Department of Civil Engineering National Taiwan University National Taiwan University STRUCTURAL HEALTH MONITORING AND CONTROL RESEARCH IN NCREE Chin-Hsiung Loh Department of Civil Engineering, National Taiwan University November 17-19, 2003 NCREE, Taiwan JOINT NCREE/JRC WORKSHOP INTERNATIONAL COLLABORATION ON EARTHQUAKE DISASTER MITIGATION RESEARCH Methodologies, Facilities, Projects and Networking

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

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

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

Department of Civil Engineering National Taiwan University National Taiwan University Identification on Time-Varying System Recursive Lease Square with Variable Forgetting Recursive Least Square with Constant Trace Parametric Time-Frequency Method Wavelet Analysis 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.

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

Department of Civil Engineering National Taiwan University 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,

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

Department of Civil Engineering National Taiwan University National Taiwan University Damage Assessment: A Data Driven Modeling Problem Reasons 1.“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, …)

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

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

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

Department of Civil Engineering National Taiwan University National Taiwan University 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, Future Works

Department of Civil Engineering National Taiwan University National Taiwan University 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, Develop Benchmark Model for System Identification: Benchmark Model

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

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

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

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

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

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

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

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

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

Department of Civil Engineering National Taiwan University National Taiwan University The way ahead of SHM 1. Appropriate level of instrumentation, 1. Appropriate level of instrumentation, 2. Novel sensors, 2. Novel sensors, 3. Communications 3. Communications 4. Data mining and performance diagnosis, 4. Data mining and performance diagnosis, 5. Interdisciplinary, collaborative research, 5. Interdisciplinary, collaborative research, StructureControl Center Gateway Satellite Telephone Radio Cellular Fiber Optic Communications IP Users

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

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

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

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

Department of Civil Engineering National Taiwan University National Taiwan University deck column isolatorcontrol device mdmd mcmc kckc c Apply Fuzzy Logic Control of an Isolation System The ranges of Membership functions are defined according to the design values of isolator.

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

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

Department of Civil Engineering National Taiwan University 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

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

The End Department of Civil Engineering National Taiwan University National Taiwan University