The invention discloses a network fault diagnosis method based on a wavelet neural network. The method comprises the following steps: S1, obtaining network data in a fault state and a normal state; S2, carrying out numeralization and normalization processing on the network fault data, and carrying out data dimension reduction by adopting a PCA dimension reduction algorithm; S3, creating a wavelet neural network model, selecting an improved grey wolf optimization algorithm, and taking optimized parameters as parameters of the wavelet neural network model; then taking the network fault data processed in the second step as input, adding momentum factors when parameters are reversely adjusted, and establishing a network fault diagnosis model through continuous training; S4, inputting real-time network state data, and judging whether the network has a fault; and S5, outputting a network fault diagnosis result and a fault category. The momentum factor is introduced, so that the local optimization capacity of the diagnosis model is improved; an improved grey wolf algorithm is adopted, initial parameters of a fault diagnosis model are optimized, and the randomness of initial parameter selection is avoided.