Structural Health Monitoring - Reluis · SHM Definition - 1996 Damage Identification and Health...

Structural Health Monitoring

A overview of an evolving research areaPart 2 (SHM)

Bob Bolton

SHM Definition - 1996

Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review

Doebling, S W, C R Farrar, et al (1996) Damage Identification and Health Monitoring of Structural and Mechanical Systems From Changes in Their Vibration Characteristics: A Literature Review, LA-13070-MS Los Alamos National Laboratory http://wwwlanlgov/projects/ei/shm/publicationsshtml

SHM Definition – 1996Classification of methodsA system of classification for damage-identification

methods, as presented by Rytter (1993), defines four levels of damage identification, as follows:

Level 1: Determination that damage is present in the structure Level 2: Determination of the geometric location of the damage Level 3: Quantification of the severity of the damage Level 4: Prediction of the remaining service life of the structure

Rytter, A (1993) Vibrational Based Inspection of Civil Engineering Structures Aalborg, Denmark, University of Aalborg PhD

SHM Definition – 1996Damage Identification Methods

Frequency ChangesThe Forward ProblemThe Inverse Problem

Mode Shape ChangesMode Shape Curvature/Strain Mode Shape ChangesDynamically Measured Flexibility

Comparison of Flexibility ChangesUnity Check MethodStiffness Error Matrix MethodEffects of Residual FlexibilityChanges in Measured Stiffness Matrix

Matrix Update MethodsObjective Functions and ConstraintsOptimal Matrix Update MethodsSensitivity-Based Update MethodsEigenstructure Assignment MethodHybrid Matrix Update Methods and Other Considerations

Nonlinear MethodsNeural Network-Based MethodsOther Methods

SHM Definition – 2004 Definition of DamageDamage is defined as changes introduced into a system

that adversely affects its current or future performance.Damage is not meaningful without a comparison between two system states, one is often an initial or undamaged state. System changes include material and/or geometric property changes, changes in boundary conditions, and changes in system connectivity.

Sohn, H., C. R. Farrar, et al. (2004). A Review of Structural Health Monitoring Literature form 1996-2001,. LA-13976-MS. Los Alamos National Laboratory. http://www.lanl.gov/projects/ei/shm/publications.shtml.

SHM Definition – 2004 Definition of Damage StateThe damage state of a system can be described

along the lines of the levels from Rytter (1993).

Questions to ask:1. Is there damage in the system (existence)?2. Where is the damage in the system (location)?3. What kind of damage is present (type) ?4. How severe is the damage (extent)?5. How much useful life remains (prognosis)?

SHM Definition – 2004 Definition of Structural Health Monitoring

Structural Health Monitoring (SHM) is the process of implementing a damage detection strategy for engineering infrastructure. Usage monitoring (UM) Measure inputs to and responses of a structure before damage so the onset of damage and deterioration can be identified. Prognosis is the coupling of information from SHM, UM, environmental and operational conditions, component and system level testing, and modeling to estimate condition and useful life.

SHM Definition – 2004 Components of a SHM Process

1. Operational Evaluation

2. Data Acquisition, Fusion, and Cleansing

3. Feature Extraction and Information Condensation

4. Statistical-Model Development for Feature Discrimination

SHM Definition – 2004 1. Operational Evaluation

Topics to address:Economic and/or Life-Safety IssuesDefinition of Damage Environmental and/or Operational Constraints Data Management

SHM Definition – 2004 2. Data Acquisition, Fusion, and CleansingSensing and collection issues:

Excitation MethodsForced ExcitationAmbient ExcitationLocal Excitation

Sensing Structural ResponseStrainDisplacementAcceleration TemperatureWindOther Measurement QuantitiesMEMS Technology for Sensing MotionFiber-Optic SensorsSensor PlacementOther Issues

Data TransmissionWired TransmissionWireless Transmission

SHM Definition – 2004 3. Feature Extraction and Information CondensationParameters and methods:

Resonant FrequenciesFrequency Response FunctionsMode Shapes (MAC and CoMAC)Mode Shape Curvatures Modal Strain EnergyDynamic FlexibilityDampingAntiresonanceRitz VectorsARMA Family ModelsCanonical Variate Analysis (CVA)

Nonlinear FeaturesTime-Frequency AnalysisEmpirical Mode DecompositionHilbert TransformPrincipal Component Analysis or Singular Value DecompositionFinite Model UpdatingWave PropagationAutocorrelation FunctionsOther Features

SHM Definition – 2004 4. Statistical-Model Development for Feature Discrimination

Supervised LearningResponse Surface AnalysisFisher’s DiscriminantNeural NetworksGenetic AlgorithmsSupport Vector Machines

Unsupervised Learning

Control Chart AnalysisOutlier DetectionNeural NetworksHypothesis Testing

Other Probability Analyses

Totals: 180 pages

SHM Definition – 2004Applications & Related information

Applications Aerospace - 11 papersCivil Infrastructure

Bridges - 30 papersBuildings - 5 papers

Beams - 6 papersComposites - 15 papersOthers -16 papers

Related informationSHM Projects - 9 projectsWeb Sites - 16 sitesConferences - 9 conf.Journals – 7 journals

SHM State of the art – 2006Final comments from: Montalvao, D., N. M. M. Maia, et al. (2006). "A review of vibration-based

structural health monitoring with special emphasis on composite materials." Shock and Vibration Digest 38(4): 295-324.

Many techniques exist for the identification and location of damage. No method solves all problems in all structures. Techniques have damage related sensitivities. A sensitive technique may produce false-positives. A less sensitive technique may give false-negatives. Defect size has a noise floor.Researchers are exploring multiple detection strategies.Exploration of non-linear parameters is increasing.

SHM State of the art – 2006Final comments from:Montalvao, D., N. M. M. Maia, et al. (2006). "A review of vibration-based

structural health monitoring with special emphasis on composite materials." Shock and Vibration Digest 38(4): 295-324.

The quantification of damage and prediction of the remaining lifetime are the most difficult issues, particularly the latter.Most traditional detection methods are based on appreciable reductions in rigidity of a structural elementMust relate reduction in rigidity to a decrease in strength or life. Prognosis must still deal with this. Statistical methods have seen considerable development in dealing with experimental errors, incompleteness, and environmental and operational conditions. Statistical pattern recognition techniques that allow for a reduction in sensors still requires considerable further work.

SHM State of the art – 2007Worden, K., C. R. Farrar, et al. (2007). "The fundamental axioms of structural health monitoring." Proceedings of the Royal Society of London, Series A (Mathematical, Physical and Engineering Sciences) 463(2082): 1639-64.

Based on the extensive literature that has developed on structural health monitoring over the last 20 years, it can be argued that this field has matured to the point where several fundamental axioms, or general principles, have emerged. The intention of this paper is to explicitly state and justify theseaxioms. In so doing, it is hoped that two subsequent goals are facilitated. First, the statement of such axioms will give new researchers in the field a starting point that alleviates the need to review the vast amounts of literature in this field. Second, theauthors hope to stimulate discussion and thought within the community regarding these axioms.

SHM State of the art – 2007Worden, K., C. R. Farrar, et al. (2007). "The fundamental axioms of structural health monitoring." Proceedings of the Royal Society of London, Series A (Mathematical, Physical and Engineering Sciences) 463(2082): 1639-64.

Based on the extensive literature that has developed on structural health monitoring over the last 20 years, it can be argued that this field has matured to the point where several fundamental axioms, or general principles, have emerged. The intention of thispaper is to explicitly state and justify these axioms. In so doing, it is hoped that two subsequent goals are facilitated. First, the statement of such axioms will give new researchers in the field a starting point that alleviates the need to review the vast amounts of literature in this field. Second, the authors hope to stimulate discussion and thought within the community regarding these axioms.

Axiom I: All materials have inherent flaws or defects.AxiomII: The assessment of damage requires a comparison between two systemstates.Axiom III: Identifying the existence and location of damage can be done in anunsupervised learningmode, but identifying the type of damage present and thedamage severity can generally only be done in a supervised learning mode.Axiom IVa: Sensors cannot measure damage. Feature extraction throughsignal processing and statistical classification is necessary to convert sensordata into damage information.Axiom IVb: Without intelligent feature extraction, the more sensitive ameasurement is to damage, themore sensitive it is to changing operational andenvironmental conditions.Axiom V: The length- and time-scales associated with damage initiation andevolution dictate the required properties of the SHM sensing system.Axiom VI: There is a trade-off between the sensitivity to damage of analgorithm and its noise rejection capability.Axiom VII: The size of damage that can be detected from changes in systemdynamics is inversely proportional to the frequency range of excitation.

Application Rapid Analysis/Automation

Estimating dynamic properties of a stadiumAmbient vibrations at the roof of a football stadium were

recorded during a football game.

4 hours of acceleration datasampled at 80 HzComplete data set analyzed in a very short timeUsing PolyMAX resulted in extremely clear stabilization diagrams automating parameter ID

Peeters, B., H. Van Der Auweraer, et al. (2007). "Operational modal analysis for estimating the dynamic properties of a stadium structure during a football game." Shock and Vibration 14(4): 283-303.


Estimating dynamic properties of a stadium


Estimating dynamic properties of a stadium Rapid reduction of data – 4 seconds


Estimating dynamic properties of a stadiumComparison of PolyMAX and SSI

extraction methods:PolyMAX much fasterBoth methods had trouble following higher modes during event

Application Level 4 seismic monitoring system

Real-time seismic monitoringCelebi, M., A. Sanli, et al. (2004). "Real-time seismic monitoring needs

of a building owner - And the solution: A cooperative effort." Earthquake Spectra 20(2): 333-346.

Problem: The building owner needs timely advice on whether or not to occupy the building following an event.

Solution: Analysis of building response during strong-shaking event allows owner to assess possible post-earthquake inspection, retrofit, and repair needs.


Real-time seismic monitoringThe owner and the consultants have

agreed that general building-related evaluation will commence in the building following any one of the following events:

A state of emergency in the city or county of San Francisco has been declared,A M6.0 earthquake on the San Andreas or Hayward or Rodgers Creek faults, orPeak ground acceleration greater than 0.25 g (this is intended as free-field motion and adopted from Table 3-1, FEMA-352 [SAC 2000]).


Real-time seismic monitoring

Monitoring System Requirements

The system must facilitate rapid assessment of the building integrity following an earthquake;The system must provide data correlated with known and building specific engineering parameters, drift ratio, related to the expected damage conditionThe monitoring system must deliver the data within a relatively short time (a few minutes if not in seconds).


Real-time seismic monitoring

Monitoring System Status

Waiting for an eventProducing low amplitude data in real time for analyses and assessment.

System can be used for:Post event seismic assessmentTrending of structural characteristics and damage

Application Advanced technology monitoring system

GPS Bridge monitoring systemA real-time kinematic (RTK) global positioning system (GPS) has been

developed and installed on the Humen Bridge for monitoring of bridge deck motion from:

Seismic activityTraffic loadEnvironmentTemperature Wind

Guo, J., L. Xu, et al. (2005). "Application of the Real-Time Kinematic Global Positioning System in Bridge Safety Monitoring." Journal of Bridge Engineering10(2): 163-168.


GPS Bridge monitoring systemThe Humen Bridge GPS

RTK on-line monitoring system is a permanent installation It includes:

A RTK reference station12 GPS monitoring stations (7 currently installed)An optical fiber communication network A control center


GPS Bridge monitoring systemSome measurements:

Lateral Displacement

vs Wind

Vertical Displacement

vs Temperature


GPS Bridge monitoring systemSome measurements:

SpectralDensity

ResonantFrequencies


GPS Bridge monitoring systemMonitoring System Status

Implemented GPS RTK technology provide real-time multi-point displacement measurements.

Sample Rate: 1 and 20 Hz Displacement Accuracy: ±1 cmDeformation: Vertical, Lateral, RotationEstimate characteristic frequencies Traffic management system: Alarm warns drivers when displacements are beyond critical values

Torsional deck rotationduring typhoon

Application Long-term seismic monitoring

Building seismic monitoringDurand, F., J. Rogers, et al. (2004). Ambient vibration and earthquake strong-

motion data sets for selected USGS extensively instrumented buildings. Open-File Report 2004-1375. U. S. Geologic Survey, N. S. M. Program, 345 Middlefield Road, Melno Park, CA.

The buildings selected for this study meet three criteria:

(1) they are located in either the greater Los Angeles or San Francisco Bay areas;

(2) they are extensively instrumented by the USGS; and

(3) they have been strongly shaken by earthquakes with peak ground accelerations in excess of 10% of the acceleration of gravity.


Building seismic monitoring

Name and location of extensively instrumented buildings in the study.


Building seismic monitoring

Available data for three buildings.

Stat.No

Station Name City Event

DateEvent Name

Lat. (deg)

Long. (deg) M Dist.

(km)

Peak Base A (g)

Peak Roof A (g)

1103 Great Western Berkeley 18-Oct-

89Loma Prieta 37.04 -121.88 6.9 99 0.117 0.233

1662Pacific ParkPlaza

Emeryville

18-Oct-89

Loma Prieta 37.04 -121.88 6.9 97 0.232 0.49

02-Feb-03 Dublin 34.740 -121.937 3.6 34 0.005 0.008

523912440

ImperialHwy

Norwalk17-Jan-94 Northridge 34.21 -118.54 6.7 55 0.061 0.148

01-Oct-87

Whittier Narrows* 34.06 -118.08 6.1 16 N/A N/A

* Currently being processed


Building seismic monitoringFormer Great Western Savings BuildingThe former Great Western Savings building was constructed in 1969. The fourteen-story

building was constructed using an proprietary lift-slab structural system, with floors poured at the base of two concrete towers and then jacked into place.

The building underwent a limited-scope, retrofit in 2000.


Building seismic monitoringPacific Park PlazaThe thirty-story Pacific Park

Plaza building in Emeryville was constructed in 1984. The lateral force resisting system is a ductile concrete moment-resisting frame. The building has a delta wing plan and several re-entrant corners at the wing ends. The building was extensively instrumented by the USGS with sensors. The structural array is complemented by free-field and bore-hole instruments.


Building seismic monitoringImperial Norwalk CentreThe former Bechtel office

building in Norwalk is now occupied by a number of local and federal law enforcement agencies. The building is a 7- story steel moment-framed structure constructed in the early 1980’s.

The building has an unusually high aspect ratio (>3:1) in plan, but no significant vertical or plan irregularities. The analog structural array has recorded a number of Southern California earthquakes, including the 1987 Whittier Narrows and 1994 Northridge quakes.

Conclusions (my personal)

Extremely many fields involved

Spread over a wide range of applications

Methods are getting mature

Instrumentation is getting affordable

Extreme potential

It is going to be reality – we think

We better co-operate (a lot)

Structural Health Monitoring - Reluis · SHM Definition - 1996 Damage Identification and Health...

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