données, shm et analyse statistique · ongoing: saint-nazaire bridge mockup gem, university of...
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Context Modal analysis Damage assessment Conclusion
Données, SHM et analyse statistique
Laurent Mevel
Inria, I4S / Ifsttar, COSYS, SIIRennes
1ère Journée nationale SHM-France
15 mars 2018
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Context Modal analysis Damage assessment Conclusion
Outline
1 Context of vibration-based SHM
2 Modal analysis
3 Damage assessment
4 Conclusion
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Context Modal analysis Damage assessment Conclusion
Context: Structural Health Monitoring
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Context Modal analysis Damage assessment Conclusion
Context: Structural Health Monitoring
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Context Modal analysis Damage assessment Conclusion
Context: Structural Health Monitoring
Physical parameter Vibration measurements
Estimate
System identification Change detection
Statistical tests 5
Context Modal analysis Damage assessment Conclusion
Outline
1 Context of vibration-based SHM
2 Modal analysis
3 Damage assessment
4 Conclusion
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Context Modal analysis Damage assessment Conclusion
Subspace methods
From automatic controlStochastic framework under ambient excitation with orwithout known inputsParameter-free – no optimisation – no iteration
Identification algorithm
Data ⇒ SVD ⇒ Least Squares ⇒ Eigenvalues
Identification of modal parametersNatural frequenciesDamping ratiosMode shapes
Mz + Cz +Kz = νy = Lz + w
xk+1 = Axk + vkyk = Cxk + wk
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Context Modal analysis Damage assessment Conclusion
Uncertainty quantification
Why?Assess quality of estimatesEstablish confidence boundsComparison of modal parameters (e.g. for monitoring)would be meaningless without uncertainty bounds
Variance due to...Unknown system inputs – ambient excitationMeasurement noiseFinite data length
Fast and memory efficient implementation foruncertainty quantification
M. Döhler and L. Mevel. Efficient multi-order uncertainty computation for stochastic subspace identification.Mechanical Systems and Signal Processing, 38(2):346-366, 2013.
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Context Modal analysis Damage assessment Conclusion
Ifsttar gantry
Vibration monitoring using PEGASE2 platformEmbedded modal analysis and uncertainty quantificationCloud application for remote monitoring
FUI SIPRIS, with VINCI ADVITAM, in collaboration with LISIS
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Context Modal analysis Damage assessment Conclusion
Ifsttar gantry
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Context Modal analysis Damage assessment Conclusion
Wind turbine: Vestas V27, with Brüel & Kjær
Modal analysis of wind turbine in operationTake into account the periodic dynamics
Also on wind turbine with CEA-tech in Pays de Loire region11
Context Modal analysis Damage assessment Conclusion
Transfer to commercial software ARTeMIS
Structural Vibration Solutions A/S, Denmark
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Context Modal analysis Damage assessment Conclusion
Outline
1 Context of vibration-based SHM
2 Modal analysis
3 Damage assessment
4 Conclusion
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Context Modal analysis Damage assessment Conclusion
Structural health monitoring
ContextChange detection in vibration measurementsDamage diagnosis for civil or mechanical structures
Damage diagnosis1 Detection: is structure damaged?2 Localization: where is the damage?3 Quantification: what is the damage extent?4 Remaining life prediction
How?“Compare” vibration data from reference and current state
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Context Modal analysis Damage assessment Conclusion
How?
Statistical distance measuresUse data from healthy state to set up a referenceCompare new dataset to reference in statistical testsExceeding threshold: alarm
Detection: data-driven – no FE model requiredLocalization, quantification: use also FE model
M. Döhler, L. Mevel, and F. Hille. Subspace-based damage detection under changes in the ambient excitationstatistics. Mechanical Systems and Signal Processing, 45(1):207-224, 2014.
M. Döhler, L. Mevel, Q. Zhang. Fault detection, isolation and quantification from Gaussian residuals with applicationto structural damage diagnosis. Annual Reviews in Control, 42:244-256, 2016.
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Context Modal analysis Damage assessment Conclusion
S101 Bridge - collaboration with BAM, Berlin
Damage detection on S101 Bridge
In FP7 IRIS: Large scale progressive damage test asbenchmark for damage identification4 days of measurements with different damage actions
Lowering a column in 3 stepsCutting the prestressing cables
Döhler, Hille, Mevel & Rücker (2014), Structural health monitoring with statistical methods during progressivedamage test of S101 Bridge. Engineering Structures, 69: 183-193. 16
Context Modal analysis Damage assessment Conclusion
S101 Bridge
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Context Modal analysis Damage assessment Conclusion
S101 Bridge
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Context Modal analysis Damage assessment Conclusion
Transfer to commercial software ARTeMIS
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Context Modal analysis Damage assessment Conclusion
Yellow Frame: damage localization
University of British Columbia, Vancouver12 accelerometers, ambient excitationDamage introduced by removing braces
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Context Modal analysis Damage assessment Conclusion
Yellow Frame: damage localization
Allahdadian, Döhler, Ventura & Mevel (2017), Damage localization of a real structure using the statistical subspacedamage localization method. International Workshop of Structural Health Monitoring.
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Context Modal analysis Damage assessment Conclusion
Ongoing: Saint-Nazaire Bridge mockup
GeM, University of Nantes10 accelerometers, white noise excitationDamage introduced by removing 2 cable rods
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Context Modal analysis Damage assessment Conclusion
Ongoing: Saint-Nazaire Bridge mockup
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Structural Health Monitoring: SIMS, CA
Context Modal analysis Damage assessment Conclusion
Outline
1 Context of vibration-based SHM
2 Modal analysis
3 Damage assessment
4 Conclusion
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Context Modal analysis Damage assessment Conclusion
Conclusion
Statistical methods for vibration analysis of civil structures1 Modal analysis with uncertainty quantification2 Damage detection, localization, quantification
Strong theoretical background, perform well under noiseFast and memory efficient implementationValidated on case studies in the lab and in the fieldAvailable for PEGASE2 and in commercial software
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Context Modal analysis Damage assessment Conclusion
Current and future focus
Coupling data with physical modelling for precise damageassessment
Multi sensors : fiber optic, morphosense, imaging, etcLocalization, quantification of damagesTemperature nuisanceMarine growthScour...
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