DOI: 10.71758/refodat.46
title: Assessment and Reduction of Uncertainties in Operational Modal Analysis (RUN-OMA): Supplemental Data

description: The RUN-OMA project developed a novel methodology to objectively and transparently evaluate the quality of results from Operational Modal Analysis (OMA) — a technique used to determine the modal parameter of structures, such as natural frequencies, damping ratios and mode shapes. These properties are benefitial for assessing structural integrity and durability. Until now, the evaluation of such results has often relied on subjective judgment and expert experience, posing the risk of unnoticed inaccuracies affecting further analyses. The project's primary goal was to create a scientifically sound and automatable method for quantifying Polymorphic Uncertainties — encompassing both aleatory (random) and epistemic (knowledge-based) uncertainties arising throughout the measurement and analysis chain, such as sensor noise, unknown analysis parameters, or undetermined signal properties. At the heart of the project lies a comprehensive process model that maps all stages from structural excitation and vibration measurement to modal analysis. Based on this, methods were developed for polymorphic uncertainty quantification, assessment of signal suitability with respect to an OMA, and cross-validation of identified dynamic systems. These methods enable a more reliable evaluation of OMA results, leading to better-informed decisions in structural assessment. The developed techniques were implemented in open-source software and applied to realistic numerical models. All tools and results are publicly documented and accessible. The project thus makes a significant contribution to the transparency, reproducibility, and advancement of modern analysis methods in structural dynamics.
description: The following list the folders and subfolders of the repository and a short summary of its contents. Also the naming conventions for the files in these folders will be stated. estimations: contains subfolders with the data for the PolyUQ objects at the different stages of the uncertainty quantification (UQ) process. The subfolders follow the naming convention: {output}_{method}_{mode_no} where output is one of : d: damping ratio, f: natural frequency, scs: signal clarity score, snr_db: signal-to-noise ratio, sum_mc: modal reconstruction percentage method is one of the OMA methods: cf: poly-Reference Least Squares Complex Frequency (pLSCF) sc: covariance-driven Stochastic Subspace Identification (SSI-cov) sd: data-driven Stochastic Subspace Identification (SSI-data) mode_no: is the number of the 13 vibration modes (0 … 12) of interest Each subfolder contains the following files (in the order of the UQ process: polyuq_prop.npz: the propagated output samples polyuq_sens.npz: the results of the sensitivity analyses polyuq_imp.npz: the results and parameters of the Imprecision processing analyses polyuq_{estimator}_inc.npz: the final results and parameters of the Incompleteness and Variability processing analyses, where estimator is the used statistical estimator and one of avg: the average estimator hist: the histogram estimator cdf: the empirical cumulative probability distribution estimator samples: contains the input and output databases and supplemental data of the uncertainty processing step, which was performed in parallel on a HPC cluster. The majority of intermediate result data (~20 TB) is not present in this repository but is stored on tape storage at the Bauhaus-Universität Weimar and can be supplied upon reasonable request. dm_oma_a.nc: The input database as a NetCDF file to be opened with the python module xarray dm_oma_a_out_pre_clust.nc: The raw output database as a NetCDF file to be opened with the python module xarray dm_oma_a_out.nc: The output database post vibration mode-clustering as a NetCDF file to be opened with the python module xarray mechanical_frf.dat: The frequency response function of the mechanical model that was used to generate output vibration data from wind field input forces mechanical.npz: the model data to be used for setting up the mechanical model figures: contains all figures, both in PDF and PNG format, that have been derived from the result data. A selection of these will be published in the Dissertation of Simon Marwitz. The figures follow different naming conventions: imp_loo_accuracy{output}_{method}_{mode_no}: The histograms of the RBF interpolator leave-one-out validation errors (quality control of the Imprecision processing step). inc_{estimator}_{aggregate}_{output}_{method}_{mode_no}: Diagrams derived from the final Incompleteness processing results. For the definitions of estimator,output,method and mode_no see above. Additionally, method or mode_no may be all indicating a plot that contains multiple methods or vibration modes. Aggregate may be one of the Belief aggregation methods foc: Plot of Focal intervals, no belief aggregation pl: Plot of Plausibility functions derived from the Focal intervals. rbf_epsilon{output}_{method}_11: The interpolation error of the RBF interpolator with varying kernel shape parameter epsilon. sensi{output}_{method}_{mode_no}: Errorbar plots of the sensitivities of the respective output quantity with respect to all input variables sensi_stage{n}_{method}_: Combined plot of the sensitivities of all outputs of the respective stage of the OMA process model: 23: stages 2 and 3 (Ambient Vibration Testing and Signal Processing) 4: Final stage (Modal Analysis) At the root level, the following files reside: example_reconstruction_validation_{method}: result data of the reconstruction error method for the three OMA methods polyuq_samp.npz: The input samples for the of the UQ process polyuq_samp_stage1.npz: The input samples for the of the UQ process with the first stage of the OMA process model