| Description |
1 online resource (611 p.) |
| Series |
Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems Ser |
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Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems Ser
|
| Contents |
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Chapter 1 Wavelet-Based Damage-Sensitive Features Extraction -- 1.1 Introduction -- 1.2 Data Preprocessing -- 1.2.1 Feature Detection and Extraction -- 1.2.2 Statistical Model Formulation -- 1.2.3 Scale Selection -- 1.2.4 Feature Damage Index Identification Based Wavelet -- 1.3 Numerical Simulation and Results: Discussion -- 1.4 Conclusions -- References |
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Chapter 2 Deep Learning for Automated Damage Detection: A Novel Algorithm in CNN Family for Faster and Accurate Damage Identification -- 2.1 Introduction -- 2.2 Deep Learning Based Approaches for Image Classification and Object Detection -- 2.2.1 Deep Learning for Image Classification -- 2.3 Methodology -- 2.4 Conclusions -- Acknowledgements -- References -- Chapter 3 Seismic Protection of Cultural Relics Using Three-Dimensional Base-Isolation System -- 3.1 Introduction -- 3.2 Input Ground Motions -- 3.3 Finite Element Models -- 3.4 Response History Analyses -- 3.4.1 Overturn -- 3.4.2 Sliding |
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3.5 Conclusions -- Acknowledgment -- References -- Chapter 4 Combined Actuator-Shake Table Test with Optimized Input Energy -- 4.1 Introduction -- 4.2 Equations of Motion of the Experimental SDF Model -- 4.3 The Testing Power -- 4.4 Procedures for Dividing the Ground Motion between the Shake Table and Actuators -- 4.4.1 Dividing in Time Domain -- 4.4.2 Dividing in Frequency Domain -- 4.4.3 Dynamic Optimization -- 4.5 Extending to Multi Degree of Freedom (MDF) Models -- 4.6 Numerical Calculations -- 4.7 Conclusions -- References |
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Chapter 5 Design Spectra for Structures Subjected to Passing Underground Trains -- 5.1 Introduction -- 5.2 Specifications of the Trains -- 5.2.1 The Selected Trains -- 5.2.2 The Suspension System -- 5.2.2.1 Dynamical Model of the Secondary Suspension System -- 5.2.2.2 Dynamical Model of the Main Suspension System -- 5.3 The Loading Pattern -- 5.4 The 3D Model of the Soil-Tunnel System -- 5.4.1 Modeling of the Components -- 5.4.2 The Output -- 5.5 The Calculated Spectra -- 5.5.1 Introduction -- 5.5.2 The Numerical Results -- 5.6 Conclusions -- References |
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Chapter 6 Frequency-Domain Fast Maximum Likelihood Estimation of Complex Modes -- 6.1 Introduction -- 6.2 Problem Formulation -- 6.2.1 The Deterministic Model -- 6.2.2 The Probabilistic Model -- 6.3 ML Estimation -- 6.4 EM Algorithm -- 6.5 Field Test -- 6.6 Conclusion -- Acknowledgements -- References -- Chapter 7 A Full Version of Vision-Based Structural Identification -- 7.1 Introduction -- 7.2 Methodology -- 7.2.1 Vision-Based Structural Input Estimation -- 7.2.2 Vision-Based Structural Output Estimation -- 7.2.3 Extract UIL from Structural Input and Output -- 7.3 Experimental Verification |
| Notes |
Description based upon print version of record |
| Form |
Electronic book
|
| Author |
Wu, Zhishen
|
|
Noori, Mohammad
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Li, Yong
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| ISBN |
9781000178692 |
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1000178692 |
|
