European Workshop on Structural Health Monitoring (eBook)

Preface 6
Organization 12
Program Chairs 12
Program Committee 12
Contents 13
Guided Waves in Structures for SHM 24
Numerical Investigations on the Influence of Prestress on Lamb Wave Propagation 25
1 Introduction 25
2 Modeling Approach and Mechanical Description 26
2.1 Modeling Approach 26
2.2 Mechanical Description 27
2.3 Dispersion Diagrams via the Eigenvalue Problem 29
3 Experimental and Numerical Results 30
3.1 Dispersion Diagram Without Prestress 31
3.2 Influence of Prestress in Experimental and Numerical Data 31
4 Conclusion and Outlook 33
References 33
Damage Assessment in Composite Material Using Air-Coupled Transducers 35
Abstract 35
1 Introduction 35
2 Experimental Set-Up 36
3 Non-contact ACT-Based Elastic Waves Generation 37
4 Dispersion Curves Extraction 38
5 Teflon Inserts Localization Results 39
5.1 Full Wavefield Results - Piezoelectric Transducer 40
5.2 Full Wavefield Results - Air-Coupled Transducers 40
6 Conclusions 43
Acknowledgements 44
References 44
A Numerical Study on Baseline-Free Damage Detection Using Frequency Steerable Acoustic Transducers 46
Abstract 46
1 Introduction 46
2 Damage Detection with Frequency Steerable Acoustic Transducers 47
3 Numerical Simulations 49
3.1 Numerical Model 49
3.2 FSAT Directivity Characteristics 49
3.3 Damage Scenarios 50
4 Results of Damage Detection and Localization 51
5 Conclusions and Future Plans 54
Acknowledgments 54
References 55
Influence of Operational and Environmental Conditions on Lamb Wave Signals 56
Abstract 56
1 Introduction 56
2 Measurement Set-Up 57
3 Evaluation of Measured Data 58
3.1 Temperature Effect 58
3.2 Damage Effect 62
4 Conclusion 64
Acknowledgment 64
References 65
Use of Deep Learning Techniques for Damage Localization in Aeronautical Composite Structures 66
Abstract 66
1 Introduction 66
2 Methods and Experimental Setup 67
2.1 Convolutional Neural Network for Distances Estimation 67
2.2 Damage Localization Algorithm 68
2.3 Experimental Setup 69
2.4 Additional Data Acquisition for Testing 71
3 Results 71
3.1 CNN Model Training 71
3.2 Damage Localization and Imaging Results 72
4 Conclusion 73
References 73
Temperature and Damage-Affected Lamb Wave Signals in a Composite Sandwich Plate 74
Abstract 74
1 Introduction 74
2 Materials and Methods 75
3 Results 76
3.1 Climatic Chamber 76
3.2 Temperature and Damage Affected Signals 78
3.3 Impact Damage 78
4 Discussion 81
5 Conclusion 81
Acknowledgments 81
References 81
Numerical Investigation of Application of Unidirectional Generation to Improve Signal Interpretation of Circumferential Guided Waves in Pipes for Defect Detection 83
Abstract 83
1 Introduction 83
2 Circumferential SH Waves and Unidirectional Generation 85
2.1 Circumferential SH Waves 85
2.2 Unidirectional Generation of SH Waves 85
2.3 Reflection from a Defect 86
3 Finite Element Model 87
4 Results and Discussion 88
5 Conclusion 91
Acknowledgments 91
References 91
Guided Waves Benchmark Dataset and Classifier Comparison 93
1 Introduction 93
2 Benchmark Dataset Description 94
2.1 General Description and Experimental Setup 94
2.2 Aircraft Specimens Fatigue Subset (Section A) 94
2.3 Variable Environmental Conditions Subset (Section B) 95
2.4 Composite Specimens Subset (Section C) 95
3 Examples of Testing Approaches 97
3.1 Fatigue Specimen Classification Example 97
3.2 Composite Specimen Localization Example 98
4 Research Suggestions and Future of the Dataset 98
5 Summary and Conclusions 100
References 100
Dual Mode Inspection Using Guided Waves and Phased Array Ultrasonics from a Single Transducer 101
1 Introduction 101
2 Modal Analysis Formulation 102
3 Guided Wave Excitation with a Phased Array 104
4 Simulation Results 105
5 Experimental Results 107
5.1 Experimental 2DFFT 107
5.2 Guided Wave Scan 107
5.3 Phased Array Inspection 109
6 Conclusions 109
References 110
Enhanced Simulation of Guided Waves and Damage Localization in Composite Strips Using the Multiresolution Finite Wavelet Domain Method 111
Abstract 111
1 Introduction 111
2 Theoretical Background 113
2.1 Daubechies Wavelets and the Multiresolution Approximation 113
2.2 The Multiresolution Finite Wavelet Domain Method 114
2.3 High-order Layerwise Laminate Theory 115
3 Numerical Results 116
3.1 Composite Beam with First-order Shear Kinematic Assumptions 116
3.2 Composite Beam Using HLLT 117
4 Conclusions 119
References 120
Fully Integrated Hybrid “Piezoelectric/Fiber Optic” Acousto-Ultrasound Sensor Network (FAULSense™) SHM System 122
Abstract 122
1 Introduction 122
1.1 Advanced Composites in Aircraft Structures 125
2 Integrated Hybrid Structural Health Monitoring (SHM) System 125
3 FAULSense System Development and Test Results 127
4 Conclusions 130
Acknowledgements 130
References 130
Guided Wave-Gaussian Mixture Model for Damage Quantification Under Uncertainty 131
Abstract 131
1 Introduction 131
2 GW-GMM Based Crack Quantification Method 132
2.1 The GW-GMM Based Crack Quantification Process 132
2.2 Modeling and Migration Process of GMM 133
3 Validation on the Aircraft Lug Specimen 135
3.1 Experimental Setup 135
3.2 GW Features Extraction Under Uncertainty 136
3.3 Calibration Model of Crack Length with MI 136
3.4 Online Damage Quantitative Diagnosis Results 138
4 Conclusion 138
Acknowledgements 138
References 139
Damage Size Quantification Using Lamb Waves by Analytical Model Identification 141
Abstract 141
1 Introduction 141
2 Analytical Model 143
2.1 Actuator Model 143
2.2 Scattering Model 144
3 Sensor Model 147
4 Identification Algorithm 147
5 Application on Simulation Data 148
6 Conclusion 149
References 149
Efficient Layerwise Time-Domain Spectral Finite Element for Guided Wave Propagation Analysis of Multi-layered Panels 150
1 Introduction 150
2 Methodology 152
3 Numerical Results and Discussion 153
3.1 Free Vibration Analysis 153
3.2 Lamb Wave Propagation 154
3.3 Comparison of SFE with Conventional FE 157
3.4 Lamb Wave Propagation Under Transverse Excitation 157
4 Conclusions 158
References 159
A Bayesian Approach to Lamb-Wave Dispersion Curve Material Identification in Composite Plates 161
1 Introduction 161
2 Methods 163
2.1 Dispersion Curve Solutions for Orthotropic Media 163
2.2 Measuring {,} 164
2.3 Estimating Elastic Constants 164
2.4 Sampling over the Posterior Distribution 165
3 Results 166
4 Conclusions and Further Work 169
References 170
Damage Detection Based on Voltage Transfer Ratio Approach and Bayesian Classifier 172
1 Introduction 172
2 Bayesian Decision Model 173
3 Experiment Description and Experimental Data Evaluation 177
4 Summary 181
References 181
Remote Excitation Ultrasonic Waveguide-Based SHM for Critical Applications 182
Abstract 182
1 Introduction 182
1.1 Structural Health Monitoring (SHM) 182
1.2 Ultrasonic Guided Wave-Based Waveguide 183
2 Experimental Setup 184
2.1 Design of Waveguide 184
3 SHM of Plate Structure 185
3.1 Generation of S0 Mode in Plate 185
3.2 Generation of SH0 Mode in Plate 186
4 Fem Simulation Studies 188
5 Conclusion 190
References 190
Development of GUI Based Tool for the Visualization of the FBG Spectrum Subjected to Guided Waves 192
Abstract 192
1 Introduction 192
2 Models Studied and Calculation Process Used 193
2.1 Numerical Settings 193
2.2 FBG Based Software 195
2.3 Theoretical Calculations and Background 195
3 GUI Matlab Based Software 197
3.1 FBG Strain Calculations 197
3.2 Validation 199
4 Conclusion 200
Acknowledgements 200
References 200
Weld Defect Location Method of U-Shaped Crane Boom Based on Helical Guided Waves 202
Abstract 202
1 Introduction 202
2 Theoretical Background 203
2.1 Elliptical Imaging Algorithm 203
2.2 Intelligent Defect Location Algorithm 205
3 Propagation Characteristics of Helical Guided Waves in U-shaped Boom 208
4 Experimental Validation 210
5 Conclusion 215
6 Declaration of Conflicting Interests 215
Funding 216
References 216
The Effect of the Infill Density in 3D-Printed PLA on Lamb Waves’ Propagation Characteristics and their Sensitivity to the Presence of Damage 217
Abstract 217
1 Introduction 217
2 Experiment Setup 218
3 Dispersion Analysis 220
4 Damage Imaging 222
5 Conclusions 224
Acknowledgments 224
References 224
Monitoring Dendrite Formation in Aqueous Zinc Batteries with SH0 Guided Waves 226
Abstract 226
1 Measurement Principle and Experimental Setup 227
1.1 Measurement Principle 227
1.2 Experimental Setup 227
1.3 Measurement Protocol 228
2 Results 229
2.1 Optical Results 229
2.2 Ultrasonic Results 229
3 Discussion 230
4 Conclusion 232
References 232
Stress Monitoring of Plates by Means of Nonlinear Guided Waves 234
1 Introduction 234
2 Equations of Motion 235
3 Finite Element Simulations 236
4 The Second-Harmonic Resonant Wave 238
4.1 Dependence of the Response on the Initial State of Prestress 239
4.2 Resonance Condition and Interaction Between Primary and Secondary Waves 240
5 Conclusion 241
References 242
Assessment of Stringer Debonding by Guided Wave Inspection in Composite Structures 243
1 Introduction 243
2 Introduction 244
2.1 Propagation Model 244
2.2 Damage Detection Approach 246
2.3 Numerical Model 246
3 Results 248
4 Discussion 250
5 Concluding Remarks 251
References 251
Computational Lamb Wave Analysis of a CFRP Shortened Curing Cycle 253
Abstract 253
1 Introduction 253
2 Experimental Cure Monitoring 255
2.1 Ultrasonic Cycle Shortening 255
2.2 Dynamic Mechanical Analysis 256
3 The Computational Model 257
3.1 Combined Modules 257
3.2 Results and Discussion 259
4 Conclusion 261
References 262
Guided Wave-Based Assessment of Bonded Composite Joints 264
1 Introduction 264
2 Fabrication of Composite Coupons 265
3 Guided Wave-Based Assessment of Kissing Bonds 266
3.1 Experimental Setup 267
3.2 Residual Bond Strength Characterization 268
4 NDE Results and Comparison with Destructive Tests 271
5 Conclusions 272
References 272
Modeling Magnetostrictive Transducers for SH Guided Wave Generation and Reception for Structural Health Monitoring 274
Abstract 274
1 Introduction 274
2 Model Setup 275
3 Modeling Results and Discussion 276
3.1 Mode Control Plot 276
3.2 Lift-Off Distance Effect 277
3.3 Adhesive Layer Effect 278
3.4 Two-Sided Transducer 280
4 Conclusions 281
References 282
Experimental Identification of Damage in Single Lap Joint 283
1 Introduction 283
2 Materials and Methods 285
2.1 Experimental Setup 285
2.2 Analytical Model 286
3 Results and Discussion 288
4 Conclusions 291
References 291
Damage Detection in Rods via Use of a Genetic Algorithm and a Deep-Learning Based Surrogate 294
1 Introduction 294
2 Cracked Rod Spectral Element Model 295
3 Deep-Learning-Based Surrogate Model 296
4 Genetic Algorithm for Damage Detection 296
4.1 Selection 297
4.2 Crossover 298
4.3 Mutation 299
5 Damage Detection Results 299
6 Conclusions 300
References 301
Ultrasonic Damage Assessment Using Virtual Time Reversal Indices and the RAPID Method 303
Abstract 303
1 Introduction 303
2 Theoretical Framework 304
3 Experimental Set-Up 308
4 Ultrasonic Imaging Results 309
5 Conclusions 312
References 312
Improved Detection of Localized Damage in Pipe-Like Structures Using Gradient-Index Phononic Crystal Lens 314
Abstract 314
1 Introduction 314
2 Methods and Models 315
3 Results and Discussion 316
4 Conclusions 320
Acknowledgment 320
References 320
Machine Learning and Modelling in Structural Health Monitoring 322
Optimized Electromechanical Impedance Spectroscopy Using Minimal Number of Test Frequencies 323
1 Introduction 323
2 Materials and Methods 324
2.1 Experimental Setup for Impedance Measurements up to 100 kHz 324
2.2 Measuring Protocol for the Aluminum Plate with Different Size Drilled Holes 325
2.3 Statistical Analysis of the Conductance Data 325
3 Results 327
3.1 Distance-Based Clustering of the Data 327
3.2 Tree Classifiers for Semi-supervised Learning 328
4 Discussion 329
5 Conclusion 330
References 330
A New Unsupervised Learning Approach for CWRU Bearing State Distinction 332
Abstract 332
1 Introduction 332
2 CWRU Bearing Dataset 334
3 Proposed Approach 335
3.1 Data Selection 336
3.2 Measurement Segmentation 336
3.3 Segment Transformation 337
3.4 Feature Extraction 337
3.5 Feature Clustering 337
4 Results 338
5 Conclusion 338
References 339
Machine Learning Based Predictive Modelling of a Steel Railway Bridge for Damage Modelling of Train Passages and Different Usage Scenarios 340
1 Introduction 340
2 Methodology 341
2.1 Data Gathering and Processing 341
2.2 Train Passage Data Set 342
2.3 Predictive Model 343
3 Results 344
4 Modelling Usage Scenarios 345
4.1 Train Speed Scenario 345
4.2 Train Configuration Scenario 347
5 Conclusion 348
References 348
Damage Detection in Composites by AI and High-Order Modelling Surface-Strain-Displacement Analysis 350
1 Introduction 350
2 Refined 1D Models 351
3 Damage Formulation 352
4 CNN for Damage Detection 352
4.1 CNN Architecture 352
4.2 CNN Training Process 353
5 Numerical Results 353
6 Conclusions 356
References 357
Adding Autonomy to Robotic Enabled Sensing 358
Abstract 358
1 Introduction 358
2 Autonomous Pose Correction 359
2.1 Sensor Orientation 360
2.2 Sensor Standoff 362
3 Autonomous Geometry Discovery 362
3.1 On-Line Computation of Next-Best-Pose 362
3.2 Progressive Mesh Growth 363
3.3 Inspection Confinement and Collision Avoidance 364
3.4 Termination Criteria 365
4 Simulations 365
5 Conclusions 367
Acknowledgements 367
References 367
Anomaly Detection in Vibration Signals for Structural Health Monitoring of an Offshore Wind Turbine 368
1 Introduction 368
2 Case Presentation and Data Exploration 369
3 Methodologies and Results 372
3.1 Evaluation Metric 372
3.2 Baselines Models 373
3.3 Proposed Approach 373
4 Conclusion 377
References 377
Global Health Assessment of Structures Using NDT and Machine Learning 379
Abstract 379
1 Introduction 379
2 Need for Structural Health Assessment 380
3 Advances in SHA 381
4 Case Study: Assessment of Global Behaviour of RCC Building Using NDT and ML 381
5 Global Behaviour of the Structure Using Traditional Method 382
5.1 Methodology 382
5.2 Visual Inspection 383
5.3 Condition Mapping 384
5.4 Non-Destructive Testing 385
5.5 Numerical Modelling and Analysis 386
6 Global Behaviour Through Machine Learning 387
6.1 Data Collection 387
6.2 Support Vector Machine (SVM) 387
6.3 Results and Discussion 388
7 Conclusion 389
References 389
A Review on Technological Advancements in the Field of Data Driven Structural Health Monitoring 391
Abstract 391
1 Introduction 391
2 Structural Health Monitoring Using Data Driven 393
2.1 Vibration Based Structural Health Monitoring 393
2.2 Vision Based Structural Health Monitoring 396
3 Conclusions 398
References 398
Physical Covariance Functions for Dynamic Systems with Time-Dependent Parameters 401
1 Introduction 401
2 Deriving Physical Covariance Functions 403
2.1 Uninformed Gaussian Process Priors 403
2.2 Towards Physically Representative Covariance Functions 404
2.3 Handling Parameters with a Time-Dependency 405
3 A Comparison Between Kernel Performance 406
4 Concluding Remarks 410
References 410
Damage Assessment of an Aircraft’s Wing Spar Using Gaussian Process Regressors 412
Abstract 412
1 Introduction 412
2 The Finite Element Model 413
3 Damage Identification Framework and Results 415
3.1 Using Strain to Infer Damage Parameters 415
3.2 Assessing Damage Criticality 417
4 Conclusions 419
References 419
Experimental Damage Localization and Quantification with a Numerically Trained Convolutional Neural Network 421
Abstract 421
1 Introduction 421
2 Database Computation 422
3 Networks Architectures 424
4 Networks Evaluation 426
5 Conclusion 426
References 427
On the Application of Partial Domain Adaptation for PBSHM 428
1 Introduction 428
2 Domain Adaptation 429
2.1 Normal Condition Alignment 429
2.2 Balanced Distribution Adaptation 430
2.3 Instance-Weighting for Partial Domain Adaptation 432
3 Case Study: Numerical Three-Storey and Four-Storey Population 433
3.1 Simulation 433
3.2 Comparison Procedure 434
3.3 Results 435
4 Discussion and Conclusions 436
A Material Properties 437
References 437
Intelligent Health Indicators Based on Semi-supervised Learning Utilizing Acoustic Emission Data 439
Abstract 439
1 Introduction 439
2 Experimental Setup 441
3 Workflow 442
3.1 Signal Pre-processing 442
3.2 Feature Extraction (FE) 442
3.3 Feature Fusion 443
4 Results and Discussions 446
5 Conclusions 447
Funding 448
References 448
Supervised Deep Learning Algorithms for Delaminations Detection on Composites Panels by Wave Propagation Signals Analysis 449
Abstract 449
1 Introduction 449
2 Convolutional Neural Networks 450
3 SHM Algorithm Implementation 451
3.1 Numerical Model and Signal Analysis 451
3.2 RGB Images Generation 454
3.3 Images Analysis 455
3.4 Confusion Matrix 456
3.5 Classification with 0.072? lessthan ?DI? lessthan ?1.26 457
4 Conclusions 460
References 460
Site-Specific Defect Detection in Composite Using Solitary Waves Based on Deep Learning 462
Abstract 462
1 Introduction 462
2 Experimental Setup for HNSW Datasets 463
3 CNN Architectures for Defect Detection in Composites 465
4 Results and Discussion 467
5 Conclusion 469
Acknowledgements 469
References 470
Machine Learning Based Classification of Guided Wave Signals in the Context of Inter-specimen Variabilities 472
1 Introduction 472
2 Experimental Setup 474
3 Signal Processing and Data Preparation 475
3.1 Labeling Process: Path Identification 475
3.2 Disassociating Coupon Connection Between Pristine and Damaged States 476
4 Defect Detection Methodology 477
4.1 Feature Extraction Using Autoregression 477
4.2 Classification 478
5 Experimental Validation Results 479
5.1 Data Requirement Study 479
5.2 Performance Comparison 479
6 Conclusion and Perspective 480
References 480
Bayesian Changepoint Modelling for Reference-Free Damage Detection with Acoustic Emission Data 482
1 Introduction 482
2 Bayesian Online Change Point Detection 484
2.1 Bayesian Identification 484
2.2 Initialising the Model 486
3 Data Collection 486
4 Results and Discussion 487
5 Concluding Remarks and Future Work 490
References 490
Integrating Physical Knowledge into Gaussian Process Regression Models for Probabilistic Fatigue Assessment 492
1 Introduction 492
2 Methodology 494
2.1 Gaussian Process Regression 494
2.2 Description of SDOF Covariance Function 495
3 Interpretation of Model Variance 495
3.1 Interpreting the Confidence Intervals from Physics Derived Kernels 495
3.2 Combining Covariance Functions 496
4 Case Study 496
5 Discussion and Conclusions 499
References 501
Hybrid Training of Supervised Machine Learning Algorithms for Damage Identification in Bridges 502
Abstract 502
1 Introduction 502
2 Z-24 Bridge and Monitoring Data 503
3 Finite Element Model and Hybrid Training Matrix 504
4 Supervised Algorithms Training and Damage Identification 507
5 Conclusions 511
References 511
Imbalanced Multi-class Classification of Structural Damage in a Wind Turbine Foundation 512
1 Introduction 513
2 Theoretical Background 514
2.1 Mean Centered Unitary Group Scaling (MCUGS) 514
2.2 Principal Component Analysis (PCA) 514
2.3 Extreme Gradient Boosting (XGBoost) Classifier 514
3 Dataset for Validation 515
4 Damage Classification Methodology 516
5 Results and Discussion 517
6 Conclusions 519
References 519
Dynamic Behavior Analysis of a Rotor-Bearing-Squeeze Film Damper Coupling System with Bearing Outer Race Localized Defect 521
Abstract 521
1 Introduction 522
2 Modeling of the RBSC System 522
2.1 Bearing Force Model Considering Centrifugal Load 523
2.2 SFD Nonlinear Oil-Film Force Model 526
2.3 Governing Equations of Motion 527
3 Simulation and Discussion 528
4 Conclusions 530
Acknowledgment 530
References 530
Wave Propagation Modeling via Neural Networks for Emulating a Wave Response Signal 532
1 Introduction 533
2 Dataset Generation 533
3 Neural Network Framework 534
3.1 Deep Convolutional Autoencoder (DCAE) 534
3.2 Feed-Forward Neural Network (FFNN) 536
3.3 Training of the Neural Network Framework 536
4 Results 536
5 Conclusions and Future Work 539
References 539
Delamination Identification Using Global Convolution Networks 541
1 Introduction 541
2 Methodology 543
2.1 Dataset 543
2.2 Data Preprocessing 543
3 Semantic Segmentation Models 544
3.1 Global Convolutional Network 544
4 Results and Discussions 545
4.1 Numerical Cases 546
4.2 Experimental Case 548
References 548
A Spatial Autoregressive Approach for Wake Field Prediction Across a Wind Farm 550
1 Introduction 550
2 A Small Simulated Wind Farm 552
3 Spatial Autoregressive Models 554
3.1 Linear SPARX Model 554
3.2 Nonlinear SPARX Model 555
3.3 GP-SPARX Model 555
4 Result and Comparison 555
5 Conclusions 558
References 559
ConvLSTM Based Approach for Delamination Identification Using Sequences of Lamb Waves 561
1 Introduction 561
2 Dataset Preparation 563
3 A Brief Introduction to RNN, LSTM and ConvLSTM 564
4 The Proposed Model 565
5 Results and Discussions 566
6 Conclusions 568
References 568
Structural Assessment and Health Monitoring of the Builtup Environment with Satellite Radar Interferometry: Methodologies and Applications 571
The Use DInSAR Technique for the Study of Land Subsidence Associated with Illegal Mining Activities in Zaruma – Ecuador, a Cultural Heritage Cite 572
Abstract 572
1 Introduction 573
2 Study Area 574
2.1 Geological Setting 574
3 Data Set and Methods 575
3.1 Geotechnical Analysis 575
3.2 DInSAR Analysis 576
4 Results 577
4.1 Geotechnical Results 577
4.2 Interferometric Results 578
5 Conclusions 580
References 580
Structural Monitoring of a Masonry Hydraulic Infrastructure in Rome: GIS Integration of SAR Data, Geological Investigation and Historical Surveys 582
Abstract 582
1 Introduction 583
2 Methodology 583
3 Application 583
3.1 3D Model 585
3.2 Preliminary Structural Monitoring and Damage Assessment 586
4 Conclusions 588
References 588
Integration of Multi-source Data to Infer Effects of Gradual Natural Phenomena on Structures 591
Abstract 591
1 Introduction 591
2 Materials and Method 593
2.1 Selected Case Studies 593
2.2 Urban Analyses: Historic Center of Central Archaeological Area 595
2.3 Localized Analysis: The Colosseum 596
3 Results and Discussion 598
References 599
An Application of the DInSAR Technique for the Structural Monitoring of the “Vittorino da Feltre” School Building in Rome 601
Abstract 601
1 Introduction 601
2 Procedure 602
3 The “Vittorino da Feltre” School Building in Rome 603
4 SAR Data 605
5 Structural Damage Survey 609
6 Conclusion 609
References 610
Techniques for Structural Assessment Based on MT-DInSAR Data, Applied to the San Michele Complex in Rome 612
Abstract 612
1 Introduction 613
2 Proposed Comprehensive Approach 613
3 SBAS-DInSAR Methodology Applied to the Area of Rome, Italy 614
4 The San Michele Complex Case Study 614
5 Conclusions 621
References 621
Satellite Interferometric Data and Perturbation Characteristics for Civil Structures at Nanohertz 623
Abstract 623
1 Introduction 623
2 Materials and Method 624
2.1 Time Domain Analysis 624
2.2 Frequency Domain Analysis 625
2.3 Entropy Analysis 625
3 Results and Discussion 626
3.1 Time Domain Analysis 626
3.2 Frequency Domain Analysis 627
3.3 Entropy Analysis 628
4 Conclusions 630
References 630
Standardization and Guidelines on SHM and NDT: Needs and Ongoing Activities 632
Offline Algorithm Selection of CMA-ES Variants in Bayesian Optimal Sensor Placement: Application to Buildings and Recommendations to the Philippine Instrumentation Practice 633
Abstract 633
1 Introduction 633
2 Related Work on OSP in SHM 634
3 Problem Statement and Objectives 635
4 Algorithm Selection in OSP 635
5 Single-Sensor Investigation on a Steel Column 636
6 Application to the ASCE Benchmark Structure 637
6.1 Undamaged Case 637
6.2 Damaged Case 638
7 Comments on the Philippine SHM Practice 639
8 Conclusions and Recommendations 640
Acknowledgments 641
References 641
Small Punch Test Method for SHM 643
Abstract 643
1 Introduction 643
2 Small Punch Test 644
2.1 Material Sampling 644
2.2 SPT Test Set 645
2.3 SPT Test Principles 646
3 Case Study 646
3.1 Small Punch Test vs Uniaxial Tensile Test 647
3.2 Ductile-Brittle Transition Temperature 648
3.3 Results Discussion 650
4 Conclusion 651
References 651
A Preliminary Qualification Approach for Structural Health Monitoring Systems 653
Abstract 653
1 Introduction 653
2 The European Framework for Qualification of Construction Products 654
3 A Proposal for Qualification of Civil SHM Systems 656
4 Case Study and Discussion 658
5 Conclusions and Future Developments 661
Acknowledgments 661
References 661
Smart Self-Sensory Concrete Based Structures and Infrastructures 663
A Review on Non-destructive Evaluation of Civil Structures Using Magnetic Sensors 664
Abstract 664
1 Introduction 664
2 Fundamentals 665
2.1 Magnetic Flux Leakage 665
2.2 Eddy Currents 665
2.3 Hall Effect Sensors 666
2.4 Magnetoresistive Sensors 667
3 Applications 667
3.1 Hall Effect Sensors 667
3.2 Magnetoresistive Sensors 669
4 Discussion and Conclusions 670
References 672
Realization and Testing of Hybrid Textile Reinforced Concrete Prototype Modules Sensorized with Distributed Fiber Optic Sensors 674
Abstract 674
1 Introduction 674
2 Prototypes Preparation 675
3 Testing 678
3.1 Optical Testing 678
3.2 Testing of the Measuring Behaviour 679
4 Conclusions 682
Acknowledgements 682
References 682
Condition Monitoring of Ageing Bridges and Infrastructure 683
Fatigue Analysis on Four Months of Data on a Steel Railway Bridge: Event Detection and Train Features’ Effect on Fatigue Damage 684
Abstract 684
1 Introduction 684
2 Case Study and Measurement Campaign 686
3 Event-Based Methodology 687
3.1 Part I (Event Detection) 687
3.2 Part II (Processing the Events) 688
4 Results and Discussion 691
4.1 Effect of Train Type and Axle Number 691
4.2 Effect of Speed and Direction 692
5 Conclusion 693
Acknowledgments 693
References 693
Effect of Aging of Bearings on the Behavior of Single-Span Railway Bridges 695
1 Introduction 695
2 Numerical Model and Analysis 696
3 Concluding Remarks 702
References 703
Long-Term Structural Monitoring of a Skewed Masonry Arch Railway Bridge Using Fibre Bragg Gratings 704
Abstract 704
1 Introduction 704
1.1 Global Context 704
1.2 CFM-5: the ‘Barkston Road’ Bridge 705
2 The Monitoring Installation at CFM-5 707
2.1 The FBG Sensing Installation 707
2.2 Autonomous, Remote FBG Monitoring 708
3 Results and Discussion 709
3.1 Sensitivity of Bridge Response 709
4 Conclusions 713
References 713
A Novel Procedure for Damping Ratio Identification from Free Vibration Tests with Application to Existing Bridge Decks 714
Abstract 714
1 Introduction 714
2 Modal Component Extraction 715
2.1 Selection of the Signal 715
2.2 Extraction of the Modal Components 716
2.3 Evaluation of Damping Ratios 718
3 Numerical Applications 719
3.1 Theoretical Signal 720
3.2 Real Signal 721
4 Conclusions 723
References 723
A Review on Bridge Instrumentation in the United States 724
Abstract 724
1 Introduction 724
2 Structural Health Monitoring 725
3 Bridge Instrumentation in the U.S. 725
3.1 Golden Gate Bridge 725
3.2 Fred Hartman Bridge 726
3.3 Sunshine Skyway Bridge 726
3.4 Quincy Bayview Bridge 726
3.5 New Benicia-Martinez Bridge 726
3.6 North Halawa Valley Viaduct 727
3.7 Manhattan Bridge 727
3.8 Vincent Thomas Bridge 728
3.9 Mackinac Bridge 728
3.10 Carroll Lee Cropper Bridge 728
3.11 Huey P. Long Bridge 728
3.12 Neville Island Bridge 729
3.13 Birmingham Bridge 729
3.14 Columbia River I-5 Bridge 730
4 Conclusion 730
Acknowledgement 731
References 731
How to Make a Self-sensing House with Distributed Fiber Optic Sensing 733
Abstract 733
1 Introduction 733
2 DFOS Installation and Documentation 734
3 Temperature and Strain Measurements of the Ceiling 736
4 Seasonal Temperature Changes Within the Ground Plate 738
5 Movement of People Within the House 739
6 Conclusion and Outlook 740
References 741
Automation in Documentation of Ageing Masonry Infrastructure Through Image-Based Techniques and Machine Learning 742
Abstract 742
1 Introduction 742
2 Block Segmentation 743
3 Case Study 746
4 Conclusions 748
References 749
Health Monitoring Methodologies and Technologies for Aerospace Actuation and Drive Systems 751
Condition Monitoring of a Gear Box by Acoustic Camera and Machine Learning Techniques 752
Abstract 752
1 Introduction 752
1.1 Statement of the Problem 752
2 Experimental Data Analysis 753
2.1 Experimental Test Rig and Setup 753
2.2 Analysis Procedure 755
3 Analysis of the Results 758
4 Conclusions and Future Applications 760
References 761
Health Monitoring Methodologies for Aerospace Electromechanical Actuation Systems 762
1 Introduction 762
2 Aviation Trends 763
2.1 Advantages and Drawbacks 763
2.2 EMA Requirements 764
2.3 Failure Modes 766
3 Condition Monitoring 767
4 Potential Future Steps 769
5 Concluding Remarks 770
References 771
Ultrasonic and Electromagnetic Waves for Diagnosis, Monitoring and Control 773
Monitoring of Pipelines Using Microwave Structural Health Monitoring 774
1 Introduction 774
2 Theoretical Background 775
2.1 Detection Concept 775
3 Experimental Setup 776
3.1 Experimental Measurements 777
4 Results 778
4.1 Characterization of the Antenna 778
4.2 Damage Detection 779
5 Conclusion and Outlook 781
References 782
Analysis and Compensation of Relative Humidity and Ice Formation Effects for Radar-Based SHM Systems Embedded in Wind Turbine Blades 783
1 Introduction 783
2 Theroretical Background 784
2.1 Wave Excitation 784
3 Experimental Setup 784
3.1 Radar Sensor 784
3.2 Climate Chamber 785
4 Results 786
4.1 Humidity Influence 786
4.2 Environmetal Influence Compensation 787
4.3 Ice Detection 788
5 Summary and Future Work 791
References 792
In-Process Monitoring of Surface Roughness of Internal Channels Using 793
Abstract 793
1 Introduction 793
2 Methodology 794
2.1 Phase-Screen Approximation 794
2.2 Correction of Beam Spreading Effect 795
3 Numerical Simulation 796
3.1 Finite Element Modeling 796
3.2 Simulation Results 796
4 Experimental Validation 798
4.1 Experimental Setup 798
4.2 Experiment Results 799
5 Conclusions 799
References 799
Simultaneous Monitoring of Component Thickness and Internal Temperature Gradient Using Ultrasound 801
1 Introduction 801
2 Measurement Principles 802
2.1 Ultrasonic Thickness Measurement 802
2.2 Ultrasonic Temperature Sensing 803
2.3 The Dual-Wave Correction Method 803
2.4 Calculation Process 804
3 Numerical Simulation 805
3.1 Data Generation 805
3.2 Simulation Results 806
4 Experimental Verification 807
4.1 Experimental Procedures 807
4.2 Results and Discussion 808
5 Conclusion 809
References 809
The Use of a Magnetic Probe Coupler to Aid the Reliability of Manual Ultrasonic Testing (MUT) on Carbon Steel Components 810
Abstract 810
1 Introduction 810
2 The Prevalence of MUT in Industry 811
2.1 Magnetic Probe Coupler 812
2.2 Future Work 814
3 Conclusion 815
References 816
An Adaptive Impedance Matching Network for Ultrasonic De-icing 817
Abstract 817
1 Introduction 817
2 Experimental Setup 818
2.1 Impedance Measuring System 819
2.2 Adaptive Impedance Matching Network 819
3 Results 820
4 Conclusions 822
Acknowledgments 822
References 822
Practical Experiences to Know Making Acoustic Emission-Based SHM Successful 823
1 Introduction 823
2 Experiments 825
3 Methods 826
4 Results and Discussion 828
5 Summary and Conclusions 830
References 830
General Session 831
Structural Health Monitoring of Adhesively Bonded Skin-Stiffener Composite Joint Using Distributed Fibre Optic Sensor 832
Abstract 832
1 Introduction 832
2 Experimental Setup 833
3 Results and Discussions 835
4 Conclusion 838
References 839
Towards Video-Based System Identification and Finite Element Model Updating of Civil Structures and Infrastructures 840
Abstract 840
1 Introduction 840
1.1 The Rationale for Computer Vision-Based SHM 841
2 Materials and Methods 842
2.1 Phase-Based Motion Magnification (PBMM) 842
2.2 Finite Element Model Updating (FEMU) 843
3 Case Study #1: SHM of High Rise Buildings 845
4 Case Study #2: Bridge Monitoring 846
5 Conclusions 847
References 847
Monitoring of Hydraulic Structure: Problem and Approach 849
Abstract 849
1 Problem Statement 849
2 Structural Health Monitoring 851
3 Requirements for the SHM System 852
4 Data-Based Model 854
5 Long-Term Stability 855
6 Conclusion and Outlook 856
References 857
Evaluating the Usefulness of Audible Acoustics as a Damage Detection Method in Large Composite Structures 858
Abstract 858
1 Introduction 858
2 Experimental Set-Up 860
2.1 Material Specification 860
2.2 Acoustic Camera Set-Up 861
2.3 Strain Gauge Set-Up 862
3 Results 862
4 Conclusion 869
References 870
Low-Power Actuation Methods for Highly Nonlinear Solitary Wave Transducers Used to Assess Human Eyes 871
1 Introduction 871
2 Design and Development of the Transducer 873
2.1 Particle Size 873
2.2 L-Shape Container 873
2.3 Sensor Placement 875
2.4 Sensor Type 875
2.5 Solenoid Driver Selection 875
3 Testing Background and Results 876
4 Conclusion 879
References 880
Numerical and Experimental Study of Acoustic Emission Source Signal Reconstruction in Fibre-Reinforced Composite Panels 881
Abstract 881
1 Introduction 881
2 Mathematical Procedure 882
2.1 Dispersion Compensation 882
2.2 Waveform Similarity 883
3 Simulation Using 3D SEM 884
4 Experimental Procedure 885
5 Numerical and Experimental Results and Analysis 887
5.1 Simulation Results of GFRP Panel 887
5.2 Experiment on GFRP Panel 888
6 Conclusion 889
Acknowledgments 890
References 890
Damage Detection and Identification in Composites by Acoustic Emission, Ultrasonic Inspection and Computer Tomography 892
Abstract 892
1 Introduction 892
2 Sample Preparation 893
2.1 Samples with Impact 893
2.2 Samples with Porosity 893
3 Test Matrix 894
4 Experimental Results 895
4.1 Ultrasonic Inspection and CT Investigation 895
4.2 Acoustic Emission Monitoring 896
5 Conclusion 899
Acknowledgement 900
References 900
Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring 901
Abstract 901
1 Introduction 901
2 Methodology 902
2.1 Experimental Set-Up 902
2.2 Experimental Procedures 903
2.3 Data Processing 904
3 Results 905
4 Conclusions 908
Acknowledgements 908
References 908
Influence of Environmental Conditions and Damage on Closely Spaced Modes 911
1 Introduction 911
2 Theoretical Background 912
2.1 Bayesian Operational Modal Analysis 912
2.2 Uncertainty of the MAC and S2MAC 913
3 Application 914
3.1 Influence of Environmental Conditions on Natural Frequencies and Mode Shapes 915
3.2 Damage Detection 917
4 Conclusion 919
References 919
Thin Membrane with “Human Touch” Sensitivity: Body Pressure and Temperature Measurements with Optical Fiber Sensors 921
Abstract 921
1 Introduction 921
2 Design and Development of the Thin Membrane 922
2.1 Working Principles 922
2.2 Technological Development of the Thin Membrane 923
3 Calibration of the Thin Elastomeric Membrane 924
3.1 Set-Up 924
3.2 Calibration Results 925
4 Validation Tests 926
5 Conclusions 928
References 929
Enabling FO-Based HUMS Applications Through an Innovative Integration Technique: Application to a Rotor Blade Mockup 930
Abstract 930
1 Introduction 930
2 Smart-Veil Manufacturing 933
3 The Case Study: A Sensorized Helicopter Blade Mockup 936
3.1 Strain Measurement 936
3.2 Manufacturing 937
4 Calibration and Validation 939
5 Conclusions 940
Bibliography 941
An Integrated Fiber Optic Based SHM System for Structural Composite Components: Application to a Racing Motorbike Fork 942
Abstract 942
1 Introduction 942
2 Telescopic Up-Side Down Front Fork Design 943
3 Material and Methods 944
4 Structural Monitoring System Design 945
4.1 Finite Element Models 945
4.2 Fiber Bragg Grating Sensors 945
5 Production of the Fork Tubes 947
6 Validation and Load Tests 948
6.1 Motostudent Safety Checks 948
6.2 Stiffness Comparison 948
6.3 Bending Test Different Azimuth (Sensor Location) 949
7 Conclusion 951
References 951
Estimation of Local Failure in Large Tensegrity Structures via Substructuring Using Interacting Particle-Ensemble Kalman Filter 952
1 Introduction 952
2 System Model 954
3 Substructuring Approach 954
4 Output Injection Approach 956
5 Numerical Experiment 958
6 Conclusion 959
References 960
Spherical Inclusions Based Defect Modes in a Phononic Crystal for Piezoelectric Energy Harvesting 961
Abstract 961
1 Introduction 961
2 Simulation Methods 962
2.1 Band Structure Analysis 963
2.2 Transmission Analysis 964
2.3 Energy Harvester Voltage Response Analysis 965
3 Results and Discussion 966
3.1 Perfect PnC Band Structure and Transmission Analysis 966
3.2 Defect PnC Analysis 967
3.3 Energy Harvester Performance Analysis 968
4 Conclusion 970
References 970
Low Flow Rate Measurement and Leak Detection for Health Monitoring of Water Equipment 972
Abstract 972
1 Introduction 972
2 Materials and Methods 973
2.1 Flow Meter Geometry 973
2.2 Simulation 973
2.3 Sensor Synthesis 974
2.4 Testing 975
3 Results and Discussion 976
3.1 Factorial Analysis 976
3.2 Sensor Performance 976
3.3 Pressure-Drop 977
4 Conclusion 977
Acknowledgements 978
References 978
Frequency Domain System Identification of Error–in–Variables Systems for Vibration–Based Monitoring 981
1 Introduction 981
2 Frequency Domain Identification of AR+Noise Models in the Frisch Scheme 982
2.1 Problem Statement 982
2.2 A Frequency Domain Setup in the Frisch Scheme 983
3 Model Order Estimation 985
4 Experimental Validation 986
4.1 Methods 987
4.2 Results 987
5 Conclusions 989
References 990
Real-Time Remote Monitoring of Steam Turbine Blades Based on High Cycle Fatigue Module and Cloud Computing 991
Abstract 991
1 Introduction 991
2 FEM Stress Limit Calculation 992
3 HCF Analysis Method 993
4 Remote Monitoring and Cloud Computing 995
5 Conclusion 997
Acknowledgement 998
References 998
Numerical Modeling of a Pyroshock Test Plate for Qualification of Space Equipment 999
Abstract 999
1 Introduction 999
2 Methodology 1002
3 Results 1005
4 Conclusions 1007
References 1008
A Novel Smart Sensor Node with Embedded Signal Processing Functionalities Addressing Vibration–Based Monitoring 1009
1 Introduction 1010
2 Output–Only SysId Models for Vibration Analysis 1010
3 Sensor Node Description 1011
4 Experimental Validation 1013
4.1 Materials and Methods 1013
4.2 Results 1014
5 Conclusions 1017
References 1017
Collective Mobile 3D Printing: An Active Sensing Approach for Improved Autonomy 1018
1 Introduction 1018
2 Problem Formulation 1020
3 Shape Reconstruction 1021
4 Simulation Results 1022
5 Conclusions 1023
References 1023
Inferring the Size of Stochastic Systems from Partial Measurements 1025
1 Introduction 1025
2 Theory 1026
3 Numerics 1028
4 Conclusions 1030
References 1031
Wire Break Detection in Bridge Tendons Using Low-Frequency Acoustic Emissions 1033
1 Introduction 1033
2 Experiments 1034
2.1 Wire Break Experiments at Demolished Bridge Girders 1035
2.2 In-situ Wire Break Recordings on Real Bridge Construction 1035
2.3 Operational Recordings in Hagen, Germany 1036
3 Methodology 1037
3.1 Extraction of Impulse-Like Signals 1037
3.2 Time-Frequency Domain Features 1038
3.3 Wire Break Detection Using Support Vector Machines 1039
4 Results 1039
4.1 Comparison with Amplitude Based Hitdetection 1040
5 Conclusion 1040
References 1041
App4SHM – Smartphone Application for Structural Health Monitoring 1043
Abstract 1043
1 Introduction 1044
2 Software Architecture and Details 1045
2.1 Step 1 – Structure Identification 1045
2.2 Step 2 – Data Acquisition 1046
2.3 Step 3 – Feature Extraction 1046
2.4 Step 4 – Damage Detection 1047
3 Case Study: Twin Bridges Over the Itacaiúnas River 1047
4 Conclusions 1051
References 1052
Structural Damage Detection of Offshore Structures Using Kalman Filtering 1053
Abstract 1053
1 Introduction 1053
2 Mathematical Formulation and Kalman Filter 1054
2.1 State Space Formulation for Linear Systems 1055
2.2 Linear Approximation of Nonlinear Systems 1055
2.3 Augmented Kalman Filter 1056
3 Damage Detection Framework 1056
4 Numerical Example 1057
4.1 FE Model of the 2D Steel Jacket Structure 1058
4.2 Sensors, and Measurement Noise and External Loading 1059
4.3 Definition of Covariance Matrices 1059
5 Results 1060
6 Conclusions 1062
Acknowledgments 1062
References 1062
Experimental Fatigue Evaluation of a Gusset-Less Truss Connection 1064
Abstract 1064
1 Introduction 1064
2 Project Overview 1065
3 Experimental Test Setup 1066
4 Instrumentation 1068
5 Test Monitoring 1069
6 Finite Element Modeling 1070
7 Results 1071
References 1073
Author Index 1074