Detection and Classification of Low-frequency Power Disturbances Using a Morphological Max-lifting Scheme

被引：0

作者：

Zhang, Y. ^{[1
]}

Ji, T. Y. ^{[1
]}

Li, M. S. ^{[1
]}

Wu, Q. H. ^{[1
,2
]}

机构：

[1] S China Univ Technol, Sch Elect Power Engn, Guangzhou 510641, Guangdong, Peoples R China

[2] Univ Liverpool, Dept Elect Engn & Elect, Liverpool L69 3GJ, Merseyside, England

来源：

2013 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2013年

关键词：

Mathematical morphology; max-lifting scheme; power quality; low-frequency disturbance; detection; classification;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents a morphological max-lifting scheme for the detection and classification of low-frequency power disturbances. In order to extract waveform features of low-frequency disturbances, the proposed scheme employs mathematical morphology (MM) for its advantage in noise removing and max-lifting for its ability of information preserving. Afterwards, two aided variables are constructed to assist the classification of low-frequency disturbances. A variety of low-frequency power disturbances have been included in simulation studies and simulation results have demonstrated the effectiveness and feasibility of the proposed scheme.

引用

页数：5

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