The invention relates to the technical field of intelligent diagnosis, and provides a
machine tool bearing diagnosis method and
system based on improved SMOTE. According to the method, for the problem of
data imbalance caused by scarcity of fault samples in
bearing vibration signals, the vibration signals are obtained and processed into a feature sample set; identifying
minority class fault samples, calculating weight values according to sample distribution of the
minority class fault samples in the feature space, adaptively determining a generation area for each sample based on the weight values, and synthesizing new samples to balance data; and finally using the balanced sample set to
train a fault diagnosis model for classification. According to the bearing fault diagnosis method, through weight-driven adaptive region adjustment, the classification boundary is effectively protected while the sample diversity is enhanced, the accuracy of bearing fault diagnosis is improved, and the missing report rate of
minority class faults is effectively reduced.