The invention discloses a multi-source
distillation-migration mechanical fault intelligent diagnosis method based on high-order moment matching, and the method comprises the steps: building a multi-
source data set through the operation data collected from a plurality of
mechanical devices, carrying out the preprocessing, and dividing the multi-
source data set into a source domain
data set, a target domain training
data set, and a target domain
test data set; constructing a multi-source
distillation-transfer
learning network model based on high-order moment matching, and performing high-order moment matching, maximum classifier difference and multi-source
distillation training by using the source domain
data set and the target domain training data set; and taking the target domain
test data set as
test input, and synthesizing outputs of the plurality of classifiers by using an
adaptive weighting strategy to complete cross-domain fault diagnosis. According to the method, features of a source domain and a target domain are aligned at domain and category levels by utilizing multi-
source data, the classification capability of the model on target samples is improved through multi-source distillation, and
adaptive weighting is provided to integrate diagnosis results, so that the problem that the performance of a traditional method is reduced in cross-domain diagnosis is solved, and the performance of a deep model is greatly improved.