Abstract The first International Symposium on Dynamics, Monitoring and Diagnostics was
held in Chongqing, China, in April 2022. The Symposium, which was attended both virtually …

Condition-based monitoring for critical assets is reliant on the quality of the indicators used
for condition inference. These indicators must be sensitive to the development of faults …

Feature extraction from vibration signals plays a vital role in rotating machinery fault
diagnosis. The noise contained in the signals will interfere with the fault feature extraction …

This chapter explores the role of digital twins to support decision-making in managing
physical assets. In particular, the roles of physics-based digital twins and data-driven digital …

Industry 5.0 advocates for a sustainable industry, particularly in terms of energy. One of the
most fundamental elements of comprehension is knowing when the systems are operated …

This work introduces a new condition monitoring approach for complex systems based on a
standardized latent space representation. Latent variable models such as the variational …

In recent years, process monitoring structures utilize big data analytics to offer a more
realistic interpretation of systems. Nevertheless, managing large datasets and providing …

Latent variable models (LVMs) are commonly used to capture the underlying dependencies,
patterns, and hidden structure in observed data. Source duplication is a by-product of the …

Les éoliennes sont une des solutions technologiques clés pour la transition énergétique.
Une augmentation significative de la puissance éolienne installée dans le monde au cours …

Early and accurate detection of rolling element bearing faults in rotating machinery is
important for minimizing production downtime and reducing unnecessary preventative …