Publicado en 3C Tecnología – Volume 13 Issue 1 (Ed. 45)
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Resumen
Abstract
This study centers on the 3D simulation localization technology of power cable fault points, using the combination of wavelet transform and neural network, aiming to improve the accuracy and efficiency of cable fault localization. This paper adopts the method of combining wavelet transform and genetic algorithm optimization of back propagation (GA-BP) neural network. First, by constructing a three-dimensional simulation model of power cables, the wavelet transform is applied to extract fault features and the GA-BP neural network is utilized for fault point localization. The experimental results show that the average localization errors of this method in single- phase ground fault and two-phase grounded short-circuit fault are 0.112km and 0.126km, respectively, which are significantly better than the traditional method. Under different fault initial phase angle conditions, the proposed method shows strong adaptability and the error is controlled within 1%. Meanwhile, the present algorithm exhibits strong noise suppression ability under white and colored noise backgrounds, especially in low signal-to-noise ratio environments. In summary, this study demonstrates the effectiveness of the 3D simulation localization technique for power cable fault points combining wavelet transform and GA-BP neural network in improving the localization accuracy and noise resistance.
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Keywords
Power cable, three-dimensional simulation, wavelet transform, GA-BP neural network
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