Prognostic and Health Management (PHM) systems are some of the main protagonists of
the Industry 4.0 revolution. Efficiently detecting whether an industrial component has …

Deep learning applications have been thriving over the last decade in many different
domains, including computer vision and natural language understanding. The drivers for the …

In industrial applications, anomaly detectors are trained to raise alarms when measured
samples deviate from the training data distribution. The samples used to train the model …

Abstract Prognostic and systems Health Management (PHM) is an integral part of a system.
It is used for solving reliability problems that often manifest due to complexities in design …

The traditional paradigm for develo** machine prognostics usually relies on
generalization from data acquired in experiments under controlled conditions prior to …

Population-based structural health monitoring (PBSHM) offers a new viewpoint for structural
health monitoring (SHM), allowing diagnostic information to be shared across populations of …

Complex industrial systems are continuously monitored by a large number of
heterogeneous sensors. The diversity of their operating conditions and the possible fault …

Decarbonization of marine transport is a key global issue, with the carbon emissions of
international ship** projected to increase 23% to 1090 million tonnes by 2035 in …

Condition monitoring and predictive maintenance enable to focus on the operating and
degradation conditions of a specific asset and designing maintenance policies that are …

A typical district heating (DH) network consists of hundreds, sometimes thousands, of
substations. In the absence of a well-understood prior model or data labels about each …