DETECTION AND CLASSIFICATION OF POWER QUALITY DISTURBANCE WAVEFORM USING MRA BASED MODIFIED WAVELET TRANSFROM AND NEURAL NETWORKS

被引：12

作者：

Chandrasekar, Perumal ^{[1
]}

Kamaraj, Vijayarajan ^{[1
]}

机构：

[1] Pk Coll Engn & Technol, Dept Elect & Elect Engn, Coimbatore 641659, Tamil Nadu, India

来源：

JOURNAL OF ELECTRICAL ENGINEERING-ELEKTROTECHNICKY CASOPIS | 2010年 / 61卷 / 04期

关键词：

modified wavelet transforms; power quality disturbances; AM; detection and classification; ANN;

D O I：

10.2478/v10187-010-0033-4

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, the modified wavelet based artificial neural network (ANN) is implemented and tested for power signal disturbances. The power signal is decomposed by using modified wavelet transform and the classification is carried by using ANN. Discrete modified wavelet transforms based signal decomposition technique is integrated with the back propagation artificial neural network model is proposed. Varieties of power quality events including voltage sag, swell, momentary interruption, harmonics, transient oscillation and voltage fluctuation are used to test the performance of the proposed approach. The simulation is carried out by using MATLAB software. The simulation results show that the proposed scheme offers superior detection and classification compared to the conventional approaches.

引用

页码：235 / 240

页数：6

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