Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6

Preface	6
Contents	7
1 WaveAR: A Real-Time Sensor-Based Augmented Reality Implementation for Operating Deflection Shapes	9
1.1 Introduction	9
1.2 Background	10
1.3 Technical Implementation	10
1.3.1 Acceleration and Simplification of the Measurement Configuration for Electromechanical Sensors	11
1.3.2 Universal Data Acquisition Interface	11
1.3.3 Real-Time Visualization in the Form of an AR Application	12
1.4 Measurement Setup	13
1.5 Analysis	13
1.6 Conclusion	14
References	16
2 Full-Field 3D Mode Shape Measurement Using the Multiview Spectral Optical Flow Imaging Method	17
2.1 Introduction	17
2.2 Theoretical Background	18
2.3 Preliminary Experiment	18
2.4 Conclusions	19
References	20
3 Stereophotogrammetry Camera Pose Optimization	21
3.1 Introduction	21
3.2 General Stereophotogrammetry Setup	22
3.3 Stereo Pose Optimization	23
3.3.1 User Inputs	23
3.3.2 Setup: Establish Bounding Box	24
3.3.3 Pose Estimation	25
3.3.4 Pose Validation	28
3.3.5 Evaluating Output and Final Pose Selection	30
3.4 Predicting Observable Pixel Displacements with FEM	34
3.4.1 Algorithm to Determine Node Visibility from Camera Placements	34
3.4.2 Definition of Frequency Response Functions to Assess Arbitrary Inputs	38
3.4.3 Transformation to Modal Coordinates to Acquire Pixel Displacements for Modes of Interest	40
3.5 Conclusions and Future Work	44
References	45
4 Simplified Finite Element Models of Pyramidal Truss Sandwich Panels with Welded Joints for Dynamic Analysis and Their Experimental Validation	47
4.1 Introduction	47
4.2 Methodology	48
4.3 Results of Numerical Analysis	53
4.4 Experimental Validation	55
4.5 Conclusion	56
References	57
5 Operational Modal Analysis of Rotating Structures Under Ambient Excitation Using Tracking Continuously Scanning Laser Doppler Vibrometry	58
5.1 Introduction	58
5.2 Methodology	59
5.3 Experimental Setup	62
5.4 OMA Results	63
5.5 Conclusion	64
References	64
6 Delamination Detection in Fiber Metal Laminates Using Ultrasonic Wavefield Imaging	66
6.1 Introduction	66
6.2 Literature Review	67
6.3 Model Setup	68
6.4 Feature Extraction Process	68
6.4.1 Detrended Hilbert Envelope Magnitude (DHEM)	69
6.4.2 Low-Pass Local Phase Derivative (LLPD)	70
6.5 Qualitative Evaluation of the Feature Performance	72
6.5.1 Score Metric to Quantify the Feature Performance	76
6.5.2 Experimental Comparisons	77
6.6 Conclusion	78
References	79
7 One-Dimensional Convolutional Neural Networks for Real-Time Damage Detection of Rotating Machinery	80
7.1 Introduction and Overview of One-Dimensional CNNs	80
7.2 Proposed Methodology	82
7.3 Laboratory Setup for Bearing Tests	84
7.4 Damage Detection Results	84
7.5 Performance Evaluation in the Presence of Noisy Data	86
7.6 Computational Complexity Analysis	88
7.7 Conclusions	88
References	89
8 A Practical Guide to Motion Magnification	91
8.1 Introduction	91
8.2 Methodologies	92
8.2.1 Intensity	92
8.2.2 Fourier Transform	93
8.2.3 Complex Steerable Pyramid	94
8.2.4 Riesz Pyramid	95
8.3 General Guidelines for Use	95
8.4 Conclusion	97
References	97
9 Squeeze Film Damper Experimental and Numerical Correlation: Test Setup Description and Parameter Identification of Dry System	98
9.1 Introduction	98
9.2 Damper Test Stand Description	99
9.3 Closed-Form Solution	100
9.4 Experimental Procedure and Results	102
9.5 Numerical Modeling Procedure and Results	102
9.5.1 Model Description	103
9.5.2 Diaphragm Stiffness from Model	104
9.5.3 Numerical Modal and Harmonic Analysis	105
9.6 Comparison	105
9.7 Conclusion	107
References	107
10 Full-Field Modal Analysis by Using Digital Image Correlation Technique	109
10.1 Introduction	109
10.2 Background	110
10.2.1 Low Speed Camera for High Frequency Behavior Characterization	110
10.3 Experimental Setup and Results	111
10.3.1 Demo Airplane	111
10.3.2 Car Tire	112
10.4 Conclusion	115
References	116
11 Validating Complex Models Accurately and Without Contact Using Scanning Laser Doppler Vibrometry (SLDV)	117
11.1 Introduction	117
11.2 Test Case Scenarios for Vibrometry	118
11.3 Measurement Principle of a Vibrometer	118
11.4 Choosing a Vibrometer Configuration	120
11.5 Optimizing Setup and Test Parameters	120
11.6 Application Example 1: Modal Test on a Turbine Wheel [1]	121
11.7 Application Example 2: Traveling Ultrasonic Wave Analysis	123
11.8 Application Example 3: Dynamic Stress and Strain Characterization [2, 3]	125
11.9 Conclusion	126
References	128
12 Effect of Different Test Setup Configurations on the Identification of Modal Parameters from Digital Image Correlation	129
12.1 Introduction	129
12.2 Aliased Acquisition with Low-Speed Camera	130
12.3 Experimental Setup	131
12.3.1 Test Item	131
12.3.2 FRF Testing	131
12.3.3 Camera Setup/Measurement Chain	132
12.4 Results	133
12.4.1 Type of Excitation	133
12.4.2 Number of Averages	134
12.4.3 Extended Frequency Range	136
12.4.4 Effect of Speckling the Surface	137
12.5 Conclusion	138
References	138
13 WaveImage – Order ODS for Rotating Machineries	139
13.1 Introduction	139
13.2 Background	140
13.2.1 Order Analysis	140
13.2.2 Operating Deflection Shapes	141
13.2.3 Optical Flow Analysis	142
13.2.4 Measurement Setup	142
13.3 Analysis	143
13.4 Conclusion	145
References	145
14 Multi-Level Damage Detection Using Octree Partitioning Algorithm	147
14.1 Introduction	147
14.2 The Proposed Algorithm	148
14.3 Conclusion	149
References	150
15 Photogrammetry-Based Experimental Modal Analysis for Plate Structures	151
15.1 Introduction	151
15.2 Methodology	152
15.2.1 Kinematic Relation	152
15.2.2 Point-Tracking Technique	153
15.2.3 Photogrammetry-Based EMA	155
15.3 Experimental Investigation	155
15.3.1 Experimental Setup	155
15.3.2 Data Processing	156
15.3.3 EMA Method Results	157
15.4 Conclusion	158
References	159
16 An Optical Mode Shape-Based Damage Detection Using Convolutional Neural Networks	160
16.1 Introduction	160
16.2 Phase-Based Motion Magnification	161
16.3 Convolutional Neural Networks	161
16.4 Methodology	161
16.5 Conclusion	164
References	164
17 Full-Field 3D Experimental Modal Analysis from Dynamic Point Clouds Measured Using a Time-of-Flight Imager	166
17.1 Introduction	166
17.2 Background	167
17.3 Analysis	168
17.4 Conclusions	168
References	168
18 Application of a U-Net Convolutional Neural Network to Ultrasonic Wavefield Measurements for Defect Characterization	170
18.1 Introduction	170
18.2 Background	172
18.2.1 Convolutional Neural Networks	172
18.2.2 Image Segmentation	173
18.3 Methodology	173
18.3.1 Project Overview	173
18.3.2 Dataset Generation	174
18.3.3 Image Processing	176
18.3.4 Data Augmentation	176
18.3.5 CNN Training	177
18.4 Results and Discussion	179
18.5 Conclusion	183
References	183
19 Application of the RASTAR Method to Continuous Scanning LDV Measurements	185
19.1 Introduction	185
19.2 Test Structure, Setup, and Experimental Method	186
19.3 Results and Analysis	188
19.4 Conclusions	190
References	192

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