基于图像处理的带式输送机煤体积计量

王桂梅,逯圣辉,刘杰辉,杨立洁

计量学报 ›› 2020, Vol. 41 ›› Issue (6) : 724-728.

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PDF(605 KB)
计量学报 ›› 2020, Vol. 41 ›› Issue (6) : 724-728. DOI: 10.3969/j.issn.1000-1158.2020.06.15
力学计量

基于图像处理的带式输送机煤体积计量

  • 王桂梅,逯圣辉,刘杰辉,杨立洁
作者信息 +

Coal Volume Measurement of Belt Conveyor Based on Image Processing

  • WANG Gui-mei,LU Sheng-hui,LIU Jie-hui,YANG Li-jie
Author information +
文章历史 +

摘要

对基于激光斜射法三角测距原理的带式输送机上煤流体积实时计量进行了研究。首先对工业相机采集到的激光线进行图像处理以获取煤流截面,根据煤流表面激光线特点提出了一种能够大幅度降低搜索区域的激光线细化算法,并采用线性插值对断线进行连接,通过合成上下轮廓线形成完整煤截面;然后建立了动态煤体积计量模型,通过积分得到煤流体积。最后进行了实验,单帧图像的采集处理时间平均约为0.152s,且算法稳定性较好,能够满足实际工况要求。

Abstract

Real-time measurement of coal fluid volume on belt conveyor based on laser oblique shooting triangular ranging principle was studied. Firstly, image processing of laser lines collected by industrial cameras was carried out to obtain coal flow cross section. According to the characteristics of laser lines on coal flow surface, a laser line thinning algorithm which can greatly reduce the searching area was proposed. It was superior to the similar algorithms in running time and thinning effect. Linear interpolation was used to connect the broken lines and form a complete coal cross section by synthesizing the upper and lower contours. After that, a dynamic coal volume measurement model was established, and coal fluid volume was obtained by integration. Finally, experiments were carried out. The average time of acquisition and processing of single frame image was about 0.152 s, and the algorithm had good stability, which could meet the requirements of actual working conditions.

关键词

计量学 / 煤流体积 / 三角测距 / 激光斜射法 / 图像处理 / 激光线细化

Key words

metrology / coal fluid volume / triangulation range / laser oblique shooting / image processing / laser line thinning

引用本文

导出引用
王桂梅,逯圣辉,刘杰辉,杨立洁. 基于图像处理的带式输送机煤体积计量[J]. 计量学报. 2020, 41(6): 724-728 https://doi.org/10.3969/j.issn.1000-1158.2020.06.15
WANG Gui-mei,LU Sheng-hui,LIU Jie-hui,YANG Li-jie. Coal Volume Measurement of Belt Conveyor Based on Image Processing[J]. Acta Metrologica Sinica. 2020, 41(6): 724-728 https://doi.org/10.3969/j.issn.1000-1158.2020.06.15
中图分类号: TB938.1   

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基金

河北省自然科学基金(E2019402436)

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