Context: Cyber–physical systems present a challenge to testers, bringing complexity and
scale to safety-critical and collaborative environments. Digital twins enhance these systems …

This work aims to provide a broad overview of computational techniques belonging to the
area of artificial intelligence tailored for identification of nonlinear dynamical systems. Both …

This paper presents a review of the state of the art for digital twins in the application domain
of engineering dynamics. The focus on applications in dynamics is because:(i) they offer …

The use of machine learning in structural health monitoring is becoming more common, as
many of the inherent tasks (such as regression and classification) in developing condition …

This paper describes a time-evolving digital twin and its application to a proof-of-concept
engineering dynamics example. In this work, the digital twin is constructed by combining …

In the field of structural health monitoring (SHM), the acquisition of acoustic emissions to
localise damage sources has emerged as a popular approach. Despite recent advances …

Fault detection based on data from the supervisory control and data acquisition (SCADA)
system, which has been installed in most MW-scale wind turbines, has brought significant …

This paper presents a new Bayesian approach to equation discovery–combined structure
detection and parameter estimation–for system identification (SI) in nonlinear structural …

Jointed structures are ubiquitous constituents of engineering systems; however, their
dynamic properties (eg, natural frequencies and damping ratios) are challenging to identify …

The quantification of wave loading on offshore structures and components is a crucial
element in the assessment of their useful remaining life. In many applications the well …