Abstract
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.
Original language | English |
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Article number | 2761 |
Number of pages | 19 |
Journal | Applied Sciences |
Volume | 11 |
Issue number | 6 |
DOIs | |
Publication status | Published - 19 Mar 2021 |
MoE publication type | A2 Review article, Literature review, Systematic review |
Keywords
- fault diagnostics
- machine learning
- artificial intellegence
- pattern recognition
- neural networks