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首页> 外文期刊>American journal of applied sciences >Choice Of Input Data Type Of Artificial Neural Network To Detect Faults In Alternative Current Systems | Science Publications
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Choice Of Input Data Type Of Artificial Neural Network To Detect Faults In Alternative Current Systems | Science Publications

机译:交流系统故障检测的人工神经网络输入数据类型选择科学出版物

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> This paper present a study on different input data types of ANN used to detect faults such as over-voltage in AC systems (AC network , induction motor). The input data of ANN are AC voltage and current. In no fault condition, voltage and current are sinusoidal. The input data of the ANN may be the instantaneous values of voltage and current, their RMS values or their average values after been rectified. In this paper we presented different characteristics of each one of these data. A digital software C++ simulation program was developed and simulation results were presented.
机译: >本文对用于检测交流系统(交流网络,感应电动机)中的过电压等故障的ANN的不同输入数据类型进行了研究。 ANN的输入数据是交流电压和电流。在没有故障的情况下,电压和电流为正弦波。 ANN的输入数据可以是电压和电流的瞬时值,其RMS值或经过整流后的平均值。在本文中,我们介绍了每种数据的不同特征。开发了数字软件C ++仿真程序,并给出了仿真结果。

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