摘要
基于新信息优先原则,将最新突变数据列为离散GM(1,1)模型初始值,采用预测数据等维更新原始数据序列,同步递进更新初始值,如此反复建立了等维滚动的初始值递进的动态离散GM(1,1)模型,运用该模型对变压器油中溶解气体含量有明显变化的情况进行了故障预测,并与DGM(1,1)模型的预测结果进行了对比分析。结果表明,本文方法实用、有效。
According to prior new information in grey theory, the newest sudden change data series is taken as initial value of discrete GM（1 ,1） model. And the raw data series is updated and the initial value is replaced with the prediction data by a new method of equal-dimensional rolling. Then the dynamic discrete GM（1,1） model of equal-dimensional rolling and forward-varying initial value is established. Finally, the model is applied to predict fault in condition of dissolved gases changing obviously in transformer oil. Compared with the result of DGM（1,1）model, the results show that the pro- posed method is effective and practical.
出处
《水电能源科学》
北大核心
2012年第3期170-172,共3页
Water Resources and Power
基金
四川省电力电子重点学科基金资助项目(SZD0503)
关键词
初始值递进
DGM(1
1)模型
等维滚动
变压器
故障预测
forward-varying initial value
DGM（1,1） model
equal-dimensional rolling
transformer
fault prediction
