Michael Döhler

Inria Centre de Recherche Rennes Bretagne Atlantique

France

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Articles (16)

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2025

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2025

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2024

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2024

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2024

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2021

Collaborators (6)

Sebastian Thöns

Lund University

SWEDEN

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Christian Ulrich Grosse

Technical University of Munich

GERMANY

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Qinghua Zhang

Inria Centre de Recherche Rennes Bretagne Atlantique

FRANCE

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Vincent Baltazart

Université Gustave Eiffel

FRANCE

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Jon Juel Thomsen

Technical University of Denmark

DENMARK

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Szymon Gres

Aarhus University

DENMARK

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Michael Döhler

Research Interests

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Articles (16)

Subspace-based noise covariance estimation for Kalman filter in virtual sensing applications

Variance estimation of modal parameters from the poly-reference least-squares complex frequency-domain algorithm

Subspace-based modal identification and uncertainty quantification from video image flows

Automated modal parameter tracking with neural network based normalization of environmental perturbations

Predictive Probability of Localization Curves (P-POL) for Structures with Changing Environmental Conditions

Rejection of parametric model errors in a recursive Kalman filter for virtual sensing applications

Predictive probability of detection curves based on data from undamaged structures

Localizability of damage with statistical tests and sensitivity-based parameter clusters

Uncertainty quantification of input matrices and transfer function in input/output subspace system identification

Sensor placement with optimal damage detectability for statistical damage detection

Determination of structural and damage detection system influencing parameters on the value of information

Statistical subspace-based damage detection with estimated reference

Statistical model-based optimization for damage extent quantification

Subspace‐based Mahalanobis damage detection robust to changes in excitation covariance

Kalman filter-based subspace identification for operational modal analysis under unmeasured periodic excitation

A reliability-based approach to determine the minimum detectable damage for statistical damage detection

Collaborators (6)

Sebastian Thöns

Christian Ulrich Grosse

Qinghua Zhang

Vincent Baltazart

Jon Juel Thomsen

Szymon Gres

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