简化的Schavemaker交流电弧模型参数的计算方法研究  

Research on the calculation method for the parameters of the simplified Schavemaker AC arc model

作　　者：高杨 王莉[1] 张瑶佳 曾珂 GAO Yang;WANG Li;ZHANG Yaojia;ZENG Ke(College of Automation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学自动化学院,江苏南京211106

出　　处：《电力系统保护与控制》2019年第8期96-105,共10页Power System Protection and Control

基　　金：国家自然科学基金项目资助(51277093)~~

摘　　要：以工业、商业、住宅的电气系统为背景,以建立准确的电弧模型为目的,基于简化的Schavemaker模型进行研究,提出一种基于神经网络的模型参数计算方法。利用基于实验数据的模型参数计算方法得到神经网络训练样本,构建模型参数与工作条件之间的神经网络。利用所建网络可在无法获得特定工作条件下的电弧实验数据时直接预测该工作条件下的模型参数值。最终的验证结果表明,所提出的基于神经网络的模型参数计算方法准确度高,而且相比于现有方法具有一定的优越性。同时也反映了所建交流电弧模型能有效地实现电弧模拟,可为进一步的交流电弧特征学习和检测算法设计提供方法和工具。To establish an accurate arc model, this paper researches the simplified Schavemaker model under the background of industrial, commercial and residential electrical systems. A calculation method based on neural network is proposed, which uses a calculation method based on experimental data to obtain training samples and build a neural network between model parameters and working conditions. The built neural network can directly predict the model parameters’ values under certain working condition when the experimental data of this working condition cannot be obtained. The final verification results show that the proposed model parameter calculation method based on neural network has high accuracy and superiority compared with the existing methods. It also shows that the established AC arc model can realize arc simulation and can be used for further AC arc feature learning and detection algorithm design.

关 键 词：交流电弧故障 Schavemaker模型 神经网络 交流电弧时频域特征 

分 类 号：TM501.2[电气工程—电器]