Output-only modal identification has seen significant activity in recent years, especially in
large-scale structures where controlled input force generation is often difficult to achieve …

Ocular artifacts (OAs) are one the most important form of interferences in the analysis of
electroencephalogram (EEG) research. OAs removal/reduction is a key analysis before the …

Real‐time health monitoring of stay cables in cable‐stayed bridges is necessary for timely
maintenance and to avoid unforeseen fatigue damage due to vortex‐induced vibration …

A novel reference free approach for identifying structural modal parameters using recursive
canonical correlation analysis (RCCA) is proposed in this paper. Using first order eigen …

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 …

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 …

This paper presents a new paradigm of explicitly modeling and harnessing the data
structure to address the inverse problems in structural dynamics, identification, and data …

Output-only algorithms are needed for modal identification when only structural responses
are available. The recent years have witnessed the fast development of blind source …

Modal identification or testing of structures consists of two phases, namely, data acquisition
and data analysis. Some structures, such as aircrafts, high-speed machines, and plate-like …

In this study, we propose a machine‐learning‐based approach to identify the modal
parameters of the output‐only data for structural health monitoring (SHM) that makes full use …