Power Disturbance Classifier Using Wavelet-Based Neural Network

Jae-Ho Choi; Hong-Kyun Kim; Jin-Mok Lee; Gyo-Bum Chung

Power Disturbance Classifier Using Wavelet-Based Neural Network

Vol. 6, No. 4, pp. 307-314, Oct. 2006

10.6113/JPE.2006.6.4.307

Power quality

Wavelet-based neural network

Power disurbance classifier

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Abstract

This paper presents a wavelet and neural network based technology for the monitoring and classification of various types of power quality (PQ) disturbances. Simultaneous and automatic detection and classification of PQ transients, is recommended, however these processes have not been thoroughly investigated so far. In this paper, the hardware and software of a power quality data acquisition system (PQDAS) is described. In this system, an auto-classifying system combines the properties of the wavelet transform with the advantages of a neural network. Additionally, to improve recognition rate, extraction technology is considered.

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Cite this article

[IEEE Style]

J. Choi, H. Kim, J. Lee, G. Chung, "Power Disturbance Classifier Using Wavelet-Based Neural Network," Journal of Power Electronics, vol. 6, no. 4, pp. 307-314, 2006. DOI: 10.6113/JPE.2006.6.4.307.

[ACM Style]

Jae-Ho Choi, Hong-Kyun Kim, Jin-Mok Lee, and Gyo-Bum Chung. 2006. Power Disturbance Classifier Using Wavelet-Based Neural Network. Journal of Power Electronics, 6, 4, (2006), 307-314. DOI: 10.6113/JPE.2006.6.4.307.