Neural network technique for the joint time-frequency analysis of distorted signal

被引:10
作者
Bertoluzzo, M [1 ]
Buja, GS
Castellan, S
Fiorentin, P
机构
[1] Univ Padua, Dept Elect Engn, I-35131 Padua, Italy
[2] Univ Trieste, Dept Elect Elect & Comp Sci, I-34127 Trieste, Italy
关键词
distorted signal; harmonic analysis; neural network (NN) application;
D O I
10.1109/TIE.2003.819577
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nonstationary distorted signals need to be analyzed in both the time and frequency domains to determine their characteristics. In this paper, a technique based on a neural network (NN) is presented which has the merit of providing such an analysis in real time. After arranging a suitable NN, the algorithm utilized to carry out the analysis is illustrated. Then, expressions assessing the dynamic behavior and the steady-state accuracy of the technique are derived. From the expressions, the influence of the NN parameters on the technique performance is readily recognized. As an example, the technique is applied to the analysis of the time evolution of the current harmonics absorbed by a diode rectifier and the results are compared with those obtained by the short-time Fourier transform.
引用
收藏
页码:1109 / 1115
页数:7
相关论文
共 6 条
[1]   HARMONIC SOURCE MONITORING AND IDENTIFICATION USING NEURAL NETWORKS [J].
HARTANA, RK ;
RICHARDS, GG .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1990, 5 (04) :1098-1104
[2]   Neural network-based estimation of power electronic waveforms [J].
Kim, MH ;
Simoes, MG ;
Bose, BK .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 1996, 11 (02) :383-389
[3]   Real-time frequency and harmonic evaluation using artificial neural networks [J].
Lai, LL ;
Chan, WL ;
Tse, CT ;
So, ATP .
IEEE TRANSACTIONS ON POWER DELIVERY, 1999, 14 (01) :52-59
[4]  
MAMMONE RJ, 1990, NEURAL NETWORK THEOR
[5]  
Qian S., 1996, JOINT TIME FREQUENCY
[6]  
Zurada J., 1992, INTRO ARTIFICIAL NEU