Rotating machine fault diagnosis method and system

The invention discloses a rotating machine fault diagnosis method and system, and belongs to the technical field of fault diagnosis, and the method comprises the steps: converting a vibration signal corresponding to a rotating machine fault sample into an RGB image; constructing a diagnosis model, wherein the diagnosis model comprises four SDTA encoders and a softmax classifier which are connected in sequence; each STDA encoder comprises a lower sampling layer, a convolution encoder and a separation depth transpose attention encoder; a loss function is constructed, transfer learning is carried out by adjusting loss function weights of different domains, and a minimized cross entropy loss function is obtained; using the training set and the minimum cross entropy loss function to train the diagnosis model; and obtaining an original vibration signal of the rotating machine to be diagnosed, converting the original vibration signal into an RGB image, inputting the RGB image into the trained diagnosis model, and ou