| 基于小波神经网络局部放电模式识别方法的实验研究 |
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| 引用本文： | 阳国庆,郑殿春,孙学勇. 基于小波神经网络局部放电模式识别方法的实验研究[J]. 哈尔滨理工大学学报, 2005, 10(5): 98-101 |
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| 作者姓名： | 阳国庆 郑殿春 孙学勇 |
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| 作者单位： | 哈尔滨理工大学电气与电子工程学院,黑龙江,哈尔滨,150040;江西省电力设计院,江西,南昌,330006 |
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| 基金项目： | 黑龙江省自然科学基金项目(E0303) |
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| 摘 要： | 针对局部放电信号频率的特点，在小波神经网络基础上，构造一个改进型小波神经网络，并把信号在小波基的不同尺度和位移上展开，得到信号在不同尺度下的小波细节系数，将其输入到该小波网络进行局部放电模式识别．实验仿真得出，识别的相对误差范围为0．1％-3．9％．
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| 关 键 词： | 局部放电 小波神经网络 模式识别 |
| 文章编号： | 1007-2683(2005)05-0098-04 |
| 修稿时间： | 2005-01-02 |
An Experiment Study of Partial Discharge Pattern Recognition Method Based on Wavelet Neural Networks |
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| YANG Guo-qing,ZHENG Dian-chun,SUN Xue-yong. An Experiment Study of Partial Discharge Pattern Recognition Method Based on Wavelet Neural Networks[J]. Journal of Harbin University of Science and Technology, 2005, 10(5): 98-101 |
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| Authors: | YANG Guo-qing ZHENG Dian-chun SUN Xue-yong |
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| Abstract: | Considering the frequency characteristic of the partial discharge signal, on the basis of the wavelet neural network, an improved wavelet neural network is constructed. Signals are transformed by wavelet basis on different scales and displacements, and the wavelet detail coefficients are obtained under the different scales, finally sending them to the wavelet neural network to complete pattern recognition. Experiment simulations obtain the recognition relative errors range between 0. 1% and 3.9%. |
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| Keywords: | partial discharge wavelet neural network pattern recognition |
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