Mathematical Problems in Engineering / 2014 / Article / Tab 3

Research Article

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

Table 3

Elman neural network recognition results.

SequenceStateOperating conditionTarget outputActual output of network

1Normal(1750 r/min, 2 HP)(1 0 0 0)0.993781 0.0437590.001039

2Inner-race fault(1720 r/min, 3 HP)(0 1 0 0)0.00720.99100.00720.0070
3(1750 r/min, 2 HP)(0 1 0 0)0.00670.98850.00780.0079
4(1772 r/min, 1 HP)(0 1 0 0) 0.999569 0.078958
5(1797 r/min, 0 HP)(0 1 0 0)0.00670.98830.00780.0080

6Outer-race fault(1720 r/min, 3 HP)(0 0 1 0)0.0004130.1005430.990864
7(1750 r/min, 2 HP)(0 0 1 0) 0.01550.98450.0128
8(1772 r/min, 1 HP)(0 0 1 0)0.0002640.0079050.9975840.000573
9(1797 r/min, 0 HP)(0 0 1 0) 0.01090.99000.0112

10Rolling element fault(1720 r/min, 3 HP)(0 0 0 1)0.00510.0004050.01090.9866
11(1750 r/min, 2 HP)(0 0 0 1)0.00510.0002360.01170.9898
12(1772 r/min, 1 HP)(0 0 0 1)0.00640.0002450.01000.9899
13(1797 r/min, 0 HP)(0 0 0 1)0.01000.0005830.00720.9815