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Operational Modal Parameters Identification Using the ARMAV Model

2018
Applied system identification is an important issue in science and engineering. Experimental modal analysis is used to describe the dynamical behavior of structures, in general, for a given set of input and output data. This article deals with multidimensional modal parameters identification valid for output-only data—operational modal analysis (OMA ...
Heraldo N. Cambraia   +2 more
openaire   +1 more source

Modal parameter identification from operative responses

2006
Modal parameter estimates of a structure, vibrating under actual loadings and operational conditions, have addressed the interest of researchers during the last years. For all the developed approaches, structures need not be excited by expensive devices, because the modal signature of the structure can be achieved from the knowledge of the system time ...
AGNENI, Alessandro, COPPOTELLI, Giuliano
openaire   +1 more source

Identification of Modal Parameters from Inconsistent Data

2002
Most of the recent modal parameter estimators start from the fact that natural frequencies, damping ratios and modal participation factors are global parameters of the measured structure. Measuring the structure in different patches can however cause inconsistencies in the data due to e.g. the mass-loading effect of the accelerometers.
Cauberghe, Bart   +3 more
openaire   +1 more source

Concentrated Modal Parameter Identification Based on Modal-Wavelet Continuous Transformation

2010 Chinese Conference on Pattern Recognition (CCPR), 2010
Qingwei Ye   +3 more
openaire   +1 more source

Mechanisms controlling pancreatic islet cell function in insulin secretion

Nature Reviews Molecular Cell Biology, 2021
Jonathan Campbell, Christopher B Newgard
exaly  

Identification of Modal Parameters with Morlet-Wave Integral

2023
Identifying modal parameters from short and noisy signals is a challenging task. When the modal parameters are identified from the free response, then the problem of noise in the signal becomes very important ; especially for the high frequencies where the response due to high- frequencies and damping falls below the level of noise in the signal much ...
openaire  

Towards multi-modal causability with Graph Neural Networks enabling information fusion for explainable AI

Information Fusion, 2021
Andreas Holzinger   +2 more
exaly  

A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks

Nature Machine Intelligence, 2023
Yeonghun Kang, Hyunsoo Park, Berend Smit
exaly  

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