Analysis Approach for Inter-harmonic with BP Neural Network and Linear Neural Network

WANG Hao-na1; BI Zhi-zhou2; FU Zhi-hong3; LI Chun-yan3

doi:10.13296/j.1001-1609.hva.2013.02.003

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Analysis Approach for Inter-harmonic with BP Neural Network and Linear Neural Network

更新时间：2025-04-26

- Analysis Approach for Inter-harmonic with BP Neural Network and Linear Neural Network
- High VoltageApparatus Vol. 49, Issue 2, Pages: 19-24(2013)
- 作者机构：
  
  1. 广东电网公司惠州供电局
  2. 云南电力试验研究院(集团)有限公司电力研究院
  3. 重庆大学电气工程学院输配电装备及系统安全与新技术国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2013.02.003
  CLC： TM711;TP183
- Published：2013
- 稿件说明：
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[1]王好娜,毕志周,付志红,李春燕.基于BP神经网络和线性神经网络的间谐波分析方法[J].高压电器,2013,49(02):19-24.

WANG Hao-na1, BI Zhi-zhou2, FU Zhi-hong3, et al. Analysis Approach for Inter-harmonic with BP Neural Network and Linear Neural Network[J]. High voltageapparatus, 2013, 49(2): 19-24.
[1]王好娜,毕志周,付志红,李春燕.基于BP神经网络和线性神经网络的间谐波分析方法[J].高压电器,2013,49(02):19-24. DOI： 10.13296/j.1001-1609.hva.2013.02.003.

WANG Hao-na1, BI Zhi-zhou2, FU Zhi-hong3, et al. Analysis Approach for Inter-harmonic with BP Neural Network and Linear Neural Network[J]. High voltageapparatus, 2013, 49(2): 19-24. DOI： 10.13296/j.1001-1609.hva.2013.02.003.

摘要

传统的线性神经网络

其激励函数是固定函数

所以不能对间谐波的频率进行调整

而基波频率微小的偏差将导致谐波检测出现较大的误差。笔者在采用BP神经网络的高精度基波检测的基础之上

采用激励函数参数可调的线性神经网络来分析间谐波。理论分析和仿真结果都表明

无论有没有噪声

文中提出的方法都具有较高的检测精度

自适应能力较强

其中检测与偶数次谐波比较接近的间谐波的优势更明显。

Abstract

The excitation function of traditional linear neural network is fixed

it can’t adjust to harmonic frequency

and tiny deviation of base wave frequency will lead larger error to harmonic detection.Based on high precision of wave detection using the BP neural network

the linear neural network which has adjustable parameters activation function to analyse inter-harmonic in this paper.The simulation and the oretical analysis show that the proposed method has higher detection accuracy and adaptive ability whether with any noise

especially detecting the closed even harmonic frequency of inter-harmonic.

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