引用本文: | 王宇,赵庆生,郭贺宏,等.离散正交S变换在电能质量扰动检测中的应用[J].电力系统保护与控制,2015,43(17):93-97.[点击复制] |
WANG Yu,ZHAO Qingsheng,GUO Hehong,et al.Application of discrete orthonormal S-transform in detection of power quality disturbances[J].Power System Protection and Control,2015,43(17):93-97[点击复制] |
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摘要: |
为了准确检测电能质量扰动信号的起止时刻,提出了基于离散正交S变换的扰动信号检测方法。在传统S变换的基础上,结合快速傅立叶变换对信号进行离散化处理,而后引入频带中心、频带宽度和时间变量对算法进行改进。构造基函数向量得到离散正交S变换系数矩阵,最终找到变换矩阵系数的突变点,从而检测出扰动信号的起止时刻。将该方法的分析结果与传统S变换的分析结果进行比较,结果表明离散正交S变换可准确有效地检测出扰动信号的起始和终止时刻。 |
关键词: 电能质量 离散正交S变换(DOST) 系数矩阵 基函数向量 扰动时刻检测 |
DOI:10.7667/j.issn.1674-3415.2015.17.015 |
投稿时间:2014-11-18修订日期:2015-01-27 |
基金项目:山西省回国留学人员科研资助项目(2010-34);国网山西省电力公司科技项目资助(晋电发展[2014]88号) |
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Application of discrete orthonormal S-transform in detection of power quality disturbances |
WANG Yu,ZHAO Qingsheng,GUO Hehong,WANG Zhenqi,ZHANG Xuejun |
(College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China;State Grid Jinzhong Electric Power Company, Jinzhong 030600, China;Shanxi University, Taiyuan 030006, China) |
Abstract: |
Power quality disturbance signal detection method based on discrete orthonormal S-tranform is proposed to detect the begin-end moment of disturbance signal accurately. Based on the traditional S-transform, this paper discretizes the signal combined with the fast Fourier transform, then introduces band center, frequency bandwidth and time variables to improve the algorithm, constructs the basis function vectors to obtain the discrete orthonormal S-tranform (DOST) coefficient matrix, finally detects the disturbance moment of the disturbance signal by finding the catastrophe point of the discrete orthonormal S-tranform coefficient matrix. The analysis results of this method are compared with that of traditional S-transform through simulation experiment. Results show that the DOST method can detect the begin-end moment of the disturbance signal precisely and effectively. |
Key words: power quality discrete orthonormal S-transform (DOST) coefficient matrix basis function vector disturbance moment detection |