A physical knowledge-based extreme learning machine approach to fault diagnosis of rolling element bearing from small datasets

Tianyu Liu
Tianyu Liu
Li Kou
Li Kou
Le Yang
Le Yang

UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers Virtual Event Mexico September, 2020, pp. 553-559, 2020.

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Abstract:

The learning-based methods have been widely applied to design a fault diagnosis model for rolling element bearing. However, the mainstream methods can only deal with the large training dataset, which is always violated in practical application. In this paper, we propose a physical knowledge-based hierarchical extreme learning machine(H-EL...More

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