Structural Health Monitoring and Smart Sensing in Construction
- 1st Edition - March 1, 2027
- Latest edition
- Authors: Shun Weng, Hongping Zhu, Fei Gao
- Language: English
Structural Health Monitoring and Smart Sensing in Construction systematically integrates fundamental theories of structural health monitoring (SHM) with cutting-edge intell… Read more
Description
Description
Structural Health Monitoring and Smart Sensing in Construction systematically integrates fundamental theories of structural health monitoring (SHM) with cutting-edge intelligent sensing technologies. Topics range from monitoring system overviews, machine vision, and advanced piezoelectric, piezoresistive, thin-film, and fiber optic sensing, to nondestructive methods such as acoustic emission and electromagnetic testing. The book also examines data preprocessing, statistical analysis, and AI-based applications, alongside practical aspects like modal identification, model updating, and damage assessment. Through abundant case studies and exercises, the book emphasizes the integration of theory and practice, aiming to equip readers with the skills to tackle complex engineering challenges
Key features
Key features
- Systematically incorporates six emerging monitoring technologies - including machine vision, intelligent piezoelectric/piezoresistive sensing, flexible thin-film sensing, and fiber optic sensing - providing readers with a one-stop solution to master intelligent sensing tools
- Introducing a unique end-to-end framework of data preprocessing/statistical analysis/machine learning modeling/engineering decision-making
- By bridging the technical gap between structural engineering and intelligent sensing, the book constructs a unified knowledge system
- Each chapter includes real-world bridge and building case studies (e.g., crack detection in steel structures using acoustic emission) and targeted exercises, significantly enhancing the reader’s ability to tackle infrastructure maintenance challenges and shortening the learning curve from classroom theory to on-site application
Readership
Readership
Senior undergraduate and graduate students majoring in civil engineering, intelligent construction, and related disciplines in higher education
Table of contents
Table of contents
1. Overview of Structural Health Monitoring
1.1 Chapter Introduction
1.2 Background of SHM
1.3 Significance of SHM
1.4 Research Topics in SHM
1.5 Current Technical Challenges and Development Trends
1.6 Questions and Exercises
2. Structural Health Monitoring Systems
2.1 Chapter Introduction
2.2 Design of SHM System
2.3 Implementation of SHM System
2.4 Sensor Selection
2.5 Typical SHM System Cases
2.6 Questions and Exercises
3. Machine Vision-Based SHM Technology
3.1 Chapter Introduction
3.2 Machine Vision Measurement System
3.3 Fundamentals of Visual Measurement
3.4 Displacement and Modal Measurement
3.5 Dynamic Vehicle Load Detection
3.6 Questions and Exercises
4. Principles and Methods of Intelligent Piezoelectric Sensing
4.1 Chapter Introduction
4.2 Piezoelectric Effect and Mechanism
4.3 Piezoelectric Materials
4.4 Equivalent and Measurement Circuits of Piezoelectric Components
4.5 Piezoelectric Sensors
4.6 SHM Methods Based on Smart Piezoelectric Materials
4.7 Microscale Crack Detection Using Piezoelectric Impedance Techniques and Devices
4.8 Questions and Exercises
5. Principles and Methods of Intelligent Flexible Piezoresistive Sensing
5.1 Chapter Introduction
5.2 Metal Piezoresistive Sensors（中文版本是介绍普遍的金属应变片）
5.3 Flexible Piezoresistive Sensing Materials （不局限于应变，也可以测裂纹、压力等）
5.4 Sensing Mechanisms of Novel Flexible Piezoresistive Sensors
5.5 Microstructure Fabrication of Flexible Piezoresistive Sensors
5.6 Applications of Novel Flexible Piezoresistive Sensors
5.7 Case Studies
5.8 Questions and Exercises
6. Principles and Methods of Flexible Thin-Film Sensing
6.1 Chapter Introduction
6.2 Thin-Film Antenna Sensors
6.3 Thin-Film Capacitive Sensors
6.4 Biosensors
6.5 Biomimetic Film Sensors
6.6 Questions and Exercises
7. Principles and Methods of Fiber Optic Sensing
7.1 Chapter Introduction
7.2 Fiber Optic Sensing Technology
7.3 Fiber Bragg Grating Sensors
7.4 Applications of FBG Sensors
7.5 Distributed Optical Fiber Sensors (DOFS)
7.6 Applications of DOFS
7.7 Questions and Exercises
8. Acoustic Emission Nondestructive Testing Techniques
8.1 Chapter Introduction
8.2 Overview of Acoustic Emission
8.3 Fundamentals of Acoustic Emission
8.4 Acoustic Emission Testing Systems
8.5 Signal Analysis in AE Testing
8.6 Applications of AE Technology
8.7 Questions and Exercises
9. Electromagnetic Nondestructive Testing Techniques
9.1 Chapter Introduction
9.2 Overview of Electromagnetic Testing
9.3 Fundamentals of Electromagnetic Testing
9.4 Eddy Current Testing
9.5 Magnetic Particle Testing
9.6 Magnetic Flux Leakage Testing
9.7 Applications of Electromagnetic Testing
9.8 Questions and Exercises
10. Preprocessing of Big Data in SHM
10.1 Chapter Introduction
10.2 Noise Filtering in Data
10.3 Data Anomaly Detection
10.4 Missing Data Imputation
10.5 Questions and Exercises
11. Statistical Analysis of SHM Data
11.1 Chapter Introduction
11.2 Basic Statistical Analysis
11.3 Probability Density Function Estimation
11.4 Extreme Value Analysis
11.5 Correlation Analysis
11.6 Regression Analysis
11.7 Questions and Exercises
12. Machine Learning Algorithms for SHM
12.1 Chapter Introduction
12.2 Clustering Methods
12.3 Tree-Based Models
12.4 Support Vector Machines
12.5 Neural Networks
12.6 Deep Learning
12.7 Questions and Exercises
13. Structural Modal Parameter Identification
13.1 Chapter Introduction
13.2 Overview
13.3 Fundamentals of Modal Theory
13.4 Frequency Response Analysis of SDOF Systems
13.5 Frequency Response Analysis of MDOF Systems
13.6 Modal Identification Methods
13.7 Time-Domain Methods for Time-Varying Modal Identification
13.8 Questions and Exercises
14. Finite Element Model Updating of Structures
14.1 Chapter Introduction
14.2 Fundamental Theory of FE Model Updating
14.3 Methods of FE Model Updating
14.4 Frequency-Domain Substructuring-Based Model Updating
14.5 Time-Domain Sensitivity-Based Model Updating
14.6 Questions and Exercises
15. Structural Damage Identification
15.1 Chapter Introduction
15.2 Classification of Damage Identification Methods
15.3 Model-Based Damage Identification
15.4 Data-Driven Damage Identification
15.5 Optimization Algorithms-Based Damage Identification
15.6 Questions and Exercises
16. Structural Condition Assessment and Early Warning
16.1 Chapter Introduction
16.2 Overview of Bridge Condition Assessment
16.3 Analytic Hierarchy Process
16.4 Reliability-Based Assessment
16.5 Questions and Exercises References
1.1 Chapter Introduction
1.2 Background of SHM
1.3 Significance of SHM
1.4 Research Topics in SHM
1.5 Current Technical Challenges and Development Trends
1.6 Questions and Exercises
2. Structural Health Monitoring Systems
2.1 Chapter Introduction
2.2 Design of SHM System
2.3 Implementation of SHM System
2.4 Sensor Selection
2.5 Typical SHM System Cases
2.6 Questions and Exercises
3. Machine Vision-Based SHM Technology
3.1 Chapter Introduction
3.2 Machine Vision Measurement System
3.3 Fundamentals of Visual Measurement
3.4 Displacement and Modal Measurement
3.5 Dynamic Vehicle Load Detection
3.6 Questions and Exercises
4. Principles and Methods of Intelligent Piezoelectric Sensing
4.1 Chapter Introduction
4.2 Piezoelectric Effect and Mechanism
4.3 Piezoelectric Materials
4.4 Equivalent and Measurement Circuits of Piezoelectric Components
4.5 Piezoelectric Sensors
4.6 SHM Methods Based on Smart Piezoelectric Materials
4.7 Microscale Crack Detection Using Piezoelectric Impedance Techniques and Devices
4.8 Questions and Exercises
5. Principles and Methods of Intelligent Flexible Piezoresistive Sensing
5.1 Chapter Introduction
5.2 Metal Piezoresistive Sensors（中文版本是介绍普遍的金属应变片）
5.3 Flexible Piezoresistive Sensing Materials （不局限于应变，也可以测裂纹、压力等）
5.4 Sensing Mechanisms of Novel Flexible Piezoresistive Sensors
5.5 Microstructure Fabrication of Flexible Piezoresistive Sensors
5.6 Applications of Novel Flexible Piezoresistive Sensors
5.7 Case Studies
5.8 Questions and Exercises
6. Principles and Methods of Flexible Thin-Film Sensing
6.1 Chapter Introduction
6.2 Thin-Film Antenna Sensors
6.3 Thin-Film Capacitive Sensors
6.4 Biosensors
6.5 Biomimetic Film Sensors
6.6 Questions and Exercises
7. Principles and Methods of Fiber Optic Sensing
7.1 Chapter Introduction
7.2 Fiber Optic Sensing Technology
7.3 Fiber Bragg Grating Sensors
7.4 Applications of FBG Sensors
7.5 Distributed Optical Fiber Sensors (DOFS)
7.6 Applications of DOFS
7.7 Questions and Exercises
8. Acoustic Emission Nondestructive Testing Techniques
8.1 Chapter Introduction
8.2 Overview of Acoustic Emission
8.3 Fundamentals of Acoustic Emission
8.4 Acoustic Emission Testing Systems
8.5 Signal Analysis in AE Testing
8.6 Applications of AE Technology
8.7 Questions and Exercises
9. Electromagnetic Nondestructive Testing Techniques
9.1 Chapter Introduction
9.2 Overview of Electromagnetic Testing
9.3 Fundamentals of Electromagnetic Testing
9.4 Eddy Current Testing
9.5 Magnetic Particle Testing
9.6 Magnetic Flux Leakage Testing
9.7 Applications of Electromagnetic Testing
9.8 Questions and Exercises
10. Preprocessing of Big Data in SHM
10.1 Chapter Introduction
10.2 Noise Filtering in Data
10.3 Data Anomaly Detection
10.4 Missing Data Imputation
10.5 Questions and Exercises
11. Statistical Analysis of SHM Data
11.1 Chapter Introduction
11.2 Basic Statistical Analysis
11.3 Probability Density Function Estimation
11.4 Extreme Value Analysis
11.5 Correlation Analysis
11.6 Regression Analysis
11.7 Questions and Exercises
12. Machine Learning Algorithms for SHM
12.1 Chapter Introduction
12.2 Clustering Methods
12.3 Tree-Based Models
12.4 Support Vector Machines
12.5 Neural Networks
12.6 Deep Learning
12.7 Questions and Exercises
13. Structural Modal Parameter Identification
13.1 Chapter Introduction
13.2 Overview
13.3 Fundamentals of Modal Theory
13.4 Frequency Response Analysis of SDOF Systems
13.5 Frequency Response Analysis of MDOF Systems
13.6 Modal Identification Methods
13.7 Time-Domain Methods for Time-Varying Modal Identification
13.8 Questions and Exercises
14. Finite Element Model Updating of Structures
14.1 Chapter Introduction
14.2 Fundamental Theory of FE Model Updating
14.3 Methods of FE Model Updating
14.4 Frequency-Domain Substructuring-Based Model Updating
14.5 Time-Domain Sensitivity-Based Model Updating
14.6 Questions and Exercises
15. Structural Damage Identification
15.1 Chapter Introduction
15.2 Classification of Damage Identification Methods
15.3 Model-Based Damage Identification
15.4 Data-Driven Damage Identification
15.5 Optimization Algorithms-Based Damage Identification
15.6 Questions and Exercises
16. Structural Condition Assessment and Early Warning
16.1 Chapter Introduction
16.2 Overview of Bridge Condition Assessment
16.3 Analytic Hierarchy Process
16.4 Reliability-Based Assessment
16.5 Questions and Exercises References
Product details
Product details
- Edition: 1
- Latest edition
- Published: March 1, 2027
- Language: English
About the authors
About the authors
SW
Shun Weng
Shun Weng is Professor at Huazhong University of Science and Technology. Her research focuses on structural health monitoring, smart sensing and damage identification for buildings, bridges and metros. She has led National Key R&D Program projects, authored three monographs and 80+ SCI papers
Affiliations and expertise
Huazhong University of Science and Technology, ChinaHZ
Hongping Zhu
Hongping Zhu is a Professor at Huazhong University of Science and Technology. His work centres on vibration control and health assessment of civil structures. He has directed 973 and NSFC key projects, published three monographs and 200+ SCI papers, and earned one National Technological Invention Second Prize and one National Progress Second Prize
Affiliations and expertise
Huazhong University of Science and Technology, ChinaFG
Fei Gao
Fei Gao is Professor at Huazhong University of Science and Technology. His interests are steel and composite structures, structural safety diagnosis and health monitoring. He has led National Key R&D tasks and NSFC projects, published 60+ papers, and received two Hubei Provincial First Prizes
Affiliations and expertise
Huazhong University of Science and Technology, China