Structural Health Monitoring (SHM) of civil structures has been constantly evolving with
novel methods, advancements in data science, and more accessible technology to address …

The field of structural health monitoring (SHM) has gained significant attention from
academia and industry, particularly in the realm of damage detection. This approach allows …

With the advancement of deep learning, data-driven structural damage identification (SDI)
has shown considerable development. However, collecting vibration signals related to …

Track geometry is one of the critical indicators of railway tracks' condition which requires
continuous monitoring and maintenance over time. In this paper, a novel artificial …

The advances in data science in the last few decades have benefitted many other fields,
including Structural Health Monitoring (SHM). Artificial Intelligence (AI), such as Machine …

Condition assessment of civil engineering structures has been an active research area due
to growing concerns over the safety of aged as well as new civil structures. Utilization of …

In this paper, we delve into the evolving landscape of vibration-based structural damage
detection (SDD) methodologies, emphasizing the pivotal role civil structures play in society's …

The present work offers a comprehensive overview of methods related to condition
assessment of bridges through Structural Health Monitoring (SHM) procedures, with a …

The use of deep generative models (DGMs) such as variational autoencoders,
autoregressive models, flow-based models, energy-based models, generative adversarial …

Gathering properly labeled, adequately rich, and case-specific data for successfully training
a purely data-driven or hybrid model for structural health monitoring (SHM) applications is a …