Rolling Bearing Fault Diagnosis under Variable Conditions Using Hilbert-Huang Transform and Singular Value Decomposition

Table 3

Elman neural network recognition results.

Sequence	State	Operating condition	Target output	Actual output of network
1	Normal	(1750 r/min, 2 HP)	(1 0 0 0)	0.993781	3.45𝐸−08	0.043759	0.001039
2	Inner-race fault	(1720 r/min, 3 HP)	(0 1 0 0)	0.0072	0.9910	0.0072	0.0070
3		(1750 r/min, 2 HP)	(0 1 0 0)	0.0067	0.9885	0.0078	0.0079
4		(1772 r/min, 1 HP)	(0 1 0 0)	2.94𝐸−06	0.999569	5.87𝐸−05	0.078958
5		(1797 r/min, 0 HP)	(0 1 0 0)	0.0067	0.9883	0.0078	0.0080
6	Outer-race fault	(1720 r/min, 3 HP)	(0 0 1 0)	0.000413	0.100543	0.990864	6𝐸−11
7		(1750 r/min, 2 HP)	(0 0 1 0)	7.241𝑒−05	0.0155	0.9845	0.0128
8		(1772 r/min, 1 HP)	(0 0 1 0)	0.000264	0.007905	0.997584	0.000573
9		(1797 r/min, 0 HP)	(0 0 1 0)	5.880𝑒−05	0.0109	0.9900	0.0112
10	Rolling element fault	(1720 r/min, 3 HP)	(0 0 0 1)	0.0051	0.000405	0.0109	0.9866
11		(1750 r/min, 2 HP)	(0 0 0 1)	0.0051	0.000236	0.0117	0.9898
12		(1772 r/min, 1 HP)	(0 0 0 1)	0.0064	0.000245	0.0100	0.9899
13		(1797 r/min, 0 HP)	(0 0 0 1)	0.0100	0.000583	0.0072	0.9815