The invention discloses a stacked noise reduction self-coding motor fault diagnosis method based on vibration and current signals, and the method comprises the following steps: 1, obtaining the time domain signals of the vibration and current of the motor during different faults, carrying out the preprocessing, and taking the processed signals as network input; 2, determining network parameters; 3, carrying out the layer by layer training, taking a hiding layer of an AE (Auto encoder) at an upper level as the input layer of an AE at a lower level, thereby obtaining a final feature code which is used for training a Softmax network; 4, carrying out the fine tuning of the whole network, judging whether the expected precision is met or not: finishing the training of the network if the expectedprecision is met, or else adjusting the network parameters, and repeatedly carrying out the step 3; 5, finishing the network construction. According to the invention, the multilayer SDAE network is constructed, and the vibration frequency domain signal and the current time domain signal are combined as the input. The SDAE network and a classifier are sequentially trained, and the supervised finetuning of the whole network is carried, thereby achieving the precise diagnosis of the fault of the motor.