Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

Table 5

Performance of the MLPNN classifier.

Scheme	Number of neurons in hidden layer	All the 30 features as input			Features selected by FC as inputs
		Epochs	Training accuracy; (%)	Test accuracy; (%)	Epochs	Training accuracy; (%)	Test accuracy; (%)
s1	5	30	100	95.67	82	100.00	88.75
	10	35	100	92.67	78	100.00	89.75
s2	5	36	100	93.67	200	98.83	92.25
	10	47	100	94.67	63	100.00	89.25
s3	5	41	100	94.33	38	100.00	95.25
	10	61	100	90.33	163	100.00	90.50
s4	5	15	100	96.00	153	99.92	91.75
	10	42	100	94.00	102	100.00	86.50
s5	5	61	100	93.67	157	99.92	92.50
	10	182	100	86.00	92	100.00	88.00
s6	5	207	99.11	90.00	152	99.92	92.25
	10	80	100	87.33	143	100.00	89.25
s7	5	22	100	97.67	18	100.00	95.50
	10	52	100	92.33	124	100.00	91.25