A kind of
quantum echo state network model construction method for aero-engine fault early warning, first, the
time series data of aero-engine is quantized;Then,
quantum state data is used as the input of the first layer
quantum network, after the action of quantum
recursion circuit, the probabilistic output is obtained by
quantum measurement, and then is transmitted to the reserve
pool of the second layer
echo state network to obtain a high-dimensional
intermediate state;Finally, the output layer weight matrix can be obtained by least square method only once calculation, and the network training is completed.The trained quantum
echo state network model is applied to aero-engine fault prediction, and the engine operation
state prediction data with high accuracy at future time is given.The present application uses quantum controlled non-gate to realize entangled state, and approximately represents the
coupling relationship that may exist between original input data, and quantum rotation gate is set as adjustable parameter of the first layer
quantum network, so that the distribution of data can be adjusted;And echo state
network layer can play the advantages of fast calculation, and one-step training can complete the calculation of final model.