Synergistic Signal Denoising for Multimodal Time Series of Structure Vibration

Structural health monitoring (SHM) has emerged as a vital field of research, geared towards preserving the longevity and safety of civil infrastructure [1]. A critical component of SHM is the analysis of vibration time series data, which offers insights into the behavior, health, and performance of structures [2]. As infrastructure, especially in urban regions, is subject to a myriad of dynamic forces--ranging from wind to traffic loads - it becomes pivotal to extract clear and meaningful data from the complex vibration signatures that these forces induce. However, one of the significant challenges plaguing SHM practitioners is the interference of noise in these vibration signals, which can distort interpretations and lead to unreliable conclusions. The dynamic response of structures is often manifested as multimodal vibrations, meaning multiple modes or patterns of vibration coexist. These modes, each characterized by its frequency and shape, provide a fingerprint of the structure's health and dynamic properties.