Turbofan engine remaining service life prediction method based on improved stacked sparse auto-encoder and attention echo state network
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[0044] Refer figure 1 A method based on a sparse improved stackable turbofan engine from the encoder and the state of the network echo attention remaining service life prediction method, comprising the steps of:
[0045] 1) Data selection to form an original data set for the sensor data generated by the acquired engine over time. Each data sample contains a number of i-th engine environment, the running time from the beginning to now, and the operation setting information of the sensor, wherein, i denotes the i th environment, followed by the data of the original data set 3sigma noise reduction and normalization, to eliminate the gross error criterion 3sigma measurement data, i.e., data distribution is almost concentrated in the (μ-3σ, μ + 3σ) interval, the ratio 99.73%, the proportion of the data exceeds the range of 0.27 %, coarse error data belonging to this part is considered to be noise original data to eliminate noise in this part of the process data, the data size of the n...
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