基于QIA-BP神经网络算法的变压器故障诊断  

Transformer Fault Diagnosis Based on QIA-BP Neural Network Algorithm

作　　者：何宁辉 沙伟燕 胡伟 谢海滨 张佩 田天 HE Ning-hui;SHA Wei-yan;HU Wei;XIE Hai-bin;ZHANG Pei;TIAN Tian(Electric Power Research Institute,State Grid Ningxia Electric Power Co.,Ltd.,Yinchuan 750011,China;State Grid Ningxia Electric Power Co.,Ltd.,Yinchuan 750001,China)

机构地区：[1]国网宁夏电力有限公司电力科学研究院,宁夏银川750011 [2]国网宁夏电力有限公司,宁夏银川750001

出　　处：《变压器》2021年第3期50-56,共7页Transformer

摘　　要：在对变压器常见故障进行介绍的基础上,针对BP神经网络存在的缺陷,提出了经量子免疫优化的BP神经网络算法,通过与不同算法的对比,验证了该算法的准确性和快速性。Based on the introduction of common faults of transformers,aiming at the defects of BP neural network,a BP neural network algorithm optimized by quantum immune is proposed.The accuracy and rapidity of the algorithm are verified by comparing with different algorithms.

关 键 词：变压器 油中溶解气体 故障诊断 量子免疫BP神经网络 

分 类 号：TM406[电气工程—电器]