张重远,林志锋,刘栋,黄景立.基于正态云模型&改进贝叶斯分类器的变压器故障诊断[J].电测与仪表,2017,54(4):. zhangzhongyuan,linzhifeng,liudong,Huang Jingli.Transformer Fault Diagnosis Based on Normal Cloud Model & Improved Bayesian Model[J].Electrical Measurement & Instrumentation,2017,54(4):.
基于正态云模型&改进贝叶斯分类器的变压器故障诊断
Transformer Fault Diagnosis Based on Normal Cloud Model & Improved Bayesian Model
In order to solve the problem of data mining in diagnosing transformer fault, that data of dissolved gas-in-oil is divided without considering the randomness and fuzziness, Cloud model is applied. The efficiency of mining association rules is also improved through Cloud model; For the assumption in Naive Bayes Classifier is not conformed to the actual situation, An association rule forest and a method of the joint probability calculated is applied to improve Naive Bayes Classifier. The new Bayes Classifier is proved to be practical in the diagnosis of transformer by comparing with other classifier and testing example.