Trends and Challenges in Intelligent Condition Monitoring of Electrical Machines Using Machine Learning

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 power and available memory are decreasing day by day. A significant amount of data with a variety of faulty conditions of electrical machines working under different environments can be handled remotely using cloud computation. Moreover, the mathematical models of electrical machines can be utilized for the training of AI algorithms. This is true because the collection of big data is a challenging task for the industry and laboratory because of related limited resources. In this paper, some promising machine learning-based diagnostic techniques are presented in the perspective of their attributes.

Automated summary

This paper reviews the fault diagnostic techniques based on machine learning, highlighting the increasing capability of using cloud computation for processing faulty data and the potential of utilizing mathematical models of electrical machines for training AI algorithms in the era of industry 4.0.