Research Article

Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition

Table 3

The detailed information of the second group dataset.

Bearing conditionDefect diameter (mm)Number of training samplesNumber of testing samplesClass label
3 hp3 hp (case 3)2 hp (case 4)

Normal02040401

Ball fault0.0072040402
0.0142040403
0.0212040404
0.0282040405

Inner race fault0.0072040406
0.0142040407
0.0212040408
0.0282040409

Outer race fault0.00720404010
0.01420404011
0.02120404012

Number of samples240480480