The present paper describes a measurement setup and related prediction of the electrical impedance rolling bearings using machine learning algorithms. bearing is expected to be key in determining state health bearing, which an essential component almost all machines. In previous publications, determination has already been advanced analytical methods. Despite improvements accuracy achieved with...

This paper presents a novel multimodal approach to automatically detect learner uncertainty through the integration of multiple sensors. An acquisition protocol was established for the recording of learner electrical brain activity and physiological signals while interacting with a problem solving system specifically designed for uncertainty elicitation. Data were collected from 38 subjects usi...

Machine-learning algorithms have recently been applied to electrical power problems due to their potential to reduce waste and improve electrical grid reliability, but deployment of existing research is hampered by unrealistic assumptions. My thesis focuses on overcoming these assumptions. Autonomous agents have enormous potential to reduce electrical waste and improve reliability of the power ...

The wind turbine converts the wind energy into electrical energy, wherein the electrical machines are coupled with wind turbines for this conversion. The electrical machines are liable to meet with faults, but to regain the system reliability the faults should be detected earlier. According to studies of electrical power research institute (EPRI) most of the faults in electrical motors are crea...