摘要
为了提高油中溶解气体分析方法的诊断能力,提出了基于灰云模型的电力变压器故障诊断新方法。通过熵理论引入软化因子,将电力变压器故障诊断标准矩阵中的分类界限值转化为区间数概念。利用峰值、左右界限值、熵、超熵表征灰云模型,以此反映电力变压器故障诊断分类界限值的模糊性和随机性。建立电力变压器故障诊断各评估指标重要性信息的未确知有理数,得到各指标的权重值,有效地减少了诊断结果的主观性。利用结合灰云模型实现白化权函数的灰色聚类算法对变压器故障类型进行分析和判断。实际算例分析结果表明,所提方法诊断精度较高,验证了该模型的实用性和有效性,并具有分析速度快,实时性较好的优点。
In order to improve the diagnosis ability of dissolved gas analysis, a novel method for the power transformer fault diagnosis based on gray cloud model is proposedl Softening factor is introduced via entropy theory, and the classification limit single value for canonical matrix of the power transformer fault diagnosis is transformed into the concept of interval numbers limit value. The gray cloud model is used to reflect the fuzziness and randomness of the classification limit value for the power transformer fault diagnosis, which is composed of the peak value, the boundary value of left and right endpoint, the entropy, and the hyper entropy. The subjectivity of the diagnosis results is effectively reduced by establishing the importance information unascertained rational numbers of indicators for the power transformer fault diagnosis, through which the weight value of each index is obtained. A gray clustering algorithm based on gray cloud whitening weighting function is used to analyze and judge the fault pattern of the power transformer. The actual numerical example results show that the proposed method has high degree of diagnosis accuracy, and is characterized by fast diagnosis and good real-time, demonstrating the model is practical and effective.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2012年第12期151-155,共5页
Power System Protection and Control
关键词
溶解气体分析
电力变压器
故障诊断
灰云
灰色聚类
云理论
软化因子
dissolved gas analysis（DGA）
power transformer
fault diagnosis
gray cloud
gray clustering
cloud theory
softening factor
