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Application of Adaptive Neuro Fuzzy Inference System to the Partial Discharge Pattern Recognition

机译:自适应神经模糊推理系统在局部放电模式识别中的应用

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摘要

The application of adaptive neuro fuzzy inference system (ANF1S) to the partial discharge (PD) pattern recognition is presented in this paper. Four types of defect models are made according to the main reason of insulation failures in real power system. Experiments are carried out to acquire the sample data, from which eight statistical features are extracted to construct the ANFIS. Different characteristics of the proposed defect models are compared based on the extracted features. Then the ANFIS is trained by characteristic features. Testing samples are utilized to validate the performance of the recognition system. The result shows that ANFIS reaches a successful recognition rate in the application of PD pattern classification.
机译:提出了自适应神经模糊推理系统(ANF1S)在局部放电(PD)模式识别中的应用。根据实际电力系统中绝缘故障的主要原因,建立了四种缺陷模型。进行实验以获取样本数据,从中提取八个统计特征以构建ANFIS。基于提取的特征,对所提出的缺陷模型的不同特征进行比较。然后,通过特征训练ANFIS。利用测试样本来验证识别系统的性能。结果表明,ANFIS在PD模式分类中的应用达到了成功的识别率。

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