[CS57] M. D. H. Bhuyan, Y. Lecieux, J.-C. Thomas, C. Lupi, F. Schoefs, M. Döhler, and L. Mevel, "Statistical vibration-based damage localization on saint-nazaire bridge mockup," in *Proc. 40th IABSE Symposium*, Nantes, France, 2018.

[CS58] S. Greś, M. Döhler, P. Andersen, and L. Mevel, "Variance computation of the modal assurance criterion," in *Proc. 28th Conference on Noise and Vibration Engineering (ISMA)*, Leuven, Belgium, 2018.

[CS59] L. Long, S. Thöns, and M. Döhler, "The effects of deterioration models on the value of damage detection information," in *6th International Symposium on Life-Cycle Civil Engineering (IALCCE)*, Ghent, Belgium, 2018.

[CS60] S. Greś, M. Döhler, P. Andersen, and L. Mevel, "Variance computation of MAC and MPC for real-valued mode shapes from the stabilization diagram," in *Proc. 8th International Operational Modal Analysis Conference (IOMAC)*, Copenhagen, Denmark, 2019.

[CS61] M. D. H. Bhuyan, N. Le Touz, G. Gautier, M. Döhler, F. Hille, J. Dumoulin, and L. Mevel, "Load vector based damage localization with rejection of the temperature effect," in *Proc. 8th International Operational Modal Analysis Conference (IOMAC)*, Copenhagen, Denmark, 2019.

[CS62] E. Viefhues, M. Döhler, Q. Zhang, F. Hille, and L. Mevel, "Subspace-based damage detection with rejection of the temperature effect and uncertainty in the reference," in *Proc. 8th International Operational Modal Analysis Conference (IOMAC)*, Copenhagen, Denmark, 2019.

[CS63] M. D. H. Bhuyan, M. Döhler, Y. Lecieux, C. Lupi, J.-C. Thomas, F. Schoefs, F. Hille, and L. Mevel, "Statistical subspace based damage localization on Saint-Nazaire Bridge mock-up," in *Proc. 8th International Operational Modal Analysis Conference (IOMAC)*, Copenhagen, Denmark, 2019.

[CS64] S. Greś, M. Döhler, P. Andersen, L. Damkilde, and L. Mevel, "Hankel matrix normalization for robust damage detection," in *Proc. 8th International Operational Modal Analysis Conference (IOMAC)*, Copenhagen, Denmark, 2019.

[CS65] A. Mendler, S. Allahdadian, M. Döhler, L. Mevel, and C. Ventura, "Minimum detectable damage for stochastic subspace-based methods," in *Proc. 8th International Operational Modal Analysis Conference (IOMAC)*, Copenhagen, Denmark, 2019.

[CS66] M. Baeßler, M. D. H. Bhuyan, F. Hille, E. Viefhues, M. Döhler, and L. Mevel, "Impact of environmental based effects on SHM strategies," in *Proc. 7th International Conference on Structural Engineering, Mechanics and Computation (SEMC)*, Cape Town, South Africa, 2019.

[CS67] M. Le Pen, A. Bouché, I. Guéguen, M. Döhler, L. Mevel, and V. Le Cam, "Phased and synchronous sampling between multiple smart network sensors for modal assessment of large structures," in *12th International Workshop on Structural Health Monitoring (IWSHM)*, Stanford, CA, USA, 2019.
[CS68] A. Mendler, M. Döhler, C. E. Ventura, and L. Mevel, "The minimum detectable damage as an optimization criterion for performance-based sensor placement," in *Proc. 38th International Modal Analysis Conference (IMAC)*, Houston, TX, USA, 2020.

[CS69] B. Merainani, B. Xiong, V. Baltazart, J. Dumoulin, M. Döhler, and Q. Zhang, "Experimental investigation of structural modal identification using pixels intensity and motion signals from video-based imaging devices: Performance, comparison and analysis," in *Proc. SPIE Optical Metrology*, 2021.

[CS70] S. Greś, M. Döhler, and L. Mevel, "Statistical optimization for subspace-based damage quantification," in *10th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII)*, 2021.

[CS71] E. Viefhues, M. Döhler, P. Simon, R. Herrmann, F. Hille, and L. Mevel, "Stochastic subspace-based damage detection of a temperature affected beam structure," in *10th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII)*, 2021.

[CS72] A. Mendler, A. Cadoret, C. Freyssinet, M. Döhler, Y. Lecieux, L. Mevel, and C. Ventura, "Minimum localizable damage for stochastic subspace-based damage diagnosis," in *10th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII)*, 2021.

[CS73] S. Greś, A. Mendler, N.-J. Jacobsen, P. Andersen, and M. Döhler, "Statistical damage detection and localization with Mahalanobis distance applied to modal parameters," in *Proc. 9th International Operational Modal Analysis Conference (IOMAC)*, Vancouver, Canada, 2022.

[CS74] J. Priou, S. Greś, M. Perrault, L. Guerineau, and M. Döhler, "Automated uncertainty-based extraction of modal parameters from stabilization diagrams," in *Proc. 9th International Operational Modal Analysis Conference (IOMAC)*, Vancouver, Canada, 2022.

[CS75] A. Mendler, M. Döhler, and C. U. Grosse, "Selection of damage-sensitive features based on probability of detection curves," in *Proc. 9th International Operational Modal Analysis Conference (IOMAC)*, Vancouver, Canada, 2022.

[CS76] M. Döhler, "Quantification of statistical uncertainties in subspace-based operational modal analysis and their applications," in *Proc. 9th International Operational Modal Analysis Conference (IOMAC)*, Vancouver, Canada, 2022.

[CS77] A. Mendler, S. Greś, M. Döhler, and S. Keßler, "On the probability of localizing damages based on mode shape changes," in *Proc. 10th European Workshop on Structural Health Monitoring (EWSHM)*, Palermo, Italy, 2022.

[CS78] A. Mendler, M. Döhler, and F. Hille, "Detecting changes in boundary conditions based on sensitivity-based statistical tests," in *Proc. International Symposium on Non-Destructive Testing in Civil Engineering (NDT-CE)*, Zurich, Switzerland, 2022.
[CS79] S. Greś and M. Döhler, "Uncertainty propagation in subspace methods for operational modal analysis under misspecified model orders," in *Proc. 30th Conference on Noise and Vibration Engineering (ISMA)*, Leuven, Belgium, 2022.

[CS80] A. Mendler, M. Döhler, and C. U. Grosse, "POD curves for natural frequency testing," in *Proc. International Conference on NDE 4.0*, Berlin, Germany, 2022.

[CS81] Z. Luo, B. Merainani, M. Döhler, V. Baltazart, and Q. Zhang, "Efficient subspace-based operational modal analysis using video-based vibration measurements," in *Proc. 10th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES)*, Milan, Italy, 2023.

[CS82] S. Greś and M. Döhler, "Model order selection for uncertainty quantification in subspace-based OMA of Vestas V27 blade," in *Proc. 10th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES)*, Milan, Italy, 2023.

[CS83] A. Cadoret, C. Freyssinet, M. D. H. Bhuyan, Y. Lecieux, M. Döhler, and L. Mevel, "Suivi de vibrations pour la localisation de dommages : Application à une maquette du pont de Saint Nazaire," in *Proc. Diagnobéton*, Nantes, France, 2023.

## Book chapters

[B1] M. Döhler, F. Hille, L. Mevel, and W. Rücker, in *IRIS Industrial Safety and Life Cycle Engineering – Technologies / Standards / Applications*. VCE, 2013, ch. Estimation of modal parameters and their uncertainty bounds from subspace-based system identification, 91–106, ISBN: 978-3-200-03179-1.

[B2] M. Döhler, F. Hille, and L. Mevel, in *Mechatronics for Cultural Heritage and Civil Engineering*, E. Ottaviano, A. Pelliccio, and V. Gattulli, Eds. Cham: Springer International Publishing, 2018, ch. Vibration-based monitoring of civil structures with subspace-based damage detection, 307–326, ISBN: 978-3-319-68646-2.

## Theses

[T1] M. Döhler, *Nonequispaced fast Fourier transform on the hyperbolic cross*, In German. Master thesis, Chemnitz University of Technology, Germany, 2008.

[T2] M. Döhler, *Subspace-based system identification and fault detection: Algorithms for large systems and application to structural vibration analysis*, PhD thesis, Université de Rennes 1, France, 2011.
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Abstract

Vibration-based structural health monitoring (SHM) of engineering structures like bridges,
buildings or wind turbines in operation has the objective to ensure their serviceability and
to prevent failure due to damage. It can be based on the analysis of a linear system from
measured vibration data over time, where system identification methods are required to ob-
tain the structural dynamical characteristics from data, and fault diagnosis is used to detect,
locate and quantify changes in the system. Challenges for data processing are limited noisy
measurements under unknown ambient excitation, high model orders, and linking data to
(imperfect) physical models. In this work, the robustness of methods under realistic ap-
plication conditions is considered, by evaluating and incorporating statistical uncertainty,
improving numerical efficiency and removing nuisance, with the overall goal of developing
automated SHM methods.

After focusing on efficient subspace-based identification methods for diverse operational
modal analysis problems, a consistent and numerically efficient framework for the associated
uncertainty quantification is developed. Then, a focus is made on statistical damage diagno-
sis, where robust method development enables real-world applications. Finally, a framework
to analyze detectability and localizability is established for the considered class of methods,
allowing further reliability assessment and SHM performance prediction.

Résumé

La surveillance de l'intégrité des structures (Structural Health Monitoring, SHM) des ou-
vrages d'art tels que les ponts, les bâtiments ou les éoliennes a pour objectif de garantir leur
bon fonctionnement et de prévenir les défaillances dues à l'usure ou aux endommagements au
cours du temps. Elle peut être basée sur l'analyse d'un système linéaire à partir de données vi-
bratoires mesurées. Les méthodes d'identification des systèmes sont nécessaires pour obtenir
les caractéristiques dynamiques à partir des données, et les méthodes de diagnostic des défauts
sont utilisées pour détecter, localiser et quantifier les changements dans le système. Les défis
pour le traitement des données sont, notamment, que les mesures sont limitées et bruitées,
l'excitation est souvent inconnue, les ordres de modèle sont élevés, et le lien entre données et
modèles physiques (imparfaits) est nécessaire pour un diagnostic avancé. Dans ces travaux,
la robustesse des méthodes dans des conditions d'application réalistes est étudiée, en évaluant
et en incorporant l'incertitude statistique, en améliorant l'efficacité numérique et en traitant
les nuisances, dans le but général de développer des méthodes SHM automatisées.

Après s'être focalisé sur les méthodes d'identification sous-espace efficaces pour divers
problèmes d'analyse modale opérationnelle, une méthodologie numériquement efficace pour
la quantification de l'incertitude associée est développée. Ensuite, l'accent est mis sur le
diagnostic statistique des endommagements, où le développement de méthodes robustes per-
met de considérer des applications réalistes. Enfin, une méthodologie pour l'analyse de la
détectabilité et de la localisabilité est établie pour la classe de méthodes considérée, ce qui
permet l'évaluation de la fiabilité et la prédiction des performances SHM.