绝缘子等值附盐密度的预测  

Prediction of Insulator′s ESDD

作　　者：程加堂[1] 熊伟[1] 艾莉[1] 

机构地区：[1]红河学院工学院,云南蒙自661100

出　　处：《电瓷避雷器》2010年第4期8-11,共4页Insulators and Surge Arresters

摘　　要：等值附盐密度是确定污秽等级和绘制电网污区分布图的主要依据,而气象因子对绝缘子的等值附盐密度(ESDD)影响复杂,难以建立精确的数学模型来表述二者间的关系。结合灰色模型和神经网络模型在反映数据序列变化趋势性上的明显效果,采用带神经网络补偿器的灰色神经网络模型来预测绝缘子在一定气象因子条件下的等值附盐密度,拟合输入与输出之间的复杂非线性函数关系。结果表明该模型有较高的预测精度,优于单纯的灰色神经网络模型,具有一定的理论价值和实际应用价值。The equivalent salt deposit density （ESDD） is the basis of determining pollution classes and mapping grid pollution areas. However, the influence of meteorological factors on insulator ESDD （ESDD） is complex, difficult to establish accurate mathematical model to express the relationship between the two. Combined with the gray model and neural network model to reflect the apparent effect on the changing trend of data sequence , the gray neural network model with the neural network compensator is used to predict the insulator＇s ESDD under the conditions of certain meteorological factors, the nonlinear mapping between input and output is fitted. The results show that the model has higher prediction accuracy and is better than a simple gray neural network model, and have some theoretical value and practical application value.

关 键 词：绝缘子 等值附盐密度 灰色神经网络 预测 神经网络补偿器 

分 类 号：TM216[一般工业技术—材料科学与工程]