用户供电端智能运维自动化报障系统设计

Design of automatic barrier alarm system for intelligent operation and maintenance of user power supply terminal

为了提高用户端故障诊断工作效率,结合BP神经网络和GA算法设计一个用户供电端智能运维自动化变压器故障诊断系统。首先,通过分析BP神经网络和GA算法原理,对GA算法选择算子、交叉算子、变异算子进行改进,并利用改进GA算法优化BP神经网络参数,提高了变压器故障诊断效率和诊断速率;其次,基于改进GA算法优化的BP神经网络,构建了用户供电段智能运维自动化变压器故障诊断模型;最后,通过实验对提出方法进行验证,结果表明,提出的方法具有较好的性能,有助于用户供电端实现故障自动化报障。

In order to improve the efficiency of fault diagnosis at the client end, this paper combines BP neural network and GA algorithm to design an intelligent operation and maintenance automation transformer fault diagnosis system at the user power supply end. Firstly, by analyzing the principle of BP neural network and GA algorithm, the selection operator, crossover operator and mutation operator of GA algorithm are improved, and the improved GA algorithm is used to optimize the parameters of BP neural network, which improves the efficiency and rate of transformer fault diagnosis. Secondly, based on the BP neural network optimized by the improved GA algorithm, the fault diagnosis model of the intelligent operation and maintenance automation transformer in the user power supply segment was constructed. Finally, the proposed method is verified by experiments. The results show that the proposed method has good performance and is helpful to realize automatic fault detection at the power supply end of the user.