Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

Bridges play a crucial role in modern societies, regardless of their culture, geographical
location, or economic development. The safest, economical, and most resilient bridges are …

Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …

Offshore Wind has become the most profitable renewable energy source due to the
remarkable development it has experienced in Europe over the last decade. In this paper, a …

Anomaly detection is an important problem that has been researched within diverse
research areas and application domains. Many anomaly detection techniques have been …

Novelty detection is the identification of new or unknown data or signal that a machine
learning system is not aware of during training. Novelty detection is one of the fundamental …

The difficulty of achieving controlled input has led to the development of new output-only
structural health monitoring (SHM) approaches. Without measuring the input or assuming a …

Stated in its most basic form, the objective of structural health monitoring is to ascertain if
damage is present or not based on measured dynamic or static characteristics of a system to …

Novelty detection is the identification of new or unknown data or signal that a machine
learning system is not aware of during training. In this paper we focus on neural network …

Based on the extensive literature that has developed on structural health monitoring over the
last 20 years, it can be argued that this field has matured to the point where several …