Nonparametric Data-Driven Modeling of Linear Systems ESTIMATING THE FREQUENCY RESPONSE AND IMPULSE RESPONSE FUNCTION

Frequency response function (FRF) and impulse response (IR) measurements provide a first view on the dynamics of a system. Previously developed FRF measurement methods were optimized for the available computer power at that time. These classical methods are still popular in engineering curricula and industry. However, more advanced algorithms are now available that can reduce the measurement time and errors by a factor of two to 100 by making better use of the increased compute power. Because these methods are not well known to the public, they are not frequently used, leading to a waste of money, resources, and time. The goal of this article is to bridge this gap by providing a deeper insight into the underlying problems of FRF and IR measurements and to use this better understanding to introduce the recent more powerful methods. Links to publicly available software are provided, which helps to reconstruct the results shown in this article and minimizes the effort to adopt these new algorithms.

Jaar van publicatie:2018

BOF-keylabel:ja

BOF-publication weight:3

CSS-citation score:2

Auteurs:International

Authors from:Higher Education

Toegankelijkheid:Closed