Sensor Technologies for Civil Infrastructures

Volume 1: Sensing Hardware and Data Collection Methods for Performance Assessment

2nd Edition - July 19, 2022

Editors: Jerome P. Lynch, Hoon Sohn, Ming L. Wang

Paperback ISBN:

9 7 8 - 0 - 0 8 - 1 0 2 6 9 6 - 0

eBook ISBN:

9 7 8 - 0 - 0 8 - 1 0 2 6 9 7 - 7

Sensor Technologies for Civil Infrastructure, Volume 1: Sensing Hardware and Data Collection Methods for Performance Assessment, Second Edition, provides an overview of sensor… Read more

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Sensor Technologies for Civil Infrastructure, Volume 1: Sensing Hardware and Data Collection Methods for Performance Assessment, Second Edition, provides an overview of sensor hardware and its use in data collection. The first chapters provide an introduction to sensing for structural performance assessment and health monitoring, and an overview of commonly used sensors and their data acquisition systems. Further chapters address different types of sensor including piezoelectric transducers, fiber optic sensors, acoustic emission sensors, and electromagnetic sensors, and the use of these sensors for assessing and monitoring civil infrastructures. The new edition now includes chapters on machine learning methods and reliability analysis for structural health monitoring. All chapters have been revised to include the latest advances in materials (such as piezoelectric and mechanoluminescent materials), technologies (such as LIDAR), and applications.

Cover image
Title page
Table of Contents
Copyright
List of contributors
Part One. Introduction and sensor technologies
1. Introduction to sensors and sensing systems for civil infrastructure monitoring and asset management
1.1. Introduction to infrastructure sensing
1.2. Description of the book organization
1.3. Summary
2. Sensor data acquisition systems and architectures
2.1. Scope of this chapter
2.2. Concepts in signals and digital sampling
2.3. Analog-to-digital conversion
2.4. Digital-to-analog conversion
2.5. Data acquisition systems
2.6. Optical sensing DAQ system
2.7. Wireless data acquisition
2.8. Summary and future trends
3. Commonly used sensors for civil infrastructures and their associated algorithms
3.1. Introduction
3.2. Brief review of commonly used sensing technologies
3.3. Associated algorithms
3.4. Examples of continuous monitoring systems
3.5. Conclusions and future trends
4. Piezoelectric transducers
4.1. Introduction
4.2. Principle of piezoelectricity
4.3. Piezoelectric materials and the fabrication of piezoelectric transducers
4.4. Piezoelectric transducers for SHM applications
4.5. Bonding effects
4.6. Limitations of piezoelectric transducers
4.7. SHM techniques using piezoelectric transducers
4.8. Applications of piezoelectric transducer–based SHM
4.9. Future trends
4.10. Chapter summary
5. Optical fiber sensors
5.1. Introduction
5.2. Properties of optical fibers
5.3. Common optical fiber sensors
5.4. Future trends
5.5. Sources for further advice
5.6. Conclusions
6. Acoustic emission sensors for assessing and monitoring civil infrastructures
6.1. Introduction
6.2. Fundamentals of acoustic emission technique
6.3. Interpretation of AE signals
6.4. AE localization methods
6.5. Severity assessment
6.6. AE equipment technology
6.7. Field applications and structural health monitoring using AE
6.8. Future challenges
6.9. Conclusion
7. Radar technology: radio frequency, interferometric, millimeter wave and terahertz sensors for assessing and monitoring civil infrastructures
7.1. Introduction
7.2. Radar and millimeter wave sensors
7.3. Terahertz sensors
7.4. Conclusions and future trends
8. Electromagnetic sensors for assessing and monitoring civil infrastructures
8.1. Introduction to magnetics and magnetic materials
8.2. Introduction to magnetoelasticity
8.3. Magnetic sensory technologies
8.4. Role of microstructure in magnetization and magnetoelasticity
8.5. Magnetoelastic stress sensors for tension monitoring of steel cables
8.6. Temperature effects
8.7. Eddy current
8.8. Removable (portable) elastomagnetic stress sensor
8.9. Conclusion and future trends
9. Microelectromechanical systems for assessing and monitoring civil infrastructures
9.1. Introduction
9.2. Sensor materials and micromachining techniques
9.3. Sensor characteristics
9.4. MEMS sensors for SHM
9.5. Application examples
9.6. Durability of MEMS sensors for SHM
9.7. Current research directions of MEMS sensors for SHM
9.8. Further resources
10. Laser-based sensing for assessing and monitoring civil infrastructures
10.1. Laser-based sensing
Appendix
11. Vision-based sensing for assessing and monitoring civil infrastructures
11.1. Introduction
11.2. Vision-based measurement techniques for civil engineering applications
11.3. Important issues for vision-based measurement techniques
11.4. Applications for vision-based sensing techniques
11.5. Conclusions
12. Introduction to wireless sensor networks for monitoring applications: principles, design, and selection
12.1. Introduction and motivation
12.2. Overview of wireless networks
12.3. Hardware design and selection
12.4. Wireless sensor network software
12.5. Summary and outlook
13. Vibration energy harvesters for sensing applications
13.1. Introduction
13.2. Harvester dynamic modeling
13.3. Power availability and the optimal harvesting admittance
13.4. Power extraction circuits
13.5. Recent advancements and future directions
Part Two. Sensor data management
14. Data management technologies for infrastructure monitoring
14.1. Introduction
14.2. An information modeling framework
14.3. A scalable data management framework
14.4. A cyberinfrastructure platform
14.5. Utilization of the cloud-based cyberinfrastructure platform
14.6. Summary and discussion
15. Sensor data analysis, reduction, and fusion for assessing and monitoring civil infrastructures
15.1. Introduction
15.2. Bayesian inference and monitoring data analysis
15.3. Data reduction
15.4. Data fusion
15.5. Further trends
15.6. Sources of further information and advice
16. Analytical techniques for damage detection and localization for assessing and monitoring civil infrastructures
16.1. Introduction
16.2. Linear time invariant systems
16.3. Modal form
16.4. Relation between the complex and the normal mode models
16.5. Damage detection
16.6. Damage localization
16.7. Future trends
16.8. Sources of further information and advice
17. Output-only modal identification and structural damage detection using time–frequency and wavelet techniques for assessing and monitoring civil infrastructures
17.1. Introduction
17.2. Time–frequency methods: STFT, EMD, and HT
17.3. Modal identification of linear time invariant and linear time variant systems using EMD/HT and STFT
17.4. Modal identification of LTI and LTV systems using wavelets
17.5. Experimental and numerical validation of modal identification of LTI and LTV systems using STFT, EMD, wavelets, and HT
17.6. Conclusion
18. Deep learning and data analytics for assessing seismic performance of civil infrastructures
18.1. Introduction
18.2. Stacked long short-term memory network
18.3. Physics-guided convolutional neural network
18.4. Physics-informed multi-LSTM networks
18.5. Application examples
18.6. Conclusions and future trends
19. Prognosis and life-cycle assessment based on SHM information
19.1. Introduction
19.2. Statistical and probabilistic aspects for efficient prognosis
19.3. Life-cycle analysis using monitoring data
19.4. Multiobjective optimum monitoring planning
19.5. Conclusions
Abbreviations
20. Decision-making in SHM systems for asset management
20.1. Introduction
20.2. Bayesian inference and dynamic systems
20.3. Optimal decision-making
20.4. Value of information
20.5. Examples
20.6. Discussion and conclusions
Index