| 引用本文: | 王成江,李 光.基于声发射技术的绝缘子放电识别用特征量研究[J].电力自动化设备,2012,32(7): |
| WANG Chengjiang,LI Guang.Characteristic analysis on acoustic emission signals of insulator discharge[J].Electric Power Automation Equipment,2012,32(7): |
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| 摘要: |
| 在进行绝缘子内部放电、污秽放电和电晕放电声发射试验的基础上，研究和寻找能够识别不同类型放电声发射波的特征量。根据不同类型的放电声发射波的差别，初选了15个特征量，分别反映了波形之间的差别和声发射波的变化及发展趋势。为减少初选特征量的信息重叠和冗余，在保证信息量的基础上，利用主成分分析法，把初选的15个特征量降维到3个互不相关的主成分指标，以减少识别计算量，加快识别速度。利用主成分分析后得到的新的主成分指标，可快速地进行放电类型识别和放电状态评价。 |
| 关键词: 绝缘子 放电 声发射 主成分分析 识别 |
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| Characteristic analysis on acoustic emission signals of insulator discharge |
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WANG Chengjiang, LI Guang
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School of Engineering and Renewable Energy，China Three Gorges University，Yichang 443002，China
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| Abstract: |
| The acoustic emission waves of insulator internal discharge，filthy discharge and corona discharge are tested and their characteristic variables are studied，by which different discharge types could be identified. 15 characteristic variables are selected to reflect respectively the differences between waveforms and the trend of wave variation. With enough information，the principal component analysis is then used to cut down the 15 originally selected variables to 3 unrelated principal component indicators，which reduces the computational complexity and improves the speed of recognition. With the principal component indicators，the discharge type is quickly identified and the discharge status is evaluated. |
| Key words: electric insulators discharge acoustic emission principal component analysis identification |
