CAJ | 학술논문

提出了基于T-S模糊神经网络的电晕放电模式识别方法,设计制作了三类电晕放电实验模型,并从采集的电晕放电信号中提取最大值、最小值、均值及其分形维数作为网络的输入特征向量,根据特征向量维数、隶属度函数类型及隶属度函数个数对T-S模糊神经网络的拓扑结构进行分析,将输入神经元个数为4、隶属度函数层为3个高斯型函数的网络确定为电晕放电的模式识别网络,并对此类网络进行训练和测试,结果表明此网络用于电晕放电模式识别是有效的.
제출료기우T-S모호신경망락적전훈방전모식식별방법,설계제작료삼류전훈방전실험모형,병종채집적전훈방전신호중제취최대치、최소치、균치급기분형유수작위망락적수입특정향량,근거특정향량유수、대속도함수류형급대속도함수개수대T-S모호신경망락적탁복결구진행분석,장수입신경원개수위4、대속도함수층위3개고사형함수적망락학정위전훈방전적모식식별망락,병대차류망락진행훈련화측시,결과표명차망락용우전훈방전모식식별시유효적.
T-S fuzzy neural network (T-S FNN) is presented to recognize the types of corona discharge.Three types of corona discharge model are made,the maximum,minimum,mean and fractal dimension are extracted from sampling corona discharge signals and then used as the input vectors of neural network.T-S FNN topological structure is investigated in accordance with the number of input vectors,membership functions and the number of membership functions.The T-S FNN,with 4 input neurons and 3 Gaussian functions,is confirmed as the pattern recognition network,and the network are trained and tested with the extracted features.Results indicate that the method is effective.