Smart processing of data from permanent Smart processing of data from permanent monitoring systems: innovations and needsmonitoring systems: innovations and needs
(BRIMOS (BRIMOS –– EMASS)EMASS)
Herman Van Herman Van derder AuweraerAuweraer, Bart , Bart PeetersPeeters55--thth SAMCO Workshop, 26SAMCO Workshop, 26--27 Jan. 200427 Jan. 2004
5-th SAMCO WorkshopVienna, January 26-27, 2004
ContextBridge Monitoring
•• Permanent monitoring systemsPermanent monitoring systems•• LongLong--span cablespan cable--stayed and suspension bridgesstayed and suspension bridges
–– Large investmentLarge investment–– Motivated by insurance companiesMotivated by insurance companies
•• PurposePurpose–– Design verificationDesign verification–– Event recordingEvent recording
–– ArchiveArchive–– ServiceabilityServiceability
–– Health monitoringHealth monitoring•• MassiveMassive amounts of dataamounts of data
–– Smart processingSmart processing–– ManagementManagement
5-th SAMCO WorkshopVienna, January 26-27, 2004
Operational Modal AnalysisVasco da Gama Bridge
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5-th SAMCO WorkshopVienna, January 26-27, 2004
Ambient AccelerationsModes BV1 and T2
Vertical accelerationVertical accelerationTransversal accelerationTransversal acceleration
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5-th SAMCO WorkshopVienna, January 26-27, 2004
Øresund Bridge: Continuous Monitoring System Cable Forces
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5-th SAMCO WorkshopVienna, January 26-27, 2004
Future: Stonecutters Bridge in Hong Kong
•• Stonecutters Bridge (2007)Stonecutters Bridge (2007) •• WASHMS: wind and structural WASHMS: wind and structural health monitoring systemhealth monitoring system•• WindWind•• TemperatureTemperature•• AccelerationsAccelerations•• StrainsStrains•• TrafficTraffic loadingloading•• HHumidityumidity, rainfall, rainfall•• DDisplacementisplacement (by GPS)(by GPS)•• CCorrosionorrosion•• TOTAL: 1114 channels !!!TOTAL: 1114 channels !!!
5-th SAMCO WorkshopVienna, January 26-27, 2004
From Real-time Displacements to FE Model validation
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Signal capturing and processingSignal capturing and processing•• SensorsSensors•• Sensor networksSensor networks•• Data transmissionData transmission•• Data processingData processing
•• Change detectionChange detection•• Signal based methodsSignal based methods•• Model based methodsModel based methods
–– Model comparisonModel comparison–– Statistical TestStatistical Test
•• Discrimination of environmental effectsDiscrimination of environmental effects•• Data managementData management
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Smart SensorsSmart Sensors•• Use of MEMSUse of MEMS•• Optical sensorsOptical sensors•• Local digitizationLocal digitization•• Local processing (correction, calibration, preLocal processing (correction, calibration, pre--
processing, FFT, ….)processing, FFT, ….)•• Fusion of data types: vibration, displacement, Fusion of data types: vibration, displacement,
corrosion, GPS, video, environmental, static … corrosion, GPS, video, environmental, static … •• Gradual transition to advanced sensors (needGradual transition to advanced sensors (need--toto--
have basis) have basis) --> mixed mode support approach
© 2000, Stanford University© 2000, Stanford University
> mixed mode support approach
5-th SAMCO WorkshopVienna, January 26-27, 2004
SensorsOptical Fibers
•• TechnologyTechnology•• Interferometry Interferometry using 2 fibersusing 2 fibers
–– Mechanically coupledMechanically coupled–– Free reference fiber Free reference fiber
(temperature)(temperature)•• Bragg gratingsBragg gratings
–– MultiplexingMultiplexing•• OtherOther
•• Can offer added valueCan offer added value•• Quality / stabilityQuality / stability•• LongLong--term reliabilityterm reliability•• InstallationInstallation
•• ParametersParameters•• Strain (static + dynamic)Strain (static + dynamic)•• TemperatureTemperature•• HumidityHumidity•• Corrosion
©© SmartecSmartec
©© SmartecSmartecCorrosion
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• BusBus--systems and wireless transmissionsystems and wireless transmission•• Sensor network architecturesSensor network architectures•• Data bus systems (e.g. CDMA, SPDIF,…)Data bus systems (e.g. CDMA, SPDIF,…)•• Wireless transmission (from analog to WLAN…)Wireless transmission (from analog to WLAN…)
•• Critical Issues: Critical Issues: •• Absolute time synchronization (through WLAN, through Absolute time synchronization (through WLAN, through
GPS, by cable, by predictive correction…)GPS, by cable, by predictive correction…)•• Data transmission performanceData transmission performance
–– Distance versus Bit rateDistance versus Bit rate–– Accuracy, resolution, dropAccuracy, resolution, drop--out…out…
•• Power consumption and supply (cable, battery, power Power consumption and supply (cable, battery, power “scavenging”) [IMEC]“scavenging”) [IMEC]
•• Research topic at LMSResearch topic at LMS
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Breakthrough research in highBreakthrough research in high--value sectorsvalue sectors•• Medical: IMEC Human++ programMedical: IMEC Human++ program•• Space: NASA shuttle and ISSSpace: NASA shuttle and ISS•• Aeronautics: onAeronautics: on--board SHM, flutter detectionboard SHM, flutter detection•• Earthquake alert and analysis (NEEES, EEarthquake alert and analysis (NEEES, E--defense…)defense…)
•• Develop synergies, reDevelop synergies, re--use results where possibleuse results where possible•• Other EC projectsOther EC projects•• EUREKA (FLITE…)EUREKA (FLITE…)•• NationalNational•• InternationalInternational
5-th SAMCO WorkshopVienna, January 26-27, 2004
IMEC Human++ Program
5-th SAMCO WorkshopVienna, January 26-27, 2004
IMEC Human++ Program
5-th SAMCO WorkshopVienna, January 26-27, 2004
IMEC Micro-sensor and Human++ Program
5-th SAMCO WorkshopVienna, January 26-27, 2004
IMEC Micro-sensor and Human++ Program
5-th SAMCO WorkshopVienna, January 26-27, 2004
IMEC Micro-sensor and Human++ Program
5-th SAMCO WorkshopVienna, January 26-27, 2004
Example: Aerospace Wireless Communication
•• MicroTAUMicroTAU, wireless tri, wireless tri--axial axial accelerometeraccelerometer•• NASA Space ShuttleNASA Space Shuttle•• TTo detect vibration of payloads o detect vibration of payloads
during launch and landingduring launch and landing•• fsfs = 250 Hz= 250 Hz•• 9 min memory9 min memory
•• Wireless?Wireless?•• WWireless data synchronization ireless data synchronization
between units between units (±30(±30µµss @ 250Hz@ 250Hz))•• Wireless data downloadWireless data download
•• Other programs: Other programs: •• IWIS (synch. 300 ns) IWIS (synch. 300 ns) --> ISS> ISS•• WAIS (synch. 300 ns) WAIS (synch. 300 ns) --> Naval Air> Naval Air•• WATS (synch. (±10WATS (synch. (±10µµs) s) --> USAF
© INVOCON© INVOCON
> USAF
5-th SAMCO WorkshopVienna, January 26-27, 2004
Sensor Data Collection Topologies
•• Sequoia Sequoia TriaxialTriaxial Acceleration Computer (Acceleration Computer (SeTACSeTAC) [Italy]) [Italy]•• Adding data processingAdding data processing capabilitiescapabilities
© © SequoiaSequoia
5-th SAMCO WorkshopVienna, January 26-27, 2004
Wireless Communication
•• WiMMSWiMMS•• Wireless Modular Wireless Modular
Monitoring SystemMonitoring System•• The John A.The John A. BlumeBlume
Earthquake EngineeringEarthquake EngineeringCenterCenter, Stanford University, Stanford University
•• New technologiesNew technologies•• MEMS accelerometerMEMS accelerometer•• Embedded systemsEmbedded systems
–– Data acquisitionData acquisition–– Computational powerComputational power
•• Wireless communicationWireless communication–– ISM bandISM band
© Stanford University© Stanford University
5-th SAMCO WorkshopVienna, January 26-27, 2004
Wireless Communication
•• PlugPlug--andand--play sensors in wireless networksplay sensors in wireless networks
© © CrossbowCrossbow
5-th SAMCO WorkshopVienna, January 26-27, 2004
Generic Sensor Network
Communications
- wireless
- copper
- fibre
-?
Internet
Evaluation
electronicsFibre sensor
electronics
Node processor
electronics
Temperature
Humidity
pH
Wind speed
Corrosion
Strain gauge
Accelerometer
etc
“Site”
Node
Storage
Actuators ?
Some nodes have sensors, some don’t Presentation© © CSLCSL
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Distributed data processingDistributed data processing•• Local PreLocal Pre--processing: FFT, features ... processing: FFT, features ... •• Data reduction/compression (However, for modal Data reduction/compression (However, for modal
analysis: at least crossanalysis: at least cross--powers needed powers needed -- references) references) •• Local/global task distribution Local/global task distribution --> > local modal analysis?local modal analysis?•• Data request Data request –– data provision services data provision services --> Internet, LAN…> Internet, LAN…•• Use of Agent Technologies (LMS)Use of Agent Technologies (LMS)•• Specific Architectures ResearchSpecific Architectures Research
–– Berkeley: TinyBerkeley: Tiny--OS, “Motes”OS, “Motes”–– KarlsruheKarlsruhe: Smart: Smart--IT / IT / Ubicomp Ubicomp –– K.U.L. / V.U.B. in BelgiumK.U.L. / V.U.B. in Belgium–– …………
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Research ApproachResearch Approach•• Test individual solutions on existing HW platform (Test individual solutions on existing HW platform (cfrcfr. ex.). ex.)•• Then prototype integration in platform to be decidedThen prototype integration in platform to be decided
© © VCE VCE -- BRIMOSBRIMOS
© © LMSLMS © © GeoSIGGeoSIG © © Larson DavisLarson Davis
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Change detection: current research at LMS: Change detection: current research at LMS: Model based methods: Model based methods: •• Modal analysis Modal analysis --> requires automation > requires automation •• Statistical test Statistical test --> requires good nominal model and test data > requires good nominal model and test data
[INRIA approach, flutter detection][INRIA approach, flutter detection]•• Discrimination of environmental effects: importance of Discrimination of environmental effects: importance of
influence assessed, but approach to deal with it??influence assessed, but approach to deal with it??
0.00 9.96Hz 2.91e-9
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5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification: slat track
500 1000 1500 2000 2500 3000 350032.8
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5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification
•• Modal analysis automation research at LMSModal analysis automation research at LMS•• Robust and repeatable modal identificationRobust and repeatable modal identification•• Minimizing user interactionMinimizing user interaction•• Improved mathematical pole discriminationImproved mathematical pole discrimination•• I/OI/O PolyMAXPolyMAX method: discretemethod: discrete--frequency domain frequency domain
method with superior stabilization behaviour method with superior stabilization behaviour •• Now being researched for OMA applicationNow being researched for OMA application•• MultiMulti--patch data synthesispatch data synthesis•• Decision methodology:Decision methodology:
–– ClusteringClustering–– RuleRule--basedbased–– Neural NetworksNeural Networks
5-th SAMCO WorkshopVienna, January 26-27, 2004
Polymax I/O: Porsche 911 Targa Carrera 4Fully Trimmed Car
LSCELSCE PolyMAXPolyMAX
5-th SAMCO WorkshopVienna, January 26-27, 2004
Polymax I/O: Aircraft In-flight Testing
0 .0 0
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5-th SAMCO WorkshopVienna, January 26-27, 2004
Stochastic Subspace Identification (BR)Z-24
OperationalOperationalCMIFCMIF
5-th SAMCO WorkshopVienna, January 26-27, 2004
Operational PolyMAXZ-24
OperationalOperationalCMIFCMIF
5-th SAMCO WorkshopVienna, January 26-27, 2004
Operational PolyMAXMulti-Patch Processing
2 3 4Reference sensorsReference sensors
1 5
•• Method 1: Independent processingMethod 1: Independent processing•• Merging shapes by computing LS modal scaling factors between Merging shapes by computing LS modal scaling factors between
reference sensorsreference sensors•• Averaging Averaging eigenfrequencieseigenfrequencies and dampingand damping
•• Method 2: Combined processing, scale shapes afterwardsMethod 2: Combined processing, scale shapes afterwards•• All half spectra are stacked (the reference sensors appear many All half spectra are stacked (the reference sensors appear many times)times)•• Only 1 set of modal parametersOnly 1 set of modal parameters
–– Rescale shapes as in method 1Rescale shapes as in method 1•• Method 3: Combined processing, scale data on beforehandMethod 3: Combined processing, scale data on beforehand
•• Scale half spectra based on averaged spectra between the referenScale half spectra based on averaged spectra between the referencesces•• No need to scale shapes after identificationNo need to scale shapes after identification
5-th SAMCO WorkshopVienna, January 26-27, 2004
Z24-Bridge
Mode 1 Mode 2
5-th SAMCO WorkshopVienna, January 26-27, 2004
Z24-BridgeMode 3
PolyMAXPolyMAX SSISSI
5-th SAMCO WorkshopVienna, January 26-27, 2004
Z24-BridgeMode 4
SSISSIPolyMAXPolyMAX
5-th SAMCO WorkshopVienna, January 26-27, 2004
Challenges for structural monitoringand damage identification: conclusions
•• Systems research on the level ofSystems research on the level of•• Smart sensors, heterogeneous sensorsSmart sensors, heterogeneous sensors•• Sensor networks, topologies, interfaces, busesSensor networks, topologies, interfaces, buses•• Wireless transmission & synchronizationWireless transmission & synchronization•• Power consumptionPower consumption
•• Analysis methods research:Analysis methods research:•• Various detection and localization methods (Test & FE)Various detection and localization methods (Test & FE)•• PolymaxPolymax method seen as key technology for automation of method seen as key technology for automation of
OMA and hence for monitoringOMA and hence for monitoring•• Methods for environmental effect discriminationMethods for environmental effect discrimination•• Methods for decisionMethods for decision•• Local/global processing (reduction & autonomy)Local/global processing (reduction & autonomy)
•• Leverage horizontal research results: Relevant input Leverage horizontal research results: Relevant input from Medical and from Medical and AeroSpaceAeroSpace research (IMEC, CSL, research (IMEC, CSL, INRIA, LMS...)INRIA, LMS...)
5-th SAMCO WorkshopVienna, January 26-27, 2004
Thank you !Thank you !