基于光波导边界传输特性的污秽在线监测技术

CAI Wei

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基于光波导边界传输特性的污秽在线监测技术

更新时间：2025-08-13

- 基于光波导边界传输特性的污秽在线监测技术
- Automation of Electric Power Systems Vol. 38, Issue 10, Pages: 107-112(2014)
- 作者机构：
  
  第二炮兵工程大学,陕西省,西安市,710025
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
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CAI Wei. [J]. Automation of electric power systems, 2014, 38(10): 107-112.
DOI：

CAI Wei. [J]. Automation of electric power systems, 2014, 38(10): 107-112. DOI：

摘要

基于光波导边界传输特性和人工神经网络

文中介绍了一种可同时监测输电线路绝缘子表面等值盐密和灰密的污秽在线监测装置。在详细分析光波导表面污层对全反射光束影响机理的基础上

提出了光波导和光源设计方案。通过不同湿度、不同污秽等级、不同灰盐比条件下的积污标定试验

获取了大量样本数据

并依此建立和训练了人工神经网络模型。检验结果和运行实践表明

利用该装置及训练后的内嵌神经网络模型

可实现盐密和灰密的同时监测

且测试精度满足相关标准要求。

Abstract

An online pollution monitoring equipment is developed based on boundary transmission characteristics of optical waveguide and artificial neural network (ANN)

which can measure both equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) on insulators’ surfaces. By analyzing the effects of the optical waveguide’s surface pollution on the reflected beam

the optical waveguide and the optical source are designed. A series of validating and calibrating tests have been made under different humidity

different salt density and ash density conditions

from which a large quantity of sample data are obtained and a unique ANN model is built and trained. The inspecting and running results show that this equipment together with the embedded ANN model can be used to monitor ESDD and NSDD of the insulators at once

and with satisfactory test precision.

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Related Institution

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