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基于红外CCD的钢水红外测温模型分析

杨友良 刘爱旭 马翠红 连畅

激光技术2018,Vol.42Issue(4):562-566,5.
激光技术2018,Vol.42Issue(4):562-566,5.DOI:10.7510/jgjs.issn.1001-3806.2018.04.024

基于红外CCD的钢水红外测温模型分析

Analysis of infrared temperature measurement model of molten steel based on infrared CCD

杨友良 1刘爱旭 1马翠红 1连畅1

作者信息

  • 1. 华北理工大学电气工程学院,唐山063210
  • 折叠

摘要

Abstract

In order to quickly and accurately measure the molten steel temperature on line,infrared CCD camera temperature measurement technology was used to measure the surface temperature of molten steel.The image of molten steel at different temperatures was collected by an infrared CCD camera to calculate the average of the grayscale values in the region of the image near the temperature measured by the thermocouple.The golden section optimization method was introduced to determine the expansion coefficient in the generalized regression neural network.The nonlinear curve fitting between gray scale and temperature was compared by using the traditional least square method and the modified generalized regression neural network.The results show that the temperature measurement model established by the improved generalized regression neural network can effectively improve the on-line temperature measurement accuracy and make the measurement error of molten steel temperature within 0.1%.It meets the requirements of industrial design.This study provides a reference for the application of generalized regression neural network in the field of molten steel temperature measurement.

关键词

测量与计量/广义回归神经网络测温/精度提高/灰度比值/最小二乘法

Key words

measurement and metrology/temperature measurement based on generalized regression neural network/precision improvement/grayscale ratio/least square method

分类

机械制造

引用本文复制引用

杨友良,刘爱旭,马翠红,连畅..基于红外CCD的钢水红外测温模型分析[J].激光技术,2018,42(4):562-566,5.

基金项目

国家自然科学基金资助项目(61171058) (61171058)

激光技术

OA北大核心CSCDCSTPCD

1001-3806

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