By means of an artificial neural network (ANN) model, higher measurement accuracy of integer harmonics can be obtained. Combining the windowed fast Fourier transform (FFT) algorithm with the improved ANN model, we present a new precise algorithm for non|integer harmonics analysis. According to the result obtained from the Hanning|windowed FFT algorithm, we choose the initial values of orders of harmonics for the neural network. Through such processing, the time of iterations is shortened and the convergence rate of neural network is raised thereby. The simulation results show that close non|integer harmonics can be separated from a signal with higher accuracy and better real|time by using the algorithm presented in the paper. Combining the windowed fast Fourier transform (FFT) algorithm with the improved ANN model, we present a new precise algorithm for non | integer harmonics analysis. According to the result obtained from the Hanning | windowed FFT algorithm, we choose the initial values ​​of orders of harmonics for the neural network. raised thereby. The simulation results show close close non | integer harmonics can be separated from a signal with higher accuracy and better real | time by using the algorithm presented in the paper.