基于智能物联网技术的变压器油介质损耗带电检测系统研究

2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) Pub Date : 2022-10-28 DOI:10.1109/ICDSCA56264.2022.9988516

Kexin Zhang, Siwei Han, Jianquan Liang, Yue Wang, Dewen Zhang, Shiyu Chen

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引用次数: 0

摘要

本文分析了Blackman自卷积窗的光谱特性。同时，提出了一种基于计算机智能物联网技术的黑曼自卷积窗双谱插值FFT介质损耗角带电检测算法，并详细推导了介质损耗角的计算公式。最后用计算机进行了仿真验证。结果表明，该算法能有效提高介质损耗角的测量精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Research on Transformer Oil Dielectric Loss Live Detection System Based on Intelligent Internet of Things Technology

This paper analyzes the spectral properties of Blackman self-convolution windows. At the same time, a blackman self-convolution window bispectrality interpolation FFT based on the computer intelligent Internet of things technology is proposed for the dielectric loss angle charged detection algorithm, and the calculation formula of the dielectric loss angle is deduced in detail. Finally, the computer is used for simulation verification. The results show that the algorithm It can effectively improve the measurement accuracy of the dielectric loss angle.

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来源期刊

2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)

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