers and DIC Results 2.3.4 FEA Results 2.3.5 Correlation with Accelerometers Mode Set 2.3.6 Correlation with DIC Mode Set 2.4 Conclusions References 3 Data Challenges for Structural Health Monitoring of Electrical Machines 3.1 Introduction 3.2 Experimental Data 3.2.1 Adaptive Frequency 3.2.2 Modified Kalman Filter 3.2.3 Spectral Subtraction 3.2.4 Analysis of Raw Current Data 3.2.5 Acceleration Data Analysis 3.3 Conclusion References 4 Neuromorphic Data Processing for Event-Driven Imagery for Acoustic Measurements 4.1 Introduction 4.2 Background 4.3 LMU Definite Integration and Fourier Transform 4.4 LMU Beamforming 4.5 Conclusion References 5 Template Matching and Particle Filtering for Structural Identification of High- and Low-Frequency Vibration 5.1 Introduction 5.2 Background 5.3 Analysis 5.3.1 Beam Experiment 5.3.2 Bridge Test 5.4 Conclusion References 6 Multi-Sensor Collaborative Sampling Schemes to Reconstruct Undersampled Mechanical System Signals for Machinery Fault Detection 6.1 Introduction 6.1.1 Background 6.1.2 Motivation 6.1.3 Purpose 6.2 Experimental Methods 6.2.1 Modeling and Simulation 6.2.2 Data Acquisition 6.2.3 Signal Processing 6.2.4 Experimental Setup 6.2.5 Data Acquisition, Hardware, and Testing Parameters 6.2.6 Data Collection and Signal Processing 6.2.7 Data Analysis 6.2.8 Metrics 6.3 Results 6.3.1 Effect of Time Delay on Signal Reconstruction 6.3.2 Effect of Sampling Rate on Signal Reconstruction 6.4 Conclusions References 7 Regime Sorting for Multiscale Vibrations and Phase-Based Motion Extraction 7.1 Introduction 7.2 Theory 7.3 Implementation 7.4 Verification 7.4.1 Synthetic 7.4.2 Experimental 7.5 Complicated Scenes 7.6 Conclusions References 8 Digital Image Correlation with a Neuromorphic Event-Based Imager 8.1 Introduction 8.2 Latex Band Test 8.3 Conclusion References 9 Monitoring the Response of Electrical Components During Environmental Vibration Tests Using a Scanning Laser Doppler Vibrometer Nomenclature 9.1 Introduction 9.2 Experimental Setup 9.3 Results 9.3.1 Comparison Between Accelerometer and Noncontact Velocity Response Measurements 9.3.2 Full-Field Operational Modal Analysis 9.4 Conclusion References 10 Advanced Mesh Reconstruction with Low-Budget RGBD Hardware for Modal Analysis 10.1 Introduction 10.2 Background 10.3 Technical Implementation 10.4 Data Acquisition 10.5 Data Sources 10.6 Data Quality Check 10.7 Data Preparation 10.8 Results 10.9 Conclusions and Outlook References 11 Stereoscopic High Speed Camera Based Operational Modal Analysis Using a One-CameraSetup 11.1 Introduction 11.2 Experimental Setup 11.2.1 Equipment 11.2.2 Setup 11.2.3 Lucas–Kanade Displacement Identification 11.2.4 3D Reconstruction Equations 11.3 Experimental Results 11.3.1 Comparison with Accelerometer Results 11.3.2 OMA 11.4 Conclusion References 12 In-plane Vibration Measurement of an Aluminum Plate Using a Three-Dimensional Continuously Scanning Laser Doppler Vibrometer System 12.1 Introduction 12.2 Instrument and Method for Measuring In-plane ODSs of a Platelike Structure 12.3 Experimental Investigation 12.4 Conclusion References 13 Measuring Full-Field Deformation in Ultra-High-Performance Concrete Structural Components Using Tag-Based Robotic Vision 13.1 Introduction 13.2 Methodology 13.2.1 Pinhole Camera Model 13.2.2 Bundle Adjustment Algorithm 13.2.3 Levenberg-Marquardt Algorithm 13.3 Experimental Setup 13.3.1 Tag-Based Detection Method 13.3.2 Deployments of Cameras 13.3.3 Concrete Beam Bending 13.4 Result and Discussion 13.4.1 Tag-Based Detection 13.4.2 Concrete Beam Bending 13.5 Conclusion and Future Work References 14 Dynamic Behaviour and Magneto-Mechanical Efficiency of a Contactless MagneticTransmission 14.1 Introduction 14.2 Mechanical Planetary Gear Train Versus Planetary Magnetic Gear 14.3 Design and Realisation of a Contactless Magnetic Transmission 14.3.1 Dynamic Analysis Using Matlab/Simulink 14.3.2 Design of a Magnetic Gear and Dedicated Test Rig 14.4 No-Load Experiments 14.5 Conclusion References 15 Structural Damage Identification for Plate-Like Structures Using Two-Dimensional Teager Energy Operator-Wavelet Transform 15.1 Introduction 15.2 Methodology 15.2.1 Formulation of 2D-CPFW for Plate-Like Structures 15.2.2 Local Anomalies Intensified from Ws,t Curvature of Ws,t Local Anomalies Intensification Using TEO 15.2.3 Damage Identification Based on Intensified Anomalies 15.3 Numerical Investigation 15.3.1 Numerical Test Specimen and Finite Element Model 15.3.2 Numerical Damage Identification Results and Discussion 15.4 Concluding Remarks References 16 A Vision-Based Quantification Approach for Reinforced Concrete Tunnel Liner Delamination 16.1 Introduction 16.2 Background 16.3 Analysis 16.4 Conclusion References 17 An Optical Temporal and Spatial Vibration-Based Damage Detection Using Convolutional Neural Networks and Long Short-Term Memory 17.1 Introduction 17.2 Phase-Based Motion Magnification 17.3 Convolutional Neural Networks 17.4 Long Short-Term Memory Network 17.5 Methodology 17.6 Conclusion References 18 A Hybrid-Attention-LSTM-Based Deep Convolutional Neural Network to Extract Modal Frequencies from Limited Data Using Transfer Learning 18.1 Introduction 18.2 Research Perspectives 18.3 Performance Matrix 18.3.1 Evaluation Metric and Generalizability 18.3.2 Extrapolability and Transfer Learning 18.4 Conclusion References 19 Detecting and Reconstructing the 3D Geometry of Subsurface Structural Damages Using Full-Field Image-Based Sensing and Topology Optimization 19.1 Introduction 19.2 The Proposed Approach 19.2.1 Optimization Problem for Damage Detection 19.3 Experimental Setup 19.4 Results 19.5 Conclusion References 20 Optimal Kernel Design for the Extraction of Subtle Motions Using Convolutional NeuralNetwork 20.1 Introduction and Research Perspective 20.2 Sensitivity of the Learned Kernels Compared to Gabor Kernels 20.3 Conclusion References