In this paper, a novel decentralized modal identification method is proposed utilizing the
concepts of sparse blind source separation (BSS) and parallel factor decomposition. Unlike …

Popular ambient vibration-based system identification methods process information
collected from a dense array of sensors centrally to yield the modal properties. In such …

Blind source separation (BSS) based methods have been shown to be efficient and powerful
to perform output-only modal identification. Existing BSS modal identification methods …

During these years, blind source separation (BSS) techniques have been demonstrated as a
promising tool for operational modal identification of large-scale engineering structures only …

Output-only modal identification plays an important role in the structural health monitoring of
large-scale structures. In recent years, blind source separation (BSS) has achieved great …

In this paper, a new decentralized identification method based on the principles of blind
source separation (BSS) that can perform modal identification in the presence of …

Blind source separation receives increasing attention as an alternative tool for operational
modal analysis in civil applications. However, the implementations on real-life structures in …

It is practical to develop a modal identification method using a decentralized sensor network
for field tests. Sparse component analysis (SCA) is a potential method in the framework of …

Sparse component analysis (SCA) approach was adopted to handle underdetermined blind
modal identification of structures, where the number of sensors is less than the number of …

Ambient system identification in noisy environments, in the presence of low‐energy modes
or closely‐spaced modes, is a challenging task. Conventional blind source separation …