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An evolutionary computation based fuzzy fault diagnosis system for a power transformer

机译:基于进化计算的电力变压器模糊故障诊断系统

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To improve the diagnosis accuracy of conventional dissolved gas analysis (DGA) approaches, this paper proposes an evolutionary programming (EP) based fuzzy system development technique to identify the incipient faults of the power transformers. In comparison to results of the conventional DGA and artificial neural network (ANN) classification methods, the proposed method has been verified to possess superior performance both in developing the diagnosis system and in identifying the practical transformer fault cases.
机译:为了提高常规溶解气体分析(DGA)方法的诊断精度,本文提出了一种基于进化的模糊系统开发技术来识别电力变压器的初始故障。与传统DGA和人工神经网络(ANN)分类方法的结果相比,已经验证了该方法在开发诊断系统和识别实际变压器故障情况下具有卓越的性能。

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