基于图像处理的带式输送机煤体积计量

doi:10.3969/j.issn.1000-1158.2020.06.15

Abstract
Figure/Table
References (16)
Related Citation (15)

Download: PDF (605 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

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.

Key words： metrology coal fluid volume triangulation range laser oblique shooting image processing laser line thinning

Received: 10 May 2019 Published: 08 June 2020

PACS:

TB938.1

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WANG Gui-mei
	LU Sheng-hui
	LIU Jie-hui
	YANG Li-jie

Cite this article:

WANG Gui-mei,LU Sheng-hui,LIU Jie-hui, et al. Coal Volume Measurement of Belt Conveyor Based on Image Processing[J]. Acta Metrologica Sinica, 2020, 41(6): 724-728.

URL:

http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2020.06.15 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2020/V41/I6/724

［1］颜敏, 邓如勇, 黄校春, 等. 电子皮带秤计量准确性方法研究与设计［J］. 自动化仪表, 2019, 40(1): 67-69+73.
Yan M, Deng R Y, Huang X C, et al. Research and design of measurement accuracy method of electronic belt weigher ［J］. Automation Instrument, 2019,40 (1): 67-69+73.
［2］艾海波. 基于图像处理技术的隧道裂缝检测综述［J］. 现代计算机(专业版), 2018, (24): 72-75.
Ai H B. Survey of tunnel crack detection based on image processing technology［J］. Modern Computer (Professi-onal Edition), 2018, (24): 72-75.
［3］刘美, 薛新松, 刘广文, 等.对比度增强的彩色图像灰度化算法［J］. 长春理工大学学报(自然科学版), 2018, 41(5): 70-74.
Liu M, Xue X S, Liu G W, et al. Color image graying algorithm for contrast enhancement［J］. Journal of Cha-ngchun University of Technology (Natural Science Editi-on), 2018, 41 (5): 70-74.
［4］张海宁. 基于多峰高斯分布的彩色图像灰度化算法研究［D］. 温州:温州大学, 2018.
［5］孙国栋, 车大伟. 一种基于反馈的车牌图像二值化方法［J］. 自动化技术与应用, 2019, 38(2): 135-139.
Sun G D, Che D W. A method of binarization of license plate image based on feedback［J］. Automation technol-ogy and application, 2019, 38 (2): 135-139.
［6］冯炎. 基于对比度归一化的历史文档图像二值化算法［J］. 科学技术与工程, 2019, 19(1): 172-176.
Feng Y. Binarization algorithm of historical document image based on contrast normalization［J］. Science and Technology and Engineering, 2019, 19 (1): 172-176.
［7］薛亚男, 辛化梅. ESPI图像的细化算法改进［J］. 电子技术, 2018, 47(11): 35-37.
Xue Y N, Xin H M. Improvement of thinning algorithm for ESPI image［J］. Electronic Technology, 2018, 47(11): 35-37.
［8］胡改玲, 周翔, 杨涛, 等. 光刀自适应灰度加权亚像素中心精确提取［J］. 西安交通大学学报, 2018, 52(5): 21-28.
Hu J L, Zhou X, Yang T, et al. Accurate extraction of sub-pixel centers by light knife adaptive gray-scale weighting［J］. Journal of Xian Jiaotong University, 2018, 52(5): 21-28.
［9］孙卫红, 李乾坤, 邵铁锋, 等. 基于机器视觉的桩护壁裂缝检测方法［J］.计算机工程与应用, 2019, (14): 1-9.
Sun W H, Li Q K, Shao T F, et al. Crack detection method of pile wall based on machine vision［J］. Computer engineering and application, 2019, (14): 1-9.
［10］向丽娜. 计算机图像识别的智能化处理方法解读［J］. 电子技术与软件工程, 2019, (3): 137.
Interpretation of Intelligent Processing Method for Com-puter Image Recognition［J］. Electronic Technology and Software Engineering, 2019, (3): 137.
［11］Schoch A, Salvadori A, Germann I. High-Speed Mea-surement of Complex Shaped Parts at Elevated Tempera-ture by Laser Triangulation (Special Issue on Laser Metrology for Precision Measurement and Inspection in Industry)［J］. International Journal of Automation Technology, 2015, 9(5): 558-566.
［12］程淑红,赵考鹏,张仕军, 等. 基于U-net的水位线检测［J］. 计量学报, 2019, 40(3):361-363.
Cheng S H, Zhao K P, Zhang S J, et al. Water Level Detection Based on U-net［J］. Acta Metrologica Sinica, 2019, 40(3):361-363.
［12］顾梅花, 苏彬彬, 王苗苗, 等. 彩色图像灰度化算法综述［J］. 计算机应用研究, 2019, (5):1-10.
Gu M H, Su B B, Wang M M, et al. Summary of color image graying algorithms［J］. Computer application research, 2019, (5): 1-10.
［13］Bracˇun D, kulj G, Kadi M. Spectral selective and difference imaging laser triangulation measurement syst-em for on line measurement of large hot workpieces in precision open die forging［J］. International Journal of Advanced Manufacturing Technology, 2016, 90(1-4): 1-10.
［14］罗华飞. MATLAB GUI设计学习手记［M］. 北京: 北京航空航天大学出版社. 2009.
［15］孙正. 数字图像处理技术及应用［M］. 北京: 机械工业出版社. 2016.
［16］赵小川. 现代数字图像处理技术提高及应用案例详解MATLAB版［M］. 北京: 北京航空航天大学出版社. 2012.