Department of Civil Engineering National Taiwan University

1. Department of Civil Engineering National Taiwan University JOINT NCREE/JRC WORKSHOP INTERNATIONAL COLLABORATION ON EARTHQUAKE DISASTER MITIGATION RESEARCH Methodologies, Facilities, Projects and Networking STRUCTURAL HEALTH MONITORING AND CONTROL RESEARCH IN NCREE Chin-Hsiung Loh Department of Civil Engineering, National Taiwan University e-mail: lohc0220@ccms.ntu.edu.tw November 17-19, 2003 NCREE, Taiwan

2. Department of Civil Engineering National Taiwan University Levels of Health Monitoring  Level 1:Detect the existence of damage;  Level 2:Detect and locate damage;  Level 3:Detect, locate and quantify damage;  Level 4:Estimate remaining service life (prognosis);  Level 5:Self Diagnostics;  Level 6:Self-Healing; INCREASING DEGREE OF COMPLEXITY, GREATER NEED FOR ANALYTICAL MODELS

3. Information/Diagnostics • Signal Processing • Intelligent Algorithms • Communication • Maintenance • Reliability / Safety • Performance • Lifecycle cost Intelligent Software Analysis & Test Data (Sensor system & Tests) Intelligent Structure Department of Civil Engineering National Taiwan University Performance-Assessment of Structures Using Innovative Technology Goal: Developing design-to-service damage prognosis solution with a structural health monitoring system

4. Input Signal System Output Signal Input/Output Output Only EMD+HHT Method Linear Time Invariant Model (off-line) Linear Time Variant System (on-line) Wavelet Analysis Nonlinear System Changing Spectrum Method Department of Civil Engineering National Taiwan University A critical assessment of identification method on time-invariant, time-varying & nonlinear system Modal-based / Signal-based Identification

5. Recursive Lease Square with Variable Forgetting Recursive Least Square with Constant Trace Identification on Time-Varying System Parametric Time-Frequency Method Wavelet Analysis Department of Civil Engineering National Taiwan University Discrete Time Domain ARX Model • Identification of Nonlinear Dynamic System Using Wavelets c(t) or k(t) : The time-dependent c(t) or k(t) of the structural system can be expressed as a series expansion of wavelets.

6. Linear Parameterized Method (Identify Restoring Force) Parametric Identification Extended Kalman Filter Method Neural Network Nonlinear System Wiener Series Representation Non-parametric Identification Non-parametric Identification Technique Detecting & Quantifying Nonlinearity Frequency Domain Analysis Wavelet Analysis Harmonic Probing Method Frequency Response Function (Both Amplitude & Phase) Department of Civil Engineering National Taiwan University

7. Department of Civil Engineering National Taiwan University Dense Monitoring of Structural Integrity • Detailed response • Detailed System Identification ☛ Parameters can be estimated on-line or off-line, ☛ Model can be black-box (no direct physical relevence of parameters, ☛ Model can be white-box (directly estimate physically relevent parameters, • Detailed damage estimation ☛ Localized damage assessment requires a cheap, dense sensor array,

8. In Relating to Damage Measure 1. Changes in resonance frequencies and modal damping, 2. Changes in mode shape (or curvature): • 3. Change in flexibility, 4. Change in stiffness, 5. Change in model strain energy Department of Civil Engineering National Taiwan University

9. Department of Civil Engineering National Taiwan University Damage Assessment: A Data Driven Modeling Problem • Reasons • “Noise” is presented in the sensor measurements and • simulation outputs, • 2. External inputs may be best modeled stochastically, • 3. The structure itself may be modeled stochastically, • 4. Practical constraints may force the model to over-simplify some • aspects of the problem, giving rise to prediction errors, Then: Measures of success, estimates of accuracy, etc. are likely to be probabilistic (e.g. expected error, probability of damage, expected lifetime, …)

10. Integrated bridge management systems Health monitoring module Bridge assessment module Continuous monitoring Event Monitoring Periodic monitoring and Field inspection Integrated sensors Database of bridge response from on-structure data acquisition systems Data analysis & interpretation System Identification Damage assessment Life-time serviceability evaluation Knowledge base for decision making (operation, maintenance, design & construction) Department of Civil Engineering National Taiwan University

11. Structural Health • Monitoring Usage Monitoring Damage Prognosis Loading & Operating Identification/measurement 1. Instrumentation 2. Data Management System Assessment Model Modeling & Simulation Predictive Model Future Loading Estimation Predictive Loading Model Department of Civil Engineering National Taiwan University

12.     Department of Civil Engineering National Taiwan University Example: Vertical Array Data Surface Research topics:  Characterization of individual site  Inversion of ground motion data Geology System (ARMAX Model) • Predict ground motion (Using ARMAX model derived from previous event)

13. Department of Civil Engineering National Taiwan University Future Works • 1. Check and develop the efficiency of available monitoring • techniques together with Information produced by simulation • (including risk and weak-point oriented assessment methods), • 2. Develop damage characterization strategy (including stochastic state-space realization, extraction of flexibility proportional matrices from the realization results, localization and quantification of the damage), • 3.Develop criteria for evaluation and decision of planning, evaluation and iterative optimization of structural monitoring • 4. Develop knowledge based system (modules of the expert system) for data acquisition and assessment in monitoring structures,

14. Department of Civil Engineering National Taiwan University Benchmark Model Develop Benchmark Model for System Identification: 1. Soft-floor: the beam is pin connected with the floor, (strong column /weak beam) 2. Stiff-floor: The beam and the floor are rigidly connected,

15. Department of Civil Engineering National Taiwan University Verification with Numerical Simulation (OpenSees, ABACUS etc.) Modal-based / Signal-based Identification Damage Evaluation

16. Department of Civil Engineering National Taiwan University Case 1: Rigid Floor

17. Department of Civil Engineering National Taiwan University Case 1: Rigid Floor

18. Department of Civil Engineering National Taiwan University Structural responses under El Centro 700 gal (Weak axis). Case 1: Rigid Floor

19. Department of Civil Engineering National Taiwan University Structural responses under El Centro 700 gal / Weak axis. Case 1: Rigid Floor

20. Department of Civil Engineering National Taiwan University Case 2: Weak Floor

21. Department of Civil Engineering National Taiwan University Case 2:Weak Floor

22. Department of Civil Engineering National Taiwan University Structural responses under El Centro 700 gal (Weak axis).

23. Department of Civil Engineering National Taiwan University Structural responses under El Centro 700 gal (Weak axis).

24. Satellite IP Telephone Users RadioCellular Structure Control CenterGateway Communications Fiber Optic Department of Civil Engineering National Taiwan University The way ahead of SHM 1. Appropriate level of instrumentation, 2. Novel sensors, 3. Communications 4. Data mining and performance diagnosis, 5. Interdisciplinary, collaborative research,

25. Structures Smart Structure Control Structures Actuation System Sensing System Neural Network System Intelligent Adaptive Structure Smart Adaptive Structure Department of Civil Engineering National Taiwan University Application of Innovative Technology for Seismic Hazard Mitigation Instrumentation / Sensing Actuation Physical System

26. Department of Civil Engineering National Taiwan University 3KN MR Damper A typical hysteretic loop of MR damper under different voltages

27. Input Layer Hidden Layer Two prior steps of Displacement Voltage Three prior steps of Displacement Force Output Layer Input Layer Twelve Neurons Predicted Force   Hidden Layer Output Layer One prior steps of Force One prior steps of Voltage Fourteen Neurons Predicted Voltage Department of Civil Engineering National Taiwan University Using neural network to describe the behavior of MR damper Forward Model Inverse Model

28. National Taiwan University National Center for Research on Earthquake Engineering Semi-Active Control:Control surface of fussy logic control Case 1: Case 2: Case 3:

29. deck isolator control device column md mc kc cc Department of Civil Engineering National Taiwan University Apply Fuzzy Logic Control of an Isolation System The ranges of Membership functions are defined according to the design values of isolator.

30. Department of Civil Engineering National Taiwan University Shaking Table Test of Semi-active controlled Base-isolation System Test Set-Up 1st Test: 24 ton 2nd Test: 12 ton

31. Department of Civil Engineering National Taiwan University Future application: Control of Secondary System using MR-damper (semi-active control) Primary-Secondary System Subject to ”Dominant Earthquake”

32. Department of Civil Engineering National Taiwan University Benchmark model for structural control: Active-Bracing System Passive-Bracing System Semi-Active Bracing System Index of Control Efficiency Maximum Story-drift Maximum absolute floor acceleration Maximum floor velocity Maximum story shear / base shear Maximum control force Maximum Power of the control device Total energy absorbed by the structure Total energy absorbed by the control system Maximum stroke of base-isolation system / TMD

33. Department of Civil Engineering National Taiwan University Base-isolation system / Equipment protection system Mass Damper Examine the Cost & Benefit among different control devices

34. Department of Civil Engineering National Taiwan University The End Thank you for your attention