Fault diagnosis of induction motors utilizing local binary pattern-based texture analysis

EURASIP Journal on Image and Video Processing

Table 3 Individual classification accuracy for each of the fault categories

Feature extraction method	Classification accuracy (%) for different fault categories
	AMIS	BRB	NOM	FBO	RUN	PMIS	PUN	BRS
LBP_8,1	100	100	100	100	100	100	100	100
${LBP}_{8, 1}^{u 2}$	100	100	83.33	100	100	100	100	100
${LBP}_{8, 1}^{ri}$	100	100	100	100	100	100	100	100
${LBP}_{8, 1}^{riu 2}$	91.67	100	100	100	100	100	100	100
CLBP_S _8,1_M _8,1	100	100	100	100	100	100	100	100
$CLBP_S_{8, 1}^{u 2}_M_{8, 1}^{u 2}$	100	100	91.67	100	100	100	100	100
$CLBP_S_{8, 1}^{ri}_M_{8, 1}^{ri}$	100	100	100	100	100	100	100	100
$CLBP_S_{8, 1}^{riu 2}_M_{8, 1}^{riu 2}$	100	100	100	100	100	100	100	100
SIFT	98.33	98.33	86.67	100	100	100	100	100
Wavelet variance	83.33	100	83.33	100	83.33	83.33	83.33	100
Wavelet cross-correlation	83.33	83.33	83.33	66.67	100	83.33	83.33	50