Coal gangue loading volume measurement method based on laser triangulation
-
摘要: 为了解决地磅在煤矸石装载量称重中效率低、成本高等问题, 提出了一种基于激光三角法的非接触式煤矸石装载体积测量方法。首先通过CCD相机实时采集激光器投射在满载煤矸石的运动车厢表面的激光条纹信息, 并采用中值滤波和基于Otsu算法的阈值分割法对图像进行预处理, 实现图像有效区域的提取; 然后使用基于骨架的灰度重心法提取激光条纹的中心线; 最后采用黎曼积分计算车辆的煤矸石装载量。结果表明, 此系统结果误差控制在4%以内, 符合系统运行要求, 证实了该测量方法的可行性与实用性。该研究为复杂环境下公路运输管理的装载量测量提供了参考。Abstract: In order to solve the problems of low efficiency and high cost in weighing coal gangue loading, a non-contact coal gangue loading volume measurement method based on laser triangulation was proposed. First, the laser stripe information projected by the laser on the surface of the moving carriage full of coal gangue was continuously collected using the CCD camera. The target area of the image was extracted through median filtering method and threshold segmentation method based on Otsu algorithm during the image pre-process at the same time. Then the center line of the laser stripes were extracted using skeleton-based gray barycentric method. Finally, the Riemann integral method is used to calculate the coal gangue loading of the vehicle. The results show that the error of the system results is controlled within 4%, which meets the requirements of system operation, confirming the feasibility and practicability of the measurement method. This research provides a reference for the load measurement of highway transportation management in complex environments.
-
-
![]()
Figure 8. Volume calculation principle diagram
a—section of the carriage full of coal gangue b—Riemann method to calculate area
Table 1 Hardware selection parameter table
equipment laser CCD camera parameter characteristics wavelength：808nm image frame rate：288frame/s diode power：7000mW resolution：1280pixel×1024pixel beam power：5600mW pixel size：6.6μm×6.6μm lens fan angle：60° dynamic range：90dB 
下载: 导出CSV
-
[1] WU Y H. Current status and prospects of the disposal and utilization of coal gangue in my country[J]. China Environmental Protection Industry, 2019(1): 53-55(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTotal-ZHBY201901013.htm
[2] LIU K, MA Y D, HOU X K. Environmental hazards and comprehensive utilization status of coal gangue in my country[J]. Coal, 2013, 22(5): 59-61(in Chinese).
[3] WANG Zh J, SHENG W T, XIE J Y, et al. Research on cylindrical object positioning and measurement based on linear laser triangulation [J]. Laser Technology, 2019, 43(4): 28-34(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTotal-JGJS201904006.htm
[4] WANG Ch Y, HUANG T. Design and realization of indoor high-speed laser triangulation ranging technology[J]. Laser Technology, 2017, 41(6): 891-896(in Chinese).
[5] WEI Zh Zh, CAO L J, ZHANG G J. A novel 1-D target-based cali- bration method with unknown orientation for structured light vision sensor[J]. Optics and Laser Technology, 2009, 42(4): 570-574. http://www.sciencedirect.com/science/article/pii/S0030399209002175
[6] LI H Ch. Research on the material volume measurement method based on laser triangulation [D]. Hefei: Hefei University of Technology, 2015: 1-47(in Chinese).
[7] JIANG L. Laser triangulation displacement measurement system with dual optical path symmetry compensation [D]. Hangzhou: Zhejiang University, 2017: 1-6(in Chinese).
[8] ZHU Y. A three-dimensional profile measurement system based on laser triangulation[D]. Hefei: Hefei University of Technology, 2018: 1-8(in Chinese).
[9] MAO J H, LOU X P, LI W X, et al. Binocular 3-D volume measurement system based on line structured light[J]. Optics Technology, 2016, 42(1): 10-15(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTOTAL-GXJS201601003.htm
[10] LI P. Research on dynamic measurement system of bulk materials based on machine vision [D]. Beijing: China University of Mining and Technology, 2017: 19-26(in Chinese).
[11] LIU Y, SUN Sh Y. Laser point cloud filtering denoising based on principal component analysis and surface fitting[J]. Laser Technology, 2020, 44(4): 497-502(in Chinese).
[12] CAO G Q, LIU Y T, WANG L L. Improving the filtering processing of non-subsampled contour waves in speckle fringes[J]. Laser Technology, 2019, 43(2): 269-274(in Chinese).
[13] ZHOU Y K, ZHU Y P, ZENG B Z, et al. Overview of wide dynamic infrared image enhancement algorithms[J]. Laser Technology, 2018, 42(5): 718-726(in Chinese).
[14] GENG Q M, WU G X, XU X L, et al. Application of adaptive median filter and wavelet transform to dongba manuscript images denoising[C]//IEEE International Conference on Electronic Measurement & Instruments (ICEMI). New York, USA: IEEE, 2017: 942- 946.
[15] GONZALEZ R, WOODS R. Digital image processing[M]. 2nd ed. New Jersy, USA: Prentice Hall, 2002: 612-615.
[16] WANG H W, LIANG Y Y, WANG Zh H. Otsu image threshold segmentation method based on new genetic algorithm[J]. Laser Technology, 2014, 38(3): 364-367 (in Chinese). http://en.cnki.com.cn/Article_en/CJFDTOTAL-JGJS201403017.htm
[17] LI Zh H, GUO L, YAN J H, et al. Research on the algorithm for extracting the center of line structured light strip[J]. Journal of Inner Mongolia University of Science and Technology, 2019, 38(3): 252-257 (in Chinese).
[18] LIANG Y L, DUAN F J. A method for extracting the center line of light strips based on density clustering [J]. Laser Technology, 2020, 44(4): 459-465(in Chinese).
[19] HUANG L F, LIU G D, ZHANG Ch, et al. Laser stripe center extraction algorithm based on gray-scale weight model [J]. Laser Technology, 2020, 44(2): 190-195(in Chinese).
[20] LIU Ch J, LI B, GUO Y, et al. Research on fast extraction algorithm of light bar in real-time guidance of welding robot[J]. Laser Technology, 2015, 39(5): 642-647(in Chinese).
[21] WU Q Y. A study for key techniques of 3D-sensor based on line- structure light[D]. Chengdu: Sichuan University, 2006: 82-84(in Chinese).
计量
- 文章访问数: 8
- HTML全文浏览量: 1
- PDF下载量: 6