基于自适应线性神经元的高压电缆状态监测及故障定位方法研究
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引用本文:胡裕峰,张自远,金 涛,盛敏超,李中龙.基于自适应线性神经元的高压电缆状态监测及故障定位方法研究[J].计算技术与自动化,2022,(4):1-6
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胡裕峰,张自远,金 涛,盛敏超,李中龙 (江西省九江供电公司江西 九江 332000) 
中文摘要:高压电缆的早期故障往往是由电应力过大和电缆老化造成的。如果这种故障在短时间内以电流尖峰的形式出现,则可能出现永久性故障。为了检测高压电缆中的早期故障,提出了一种基于累积和算法以及自适应线性神经元的监测策略,从而检测单相瞬变和区分早期故障。累积和算法对噪声具有鲁棒性。在仿真中对所提出的方法进行测试,结果显示所提出方法可实现高精度和高速故障定位,验证了其有效性。
中文关键词:高压电缆  状态监测  神经网络
 
Research on High-voltage Cable Condition Monitoring and Fault Location Method Based on Adaptive Linear Neuron
Abstract:The early failure of high voltage cable is often caused by excessive electrical stress and cable aging. If this fault occurs in the form of current spike in a short time, a permanent fault may occur. In order to detect early faults in high voltage cables, a monitoring strategy based on cumulative sum algorithm and adaptive linear neurons is proposed to detect single-phase transients and distinguish early faults. The cumulative sum algorithm is robust to noise. The simulation results show that the proposed method can achieve high-precision and high-speed fault location, and verify its effectiveness.
keywords:high voltage cable  condition monitoring  neural network
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