Rotary machine residual life prediction method of multi-layer bidirectional gating cycle unit network

The invention discloses a rotary machine residual life prediction method of a multi-layer bidirectional gating cycle unit network. The rotary machine residual life prediction method comprises the following steps: acquiring a vibration signal; constructing health indexes; constructing a network training set; constructing a multi-layer bidirectional gating circulation unit network; training a multi-layer bidirectional gating cycle unit network; and carrying out network testing, residual life estimation and confidence interval acquisition; and performing residual life prediction evaluation. According to the rotary machine residual life prediction method, the advantages of strong feature extraction capability of deep learning are combined, and regression prediction is carried out by utilizinga bidirectional gated cycle unit neural network, and the confidence interval of the residual life is obtained through a Bootstrap method. Aiming at the problems that the model precision is sensitive to the value of the learni