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Detection and Classification of Open Conductor Faults in Six-Phase Transmission Line Using Wavelet Transform and Naive Bayes Classifier

机译:基于小波变换和朴素贝叶斯分类器的六相输电线路断线故障检测与分类

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The rapidly rising per capita consumption of electrical energy have put question mark on the present power network to meet the demand. The six-phase transmission can be an alternative solution to cope up with the increasing power demand having the additional power transmission capability of 73 % with the existing transmission network without any major modifications. The probable occurrence of large number of faults makes the protection task highly challenging. In this context, this paper presents a Naive Bayes classifier (NBC) based scheme to perform the task of fault detection/classification of series faults in six-phase transmission system. The NBC based classification approach is known to provide simple and efficient solution for complicated classification problems. The performance of the proposed scheme have been validated with random test cases generated under widely varying fault parameters. The test results reflect the immunity of the proposed approach to variation in fault parameters.
机译:迅速增长的人均电能消耗已经对目前的电网提出了问号,以满足需求。六相传输可以作为一种替代解决方案,以应付不断增长的功率需求,在不进行任何重大修改的情况下,现有传输网络具有73%的额外功率传输能力。可能发生的大量故障使保护任务极具挑战性。在这种情况下,本文提出了一种基于朴素贝叶斯分类器(NBC)的方案来执行六相传输系统中的故障检测/串联故障分类的任务。已知基于NBC的分类方法可为复杂的分类问题提供简单有效的解决方案。所提方案的性能已通过在广泛变化的故障参数下生成的随机测试案例进行了验证。测试结果反映了所提出方法对故障参数变化的抗扰性。

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