Improved Algorithm for Non-integer Harmonics Analysis Based on FFT Algorithm and Neural Network

By using an artificial neural network(ANN) model,high measurement accuracy of integer harmonics can be obtained.Combining the windowed fast Fourier transform(FFT) algorithm with the improved ANN model,the paper provides an improved algorithm for analysis of non-integer harmonics in electric power systems.Firstly,the Hanning-windowed FFT algorithm processes the sampled signal.By this time,the number of harmonics and the orders of harmonics are obtained.Secondly,choose the number of neural nodes according to the number of harmonics.Thirdly,choose the initial values of orders of harmonics according to the result obtained from the Hanning-windowed FFT algorithm.Moreover,an adaptive algorithm for the adjusting step of the order of harmonic is presented.Finally,by using the improved linear ANN model obtained in the paper,non-integer harmonics can be detected precisely.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 improved algorithm presented.