Chinese Journal of Mechanical Engineering

Table 5 Clustering results of rail head region defects

From: Internal Defects Detection Method of the Railway Track Based on Generalization Features Cluster Under Ultrasonic Images

		120 sets of data	300 sets of data	480 sets of data
Clustering center	Joints	[0.8132, 1.9165] [0.3324–0.3929]	[0.8646, 2.2438] [0.3388–0.3922]	[0.8695, 2.1739] [0.3366–0.3709]
Clustering center	Rail head flaws	[0.8132, 1.9165] [0.3324–0.3929]	[0.8646, 2.2438] [0.3388–0.3922]	[0.8695, 2.1739] [0.3366–0.3709]
Clustering center distance		2.3589	2.6879	2.6000
Number of positive samples		16	45	69
Number of negative samples		104	255	411
Correct clustering		114	287	461
Error clustering		6	13	19
Clustering accuracy (%)		95.00	95.67	96.04
DBI index		0.0816	0.0283	0.0521

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