On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …

Prognostics and health management (PHM) plays a constructive role in the equipment's
entire life health service. It has long benefited from intensive research into physics modeling …

Capturing sufficient and balanced data for intelligent fault diagnosis is significantly
consumptive in practice. It is tricky and demand-oriented to identify faults accurately and …

As one of the key components in rotating machinery, rolling bearings can affect the running
state of equipment and even cause huge damage. Therefore, various methods have been …

Adaptive extraction of concerned components (CC) from mixed frequency components
remains to be a challenging topic in various research domains. Most existing adaptive mode …

Building materials machinery equipment play an important role in the production of cement,
brick and tile, glass and other building materials, which are high energy consumption …

Dynamic health monitoring (DHM) and performance degradation assessment (PDA) is
critical for mechanical bearings throughout their long in-service life. For this issue, it is …

Difference mode decomposition (DMD) is an effective technique for accurately separating a
signal into fault, natural, and noise components. However, DMD relies on the assumption …

Artificial intelligence-based rotating machine health monitoring and diagnosis methods often
encounter problems, such as a lack of faulty samples. Although the simulation-based digital …

Abstract Machine condition monitoring is an emerging research domain to use monitoring
data to monitor machine conditions and prevent unexpected machine failures. In our …