Table 3 Dataset description for PRONOSTIA test bench.

From: Light convolutional neural network by neural architecture search and model pruning for bearing fault diagnosis and remaining useful life prediction

 

Condition 1

Condition 2

Condition 3

Datasets

\(\omega _s\) = 1800 rpm

\(\omega _s\) = 1650 rpm

\(\omega _s\) = 1500 rpm

\(F_r\) = 4000 N

\(F_r\) = 4200 N

\(F_r\) = 5000 N

Learning sets

Bearing 1_1

Bearing 2_1

Bearing 3_1

Test sets

Bearing 1_4

Bearing 2_4

Bearing 3_3

Bearing 1_5

Bearing 2_5

Bearing 1_6

Bearing 2_7

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