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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