基于时域反射法和模式识别网络的节能导线故障诊断方法

Diagnosis of Energy-Saving Wire Failures Based on Time Domain Reflection and Pattern Recognition Network

中文关键词:节能导线  时域反射法  模式识别网络  故障诊断

keywords:energy-saving conductor  TDR  PRN  fault diagnosis

中文摘要:开发了一种基于时域反射法（time domain reflectometry，TDR）和模式识别网络（pattern recognition network，PRN）的节能导线故障诊断方法。该方法通过整合TDR技术与PRN算法，并结合简单的定位算法，实现了对节能导线故障位置的高效定位。在信号处理阶段，利用小波分析技术对TDR响应信号进行降噪处理，并利用主成分分析法对降噪后的TDR响应信号进行分析，有效降低了数据量，缩短了计算时间。为验证所提方法的可靠性，对4种不同的故障情况进行了分类识别测试，包括2种简单的Y型网络结构及2种复杂的YY型网络结构。测试结果表明，与粒子群优化算法（particle swarm optimization，PSO）及遗传算法（genetic algorithm，GA）相比，所提方法在计算时间和识别准确率方面均展现出了显著优势，从而验证了所提方法的有效性和可靠性。

Abstract:This paper presents a fault diagnosis method for energy-saving conductors based on time domain reflectometry （TDR） and pattern recognition network （PRN）. The method integrates TDR technology with the PRN algorithm and combines a simple localization algorithm to achieve efficient location of faults in energy-saving conductors. In the signal processing stage， the paper first uses wavelet analysis technology to denoise the TDR response signal，and then uses the principal component analysis method to analyze the TDR response signal after denoising， thus effectively reducing the amount of data and shortening the calculation time. To verify the reliability of the proposed method， the paper conducts classification recognition tests on four different fault scenarios，including two simple Y-type network structures and two complex YY-type network structures. The test results show that compared with the particle swarm optimization（PSO） algorithm and genetic algorithm（GA） algorithm，the proposed method exhibits significant advantages in terms of computation time and recognition accuracy，thus verifying the effectiveness and reliability of the method.