Bearing fault diagnosis method and device based on joint distribution adaptation and storage medium

The invention discloses a bearing fault diagnosis method and device based on improved joint distribution adaptation and a storage medium, and relates to the field of bearing fault diagnosis methods. The method comprises the following steps: step 1, establishing a source domain feature set and a target domain feature set according to bearing vibration signals; 2, establishing a source domain feature sample set and a target domain feature sample set after constructing a feature mobility quantitative index; 3, manifold subspace learning is carried out on the source domain feature sample set, and a source domain feature subset and a feature mapping matrix are obtained; converting the target domain feature sample set into a target domain feature subset based on the feature mapping matrix, and then carrying out joint distribution adaptation algorithm solution to obtain a source domain feature set and a target domain feature set of distribution adaptation; 4, training a classifier by using the source domain feature