云模型和物元理论在变压器故障诊断中的应用

Tao Wang, Li-qun Shang, Xianmin Ma
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引用次数: 3

摘要

基于云模型和物元理论,结合云模型的不确定推理特点和物元理论可同时进行定性和定量分析的特点,提出了一种电力变压器故障诊断方法,有效地解决了数据样本少,特别是故障数据样本少的问题。以实际数据为例,将改进的物元理论模型与相关计算数据进行比较,结果表明改进的物元理论模型比传统方法具有更高的诊断精度。算例分析验证了该方法的正确性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Cloud Model and Matter Element Theory in Transformer Fault Diagnosis
Based on cloud model and matter element theory, and combining the uncertain reasoning characteristics of the cloud model and qualitative and quantitative analysis can be carried out at the same time by matter element theory, a power transformer fault diagnosis method is proposed, which effectively solves the problem of fewer data samples, especially fewer fault data samples. Taking the actual data as an example, the improved matter-element theory model and correlation calculation data are compared, and the results show that the improved matter element theory model has higher diagnostic accuracy than traditional methods. Example analysis verifies the correctness and effectiveness of the method.
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