CAJ | 학술논문

针对高压输电线路故障征兆和故障特征的非线性特征，结合故障起因的分类方法，研究应用 BP神经网络对高压输电线路的故障起因识别，设计了一个基于 BP 神经网络的输电线路故障起因识别实时系统，主要依靠事故环境下所发生的一系列实时序列信息进行分析，判断故障发生的原因。通过仿真和实际运行证明BP神经网络可以有效地运用到输电线路故障起因识别中。通过现有数据的收集，并对其进行分析，最终判断出电力系统故障产生的原因。
침대고압수전선로고장정조화고장특정적비선성특정，결합고장기인적분류방법，연구응용 BP신경망락대고압수전선로적고장기인식별，설계료일개기우 BP 신경망락적수전선로고장기인식별실시계통，주요의고사고배경하소발생적일계렬실시서렬신식진행분석，판단고장발생적원인。통과방진화실제운행증명BP신경망락가이유효지운용도수전선로고장기인식별중。통과현유수거적수집，병대기진행분석，최종판단출전력계통고장산생적원인。
Due to the high voltage transmission line fault symptoms and fault characteristics of the nonlinear characteristics,the combination of the causes of the fault classification method,studies the application of BP neural network for high voltage transmission line fault cause identification,designed a transmission line fault causes recognition based on BP neural network in real-time systems,rely mainly on accident environment by a series of real time sequence information analysis,determine the cause of the failure.The simulation and actual operation proves that the BP neural network can effectively used in power trans-mission line fault cause identification.Through the existing data collection,and carries on the analysis,finally determine the causes of electric power system fault.