System health management is of upmost importance with today's sensor integrated systems
where a constant stream of data is available to feed information about a system's health …

Generative models have been applied in many fields and can be evaluated with many
methods. In the evaluation of generative models, the proper evaluation metric varies with the …

In recent years, deep learning has become an emerging research orientation in the field of
intelligent monitoring and fault diagnosis for industry equipment. Generally, the success of …

With the availability of cheaper multisensor suites, one has access to massive and
multidimensional datasets that can and should be used for fault diagnosis. However, from a …

With the rapid development of modern industry and artificial intelligence technology, fault
diagnosis technology has become more automated and intelligent. The deep learning …

Effective fault diagnosis of rotating machinery plays a pretty important role in the enhanced
reliability and improved safety of industrial informatics applications. Although traditional …

In autonomous and robotic systems, the importance of Fault Detection and Diagnosis (FDD)
technologies has increasingly grown as these systems find widespread application across …

Fault diagnosis is a crucial technology for ensuring the reliable and efficient operation of
industrial systems. With the advancement of industrial informatization and intelligence, fault …

Effective condition monitoring is vital for maintaining the reliability of complex systems. One
of the most laborious aspects of training deep learning models for fault diagnosis in …

Fault diagnosis plays the increasingly vital role to guarantee the machine reliability in the
industrial enterprise. Among all the solutions, deep learning (DL) methods have achieved …