CAJ | 학술논문

变压器主要采用纵联差动保护，如何防止因涌流造成的误动已成为关键性问题。对于该问题，提出一种基于小波-DHNN识别励磁涌流的新的研究方案。利用小波变换对采样信号进行分析，得出励磁涌流的小波系数较内部故障电流有非常明显的差异，并且畸变特点伴随整个衰减过程。分析后的信号通过离散型Hopfield网络测试与识别，从而区分励磁涌流和内部故障电流。通过PSCAD和MATLAB仿真软件进行建模仿真，结果表明，该方法能可靠的识别励磁涌流和内部故障电流，并且准确率高达100%。
변압기주요채용종련차동보호，여하방지인용류조성적오동이성위관건성문제。대우해문제，제출일충기우소파-DHNN식별려자용류적신적연구방안。이용소파변환대채양신호진행분석，득출려자용류적소파계수교내부고장전류유비상명현적차이，병차기변특점반수정개쇠감과정。분석후적신호통과리산형Hopfield망락측시여식별，종이구분려자용류화내부고장전류。통과PSCAD화MATLAB방진연건진행건모방진，결과표명，해방법능가고적식별려자용류화내부고장전류，병차준학솔고체100%。
Transformers mainly take use of the longitudinal differential protection. It becomes a key issue to prevent malfunction caused by inrush current. For solve this problem, a new method is put forward to identify inrush current based on Wavelet-Discrete Hopfield neural network. Through the analysis of sampling signals by wavelet transform, it is found that the wavelet coefficients of the inrush current has a significant difference with the internal fault current, and the entire decay process is accompanied by distortion. Then the signals are tested and identified through Discrete Hopfield neural network, so as to distinguish excitation inrush current and internal fault current. PSCAD and MATLAB are used to accomplish the simulation models. The simulation results show that this method can distinguish inrush current and internal fault current reliably, and the accuracy rate is up to 100%.