To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

Nondestructive testing and evaluation (NDT&E) are commonly used in the industry for their
ability to identify damage and assess material conditions. Ultrasonic testing (UT) is one of …

Composite materials are those formed by combining two or more different materials to take
advantage of the best characteristics of each one. However, due to this heterogeneity …

Quantitatively and accurately monitoring the damage to composites is critical for estimating
the remaining life of structures and determining whether maintenance is essential. This …

Computational models are crucial in applied science and engineering, offering valuable
insights on the behavior of strutures and mechanical systems. However, their effectiveness …

Fibre ropes with the latest technology have emerged as an appealing alternative to steel
ropes for offshore industries due to their lightweight and high tensile strength. At the same …

Machine learning methods used in Structural Health Monitoring applications still have
generalization difficulties among structures, even when structures are nominally and …

This paper presents a feasibility study on damage size quantification throughout the damage
expansion procedure using the integral differential method based on the developed …

The success of detecting damage robustly relies on the availability of long periods of past
data covering multiple weather scenarios and on the information contained in the data used …

This study presents a novel approach for real-time vision-based structural health monitoring,
focusing on evaluating the deformation state of lattice structures. The structures are …