Nowadays, intelligent models can correctly detect faults by analysing signals from rotating machinery. However, most of the studies are run in controlled environments and performance industrial real-world is not yet fully validated. Hence, a suitable tool to implement fault diagnosers transfer learning, this topic under development challenges persist. This paper proposes framework for creating ...

In recent industrial applications, machine learning technology is proving useful in preventing equipment failures advance through early failure diagnosis. particular, we show that different domains can be linked adversarial with data available working conditions to facilitate the training of model, as it impractical acquire for all real-world applications. Nevertheless, initial a difficult prob...

Active magnetic bearings (AMBs) have led to great progress in the field of rotating machinery due their many advantages, such as non-contact and non-lubrication properties. As key component an AMB actuator, switching power amplifier has important impact on performance machinery. In this paper, topologies amplifiers for AMBs are introduced. The traditional half-bridge topology two newly proposed...