HVCB	High-voltage circuit breakers
DT	Decision tree algorithm
NB	Naive bayes algorithm
OCSVM	One class support vector Machine
BT	Bagger decision tree algorithm
RF	Random forest
OOB	Out of bagging
WPT	wavelet package transform
WTFE	wavelet time-frequency entropy
WTFER	wavelet time-frequency energy rate
Ei,j	energy in the i-th time and j-th frequency section
Pi,j	energy rate alone frequency direction
Qi,j	energy rate alone time direction
S	training sample set
X	test sample set
C i	i-th sample feature ∈ Rd,
d	feature space dimension
k	k-th feature in feature space
Li	i-th sample label (Fault type) ∈ R
Hj	j-th decision tree
T	collection of trees represent forest
N tree	number of tree in the forest
Sj oob	OOB data set in j-th decision tree
Sj,k oob	OOB data set that permuting k-th feature in Sjoob for j-th decision tree
Rj oob	number of correct classification in j-th decision tree with OOB data
Rj,k oob	number of correct classification in j-th decision tree for Sj,koob
Dk	important measure for k-th feature
δ	minimum feature space dimension
λ	reduce rate
RFm	m-th random forest model
E oob,m	error rate of OOB data in m-th random forest model