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A Novel Approach to Fault Classification of Power Transmission Lines Using Singular Value Decomposition and Fuzzy Reasoning Spiking Neural P Systems

机译:基于奇异值分解和模糊推理的神经P系统的输电线路故障分类的新方法

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摘要

A novel approach for classifying different types of faults occurring in power transmission lines is proposed by considering wavelet transform, singular value decomposition and Fuzzy Reasoning Spiking Neural P Systems (FRSNPS). In this approach, singular value decomposition in wavelet domain is used to extract features of fault current components recorded from power transmission lines; FRSNPS is applied to build the fault type classification model. Several cases with different fault types in power transmission lines are considered in the simulation experiments to verify the effectiveness of the proposed approach. The robustness to noise and to parameters of power transmission lines is also discussed.
机译:通过考虑小波变换,奇异值分解和模糊推理尖峰神经P系统(FRSNPS),提出了一种用于分类输电线路中不同类型故障的新方法。该方法利用小波域奇异值分解提取输电线路记录的故障电流分量特征。应用FRSNPS建立故障类型分类模型。在仿真实验中考虑了几种输电线路故障类型不同的情况,以验证所提方法的有效性。还讨论了对噪声和输电线路参数的鲁棒性。

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