粗糙集在电力变压器故障诊断中的应用

Application of Rough Set in Fault Diagnosis of Power Transformer

  • 摘要: 电力变压器是一种比较复杂的系统,在实际故障诊断中要想获得完备的实验数据比较困难。针对该问题,提出了一种基于粗糙集的电力变压器故障诊断新方法,即分析搜集到的电力变压器历史故障数据,确定条件属性集和决策属性集;对条件属性集进行约简,去除冗余信息,提取关键信息,得到相应的规则集;利用该规则集对电力变压器进行故障诊断。实例分析验证了该方法的正确性和有效性。

     

    Abstract: Power transformer is a complex system. It is difficult to gain complete experiment data in actual fault diagnosis. To solve the problem, the paper proposed a new method of fault diagnosis of power transformer based on rough set. The implementing steps of the method are as follows: analyzing collected history fault data of power transformer to determine condition attribute set and decision attribute set; deducting condition attribute set to remove redundant information and extract key information, so as to gain relative rule set; making fault diagnosis for power transformer by use of the rule set. The case analysis proved validity and effectiveness of the method.

     

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