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电网技术 2009, 33(1) 31-36 DOI:
ISSN: 1000-3673 CN: 11-2410/TM |
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| 电力系统 |
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模式分类方法在电能质量扰动信号分类中的应用综述 |
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方群会 刘强5 周林 马永强 武剑 |
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输配电装备及系统安全与新技术国家重点实验室(重庆大学)，重庆市 沙坪坝区 400044 |
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摘要：
文中首先将电能质量扰动信号分类方法划分为模式分类法与非模式分类法，然后简要介绍了模式分类法，综述了人工神经网络、贝叶斯分类、专家系统、支持向量机几种典型的模式分类方法在电能质量扰动信号分类中的应用，对比分析了各种方法的利弊，并对现存的问题及以后的发展趋势进行了展望。 |
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关键词：
电能质量扰动
模式分类
人工神经网络(ANN)
贝叶斯分类
专家系统(ES)
支持向量机(SVM)
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A Survey on Application of Pattern Classification in Power Quality Disturbance Signals Classification |
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FANG Qun-hui LIU Qiang ZHOU Lin MA Yong-qiang WU Jian |
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State Key Laboratory of Power Transmission Equipment & System Security and New Technology
(Chongqing University)，Shapingba District，Chongqing 400044，China
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Abstract:
Firstly the classification methods for power quality disturbance signals are divided into two categories, namely, the pattern classification and the non-pattern classification; then the pattern classification method is presented concisely and the application of several typical pattern classification methods such as artificial neural network, Bayes classification, expert system and support vector machine in the classification of power quality disturbance signals is summarized. The advantages and disadvantages of these methods are compared and analyzed. The problems existing in power quality disturbance signals classification are pointed out and its development trend is prospected. |
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Keywords:
power quality disturbance
pattern classification
artificial neural network (ANN)
Bayes classification
expert system (ES)
support vector machine (SVM)
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收稿日期 2008-04-21 修回日期 1900-01-01 网络版发布日期 |
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DOI: |
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基金项目:
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通讯作者: 方群会 |
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作者简介: |
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作者Email: nerisa123@163.com |
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| 参考文献： |
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| 本刊中的类似文章 |
| 1．李 霖|杨洪耕|赵艳粉.基于二维离散平稳小波变换的短时电能质量扰动检测方法[J]. 电网技术, 2007,31(11): 49-53 |
| 2．易吉良 彭建春 .基于广义S变换的短时电能质量扰动信号分类[J]. 电网技术, 2009,33(5): 22-27 |
| 3．孔英会|车辚辚|苑津莎|安 静|刘云峰 .基于小波分解和数据挖掘中决策树算法的电能质量扰动识别方法[J]. 电网技术, 2007,31(23): 78-82 |
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