Abstract:

Aimed at the problem of aeroengine condition monitoring, wavelet process neural networks (WPNN) model is proposed. Its hidden layer and output layer are composed of process neuron and hidden layer function consists of wavelet function. The network not only has the capability to deal with continuous input signals, but also has the time-frequency local property of wavelet analysis. The learning ability of WPNN is better and the predictive precision is high.

Key words: process , neuron,  , wavelet , process , neural , networks,  , learning , algorithm,  , condition , monitoring , of , aeroengine