Uncertainty quantification in operational modal analysis with stochastic subspace identification: Validation and applications

Operational Modal Analysis using a Fast Stochastic Subspace Identification Method

Stochastic subspace identification methods are an efficient tool for system identification of mechanical systems in Operational Modal Analysis, where modal parameters (natural frequencies, damping ratios, mode shapes) are estimated from measured ambient vibration data of a structure. System identification is usually done for many successive model orders, as the true system order is unknown. The...

Uncertainty Quantification for Stochastic Subspace Identification of Multi-Setup Measurements

In Operational Modal Analysis, the modal parameters (natural frequencies, damping ratios and mode shapes) obtained from Stochastic Subspace Identification (SSI) of a structure, are afflicted with statistical uncertainty. For evaluating the quality of the obtained results it is essential to know the appropriate confidence intervals of these figures. In this paper we present algorithms that autom...

Reference-based Stochastic Subspace Identification for Output-only Modal Analysis

When performing vibration tests on civil engineering structures, it is often unpractical and expensive to use arti"cial excitation (shakers, drop weights). Ambient excitation on the contrary is freely available (tra$c, wind), but it causes other challenges. The ambient input remains unknown and the system identi"cation algorithms have to deal with output-only measurements. For instance, realisa...

Stochastic System Identification for Operational Modal Analysis: A Review

This paper reviews stochastic system identification methods that have been used to estimate the modal parameters of vibrating structures in operational conditions. It is found that many classical input-output methods have an output-only counterpart. For instance, the Complex Mode Indication Function (CMIF) can be applied both to Frequency Response Functions and output power and cross spectra. T...

Stochastic system identification for operational modal analysis: a review AUTHORS