A New Deep Convolutional Domain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions

Table 3

Experimental result of CWRU.

Method	CNN	TCA	DDC	DCDAN-WDC	DCDAN
N1 ⟶ N2	85.76	87.33	90.25	97.25	99.23
N1 ⟶ N3	87.45	87.90	90.06	98.23	99.74
N1 ⟶ N4	80.50	86.56	92.33	93.54	98.87
N2 ⟶ N1	88.32	83.28	88.79	97.58	99.64
N2 ⟶ N3	91.25	90.35	93.05	98.54	99.48
N2 ⟶ N4	73.12	75.26	86.37	96.25	99.79
N3 ⟶ N1	80.37	81.76	87.43	95.35	99.52
N3 ⟶ N2	86.25	80.57	88.56	95.83	98.92
N3 ⟶ N4	86.35	88.43	93.64	98.54	99.69
N4 ⟶ N1	79.95	81.22	88.32	95.88	99.23
N4 ⟶ N2	76.04	78.24	82.67	95.93	98.33
N4 ⟶ N3	79.17	86.30	84.19	95.62	99.75
Average	82.88	83.93	88.81	96.55	99.35