A kind of
permanent magnet synchronous motor bearing fault diagnosis method based on motor
current analysis method, first acquisition
permanent magnet synchronous motor stator U, V phase current
signal, calculate W phase current;Three-phase current is obtained by
space vector dimension reduction two-phase current under rectangular coordinate
system, and two-phase current is carried out vector normalization
processing;Based on the
mechanism of action of bearing fault to current
signal and the characteristics of current
signal, the signal after
space vector dimension reduction is carried out variation
modal decomposition, the
approximate entropy of
modal component is calculated and the
feature matrix is formed;The improved standard
artificial bee colony algorithm makes the bee colony type mutually transform according to the optimal solution, and changes the bee colony initialization
population generation rule, the optimal classification model is obtained by using the optimized adaptive variable type
algorithm to optimize
machine learning
model parameter;Using optimal model, the
test set in sample set is classified according to fault type, and compared with
label to obtain
test set accuracy rate;The present application has the advantages of high accuracy, high diagnostic efficiency and the like.