A review of the fault diagnostic techniques based on machine is presented in this paper. As
the world is moving towards industry 4.0 standards, the problems of limited computational …

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 …

Thanks to digitization of industrial assets in fleets, the ambitious goal of transferring fault
diagnosis models from one machine to the other has raised great interest. Solving these …

Rotating machinery often operates under varying speed conditions. Fault detection is
necessary to prevent sudden failures and enable condition-based maintenance. Existing …

Prognostics and health management (PHM) is an engineering approach dealing with the
diagnosis, prognosis, and management of the health state of engineering systems. Methods …

One of the challenges that data-based gas path component monitoring systems are facing,
is the poor performance in those operational conditions that are not considered in the …

The modern industrial environment is equip** myriads of smart manufacturing machines
where the state of each device can be monitored continuously. Such monitoring can help …

In the literature pertaining to condition-based maintenance using machine learning, the
class of unsupervised approaches has yet to be fully explored. In particular, the topics of …

In the Industrial Internet of Things (IIoT), condition monitoring sensor signals from complex
systems often exhibit nonlinear and stochastic spatial-temporal dynamics under varying …

Time series data generated by manufacturing machines during processing is widely used in
mass part production to assess if processes run without errors. Systems that make use of this …