Structural Health Monitoring amp Damage Detection Volume 7 Proceedings of the 35th IMAC A Conference and Exposition on Structural Dynamics 2017 1st Edition by Christopher Niezreck 3319541099 9783319541099

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ISBN-10 :  3319541099 

ISBN-13 :  9783319541099

Author:  Christopher Niezreck 

Structural Health Monitoring & Damage Detection, Volume 7: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the seventh volume of ten 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 & Damage Detection, including papers on: Structural Health Monitoring Damage Detection System Identification Active Controls

Structural Health Monitoring amp Damage Detection Volume 7 Proceedings of the 35th IMAC A Conference and Exposition on Structural Dynamics 2017 1st Table of contents:

1 Exploiting Spatial Sparsity in Vibration-Based Damage Detection
1.1 Introduction
1.2 Method of Approach
1.3 LASSO Regularization
1.4 Simulations and Verification
1.5 Effects of Measurement Noise
1.6 Conclusion
References
2 Multi-Source Sensing and Analysis for Machine-Array Condition Monitoring
2.1 Introduction
2.2 Background
2.3 Experimental Setup and Procedures
2.4 Analysis Approaches
2.5 Blind Source Separation
2.6 Linear Least Squares
2.7 Brute-Force Optimization
2.8 Machine Learning Approaches
2.9 Evaluation
2.10 Further Research
2.11 Conclusion
References
3 Wavelet Transform-Based Damage Detection in Reinforced Concrete Using an Air-Coupled Impact-Echo M
References
4 Damage Detection Based on Strain Transmissibility for Beam Structure by Using Distributed Fiber Op
4.1 Introduction
4.2 Transmissibility Functions Algorithm
4.3 Strain Transmissibility Function
4.4 Simulation Validation
4.4.1 Simulation Model
4.4.2 Simulation Results
4.5 Experiment Validation
4.5.1 Brief Introduction of ODiSI-B
4.5.2 Experimental Setup
4.5.3 Experimental Result
4.6 Conclusion
4.7 Funding
References
5 Modal Parameters Estimation of an Offshore Wind Turbine Using Measured Acceleration Signals from t
5.1 Introduction
5.2 Data Acquisition
5.3 Operational Modal Analysis and Modal Parameters Tracking Approach
5.4 Results and Discussions
5.4.1 Low Frequency-Band Analysis
5.4.2 High Frequency-Band Analysis
5.5 Conclusions
References
6 Structural Damage Detection in Real Time: Implementation of 1D Convolutional Neural Networks for S
6.1 Introduction
6.2 1D and 2D CNNs
6.3 The Proposed CNN-Based Algorithm
6.4 Experimental Demonstration
6.5 Discussions
6.6 Conclusions
References
7 Monitoring the Health of a Cantilever Beam Using Nonlinear Modal Tracking
Nomenclature
7.1 Introduction
7.2 Background
7.3 Theoretical Model Development
7.4 System Identification
7.5 Experimental Procedure
7.6 Results
7.7 Discussion
7.8 Conclusion
References
8 Using Modal Parameters for Structural Health Monitoring
8.1 Introduction
8.2 Review of Modal Assurance Criterion (MAC)
8.3 Review of Shape Difference Indicator (SDI)
8.4 Identifying Cap Screw Torque
8.5 SDI and MAC with Modal Frequency Shapes
8.6 Increased SDI Sensitivity
8.7 Modal Frequency Shapes with Increased Sensitivity
8.8 Modal Damping Shapes with Increased Sensitivity
8.9 Fault Correlation Tools (FaCTs™)
8.10 Conclusion
References
9 Current Challenges with BIGDATA Analytics in Structural Health Monitoring
9.1 Introduction
9.2 Bigdata Characteristics
9.2.1 Variety
9.2.2 Volume
9.2.3 Velocity
9.2.4 Complexity
9.3 Bigdata Processing
9.4 Promises
9.5 Conclusion
References
10 Detection of Cracks in Beams Using Treed Gaussian Processes
10.1 Introduction
10.2 The Previous Approach
10.2.1 Gaussian Processes
10.2.2 Previous Method: Crack Detection
10.3 Treed Gaussian Processes
10.3.1 Regression Trees
10.4 The Current Data and Results
10.4.1 Current Data
10.4.2 Results
10.5 Conclusions

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Tags: Structural Health, Monitoring, Damage Detection, Proceedings, Structural Dynamics, Christopher Niezreck