吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (10): 2847-2855.doi: 10.13229/j.cnki.jdxbgxb.20211347

• 交通运输工程·土木工程 • 上一篇    下一篇

基于图像处理的集料级配在线检测方法

荣鑫1(),刘洪海1(),殷作耀2,林海翔2,边庆华3   

  1. 1.长安大学 道路施工技术与装备教育部重点实验室,西安 710064
    2.福建省铁拓机械股份有限公司,福建 泉州 362000
    3.甘肃路桥建设集团有限公司 公路建设与养护技术、材料及装备交通运输行业研发中心,兰州 730030
  • 收稿日期:2021-12-07 出版日期:2023-10-01 发布日期:2023-12-13
  • 通讯作者: 刘洪海 E-mail:1414276521@qq.com;liuhonghai@chd.edu.cn
  • 作者简介:荣鑫(1994-),男,博士研究生. 研究方向:道路施工与装备.E-mail:1414276521@qq.com
  • 基金资助:
    国家重点研发计划项目(SQ2020YFF0413749);交通部交通运输行业重点科技项目(2018-199)

On-line detection method of aggregate gradation based on image processing

Xin RONG1(),Hong-hai LIU1(),Zuo-yao YIN2,Hai-xiang LIN2,Qing-hua BIAN3   

  1. 1.Key Laboratory of Road Construction Technology and Equipment,Ministry of Education,Chang'an University,Xi'an 710064,China
    2.Fujian Tietuo Machinery Co. Ltd. ,Quanzhou 362000,China
    3.Research and Development Center of Transport Industry of Technologies for Materials and Equipments of Highway Construction and Maintenance,Gansu Road& Bridge Construction Group Co. ,Ltd. ,Lanzhou 730030,China
  • Received:2021-12-07 Online:2023-10-01 Published:2023-12-13
  • Contact: Hong-hai LIU E-mail:1414276521@qq.com;liuhonghai@chd.edu.cn

摘要:

为了严格控制连续式搅拌设备冷料供给系统级配精度,研究了一种基于图像处理的集料级配在线检测方法。通过在冷料仓皮带处设置集料颗粒采集平台,在集料跌落的过程中对部分集料取样并分析此时的级配情况。采用分水岭与Harris结合算法对粘连颗粒进行分割,并综合200张图片集料级配分布情况得到最终的合成级配。利用EDEM软件仿真得到在集料取样占比基本相同时,分料板在不同的皮带速度下应调节到的最佳取样距离。筛分试验与本文方法的对比结果表明:本文方法与筛分法检测的结果相关性达到了 0.998,具有较好的检测效果。

关键词: 道路工程, 连续式搅拌站, 图像处理, 集料级配, EDEM仿真

Abstract:

In order to strictly control the grading accuracy of the continuous mixing equipment supply system, an online aggregate grading detection method based on image processing has been developed. By setting up an aggregate particle collection platform at the belt of the cold storage bin, part of the aggregate is sampled during the fall of the aggregate and the gradation situation at this time is analyzed. A watershed + Harris method is used to divide it and combine the results of 200 pictures to obtain the final synthetic gradation of the asphalt mixture. When the proportion of aggregate sampling is basically the same, the optimal sampling distance that the dividing plate should be adjusted to under different belt speeds is obtained by using EDEM software simulation. By comparing the results of the screening test and the image detection method,the correlation coefficient between the image method and the screening method detection result reached 0.998,which has a good detection effect.

Key words: road engineering, continuous mixing plant, image processing, aggregate grading, EDEM simulation

中图分类号: 

  • U416.2

图1

集料在皮带上的状态"

图2

集料跌落过程"

图3

集料图像采集平台"

图4

图像处理流程"

图5

11~17 mm颗粒图像处理过程"

图6

导入的集料输送及分散装置"

图7

分散网格单元"

图8

网格单元颗粒数目和皮带速度、分料板距离及取样比例三者关系"

表1

同一取样占比下皮带速度与分料板距离关系"

序号速度/(m?s-1分料板距离/m取样占比/%
11.00.1125.01
21.20.1224.44
31.40.1325.44
41.60.1426.02

图9

集料颗粒采集情况"

图10

AC-13不同档集料试验结果"

图11

AC-13合成级配筛分值与检测值"

图12

SMA-16不同档集料检测结果"

图13

SMA-16合成级配筛分值与检测值"

表2

AC-13不同档集料筛分与检测级配"

筛孔尺寸/mm4~7 mm筛分级配/%4~7 mm检测级配/%7~11 mm筛分级配/%7~11 mm检测级配/%11~17 mm筛分级配/%11~17 mm检测级配/%Ig
16.01001001001001001000
13.210010010010099.081000.92
9.510010099.510047.8549.522.17
4.7599.7210066.9569.241.142.624.06
2.3636.8139.241.263.320.611.245.11
1.182.644.120.861.930.60.82.75

表3

AC-13合成级配检测值"

筛孔尺寸/mm筛分试验/%图像检测方法/%Ig
16.01001000
13.292.2894.92.62
9.574.66761.34
4.7551.1450.11.04
2.3632.02330.98
1.1823.4622.90.56

表4

SMA-16不同档集料筛分与检测级配"

筛孔尺寸/mm

7~11 mm

筛分级配/%

7~11 mm

检测级配/%

11~17 mm筛分级配/%11~17 mm检测级配/%Ig
16.01001001001000
13.210010098.8999.991.1
9.599.8110064.8467.012.36
4.7572.4874.93.974.573.02
2.361.873.240.761.231.84
1.181.212.620.511.011.91

表5

SMA-16合成级配检测值"

筛孔尺寸/mm筛分试验/%图像检测方法/%Ig
16.01001000
13.279.8184.114.3
9.556.7154.52.21
4.7528.629.130.53
2.3621.8221.60.22
1.1817.3118.230.92
1 张鹏飞. 连续式强制拌和沥青混合料搅拌设备关键技术研究[D]. 西安:长安大学工程机械学院,2020.
Zhang Peng-fei. Study on key technologies of continuous forced asphalt mixing equipment[D]. Xi'an:College of Construction Machine, Chang'an University, 2020.
2 王艳敏. 一种沥青再生混合料连续式搅拌站的关键技术研究与试验分析[D]. 西安:长安大学工程机械学院,2017.
Wang Yan-min. Key technologies research and test analysis of a continuous asphalt mixing plant[D]. Xi'an:College of Construction Machine, Chang'an University, 2017.
3 李震. 连续式沥青搅拌设备性能特点研究[D]. 西安:长安大学工程机械学院,2017.
Li Zhen. Study on performance characteristics of continuous asphalt mixing plant[D]. Xi'an:College of Construction Machine, Chang'an University, 2017.
4 李强,许傲,陈浩,等. 级配和水泥掺量对泡沫沥青冷再生混合料路用性能的影响[J].铁道科学与工程学报,2021,18(2):402-407.
Li Qiang, Xu Ao, Chen Hao, et al. Effects of aggregate gradations and cement content on pavement performances of cold recycled mixture with formed asphalt[J]. Journal of Railway Science and Engineering, 2021, 18 (2):402-407.
5 程永春,李赫,李立顶,等. 基于灰色关联度的矿料对沥青混合料力学性能的影响分析[J]. 吉林大学学报:工学版,2021,51(3):925-935.
Cheng Yong-chun, Li He, Li Li-ding, et al. Analysis of mechanical properties of asphalt mixture affected by aggregate based on grey relational degree[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3):925-935.
6 李升连,梁乃兴,曾晟. 采集方法对数字图像沥青混合料离析评价影响研究[J]. 重庆交通大学学报:自然科学版,2021,40(3):103-107.
Li Sheng-lian, Liang Nai-xing, Zeng Sheng. Influence of acquisition methods on segregation evaluation of digital image of asphalt mixture[J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(3): 103-107.
7 王端宜, Thyagarajan Senthilmurugan. 基于CT技术的沥青混合料动态压实均匀性评价[J]. 长安大学学报:自然科学版,2010,30(6):24-28.
Wang Duan-yi, Thyagarajan Senthilmurugan. Homogeneity evaluation of compacted asphalt mixture based on X-ray computed tomography[J]. Journal of Chang'an University(Natural Science Edition), 2010, 30(6):24-28.
8 宋永朝,梁乃兴,闫功喜,等. 基于数字图像技术的露石混凝土路面纹理构造抗滑性能[J]. 哈尔滨工业大学学报,2015,47(2):123-128.
Song Yong-chao, Liang Nai-xing, Yan Gong-xi, et al. Skid-resistant performance of texture structure of exposed-aggregate cement concrete pavement based on digital image technology[J]. Journal of Harbin Institute of Technology, 2015, 47(2):123-128.
9 Bruno B Y, Parla L, Celauro G C. Image analysis for detecting aggregate gradation in asphalt mixture from planar images[J]. Construction and Building Materials, 2012, 28(1):21-30.
10 耿超. 基于图像处理的集料形态特征定量评价[J].公路交通科技,2018,35(12):42-47.
Geng Chao. Quantitative evaluation of morphological feature of aggregate based on image processing[J]. Journal of Highway and Transportation Research and Development, 2018, 35(12):42-47.
11 Baqersad Mohamadtaqi, Hamedi Amirmasoud, Mohammadafzali Mojtaba, et al. Asphalt mixture segregation detection: digital image processing approach[J]. Advances in Materials Science and Engineering, 2017, 23(4) No. 9493408.
12 彭勇,孙立军,王元清,等.数字图像处理在沥青混合料均匀性评价中的应用[J].吉林大学学报:工学版,2007,37(2):334-337.
Peng Yong, Sun Li-jun, Wang Yuan-qing, et al. Application of digital image processing in evaluation homogeneity of asphalt mixture[J]. Journal of Jilin University(Engineering and Technology Edition), 2007,37(2):334-337.
13 Cao Rong-ji, Zhao Yu-long, Gao Ying, et al. Effects of flow rates and layer thicknesses for aggregate conveying process on the prediction accuracy of aggregate gradation by image segmentation based on machine vision[J]. Construction and Building Materials, 2019, 222:566-578.
14 王奎,黄福珍. 基于光照补偿的HSV空间多尺度Retinex图像增强[J]. 激光与光电子学进展,2022,59(10):No.1010004.
Wang Kui, Huang Fu-zhen. Multi-scale Retinex image enhancement in HSV space based on illumination compensation[J]. Laser & Optoelectronics Progress, 2022,59(10):No.1010004..
15 徐鹏程. 再生砼砖混合集料破碎分形规律与路面基层或底基层用集料级配确定方法[D]. 太原:中北大学环境与安全工程学院,2019.
Xu Peng-cheng. Fractal law of crushing process of mixed recycled aggregates and reasonable gradation for pavement base or sub-base applications[D]. Taiyuan:College of Environment and Safety Engineering, North University of China, 2019.
[1] 肖明尧,李雄飞,朱芮. 基于NSST域像素相关分析的医学图像融合[J]. 吉林大学学报(工学版), 2023, 53(9): 2640-2648.
[2] 赵胜前,丛卓红,游庆龙,李源. 沥青-集料黏附和剥落研究进展[J]. 吉林大学学报(工学版), 2023, 53(9): 2437-2464.
[3] 金小俊,孙艳霞,于佳琳,陈勇. 基于深度学习与图像处理的蔬菜苗期杂草识别方法[J]. 吉林大学学报(工学版), 2023, 53(8): 2421-2429.
[4] 杨柳,王创业,王梦言,程阳. 设置自动驾驶小客车专用车道的六车道高速公路交通流特性[J]. 吉林大学学报(工学版), 2023, 53(7): 2043-2052.
[5] 周正峰,于晓涛,陶雅乐,郑茂,颜川奇. 基于灰色关联分析的树脂与弹性体高黏沥青高温性能评价[J]. 吉林大学学报(工学版), 2023, 53(7): 2078-2088.
[6] 马涛,马源,黄晓明. 基于多元非线性回归的智能压实关键参数最优解[J]. 吉林大学学报(工学版), 2023, 53(7): 2067-2077.
[7] 王宁,马涛,陈丰,付永强. 影响智能骨料感知的关键因素及数据分析方法[J]. 吉林大学学报(工学版), 2023, 53(6): 1799-1808.
[8] 黄晓明,赵润民. 道路交通基础设施韧性研究现状及展望[J]. 吉林大学学报(工学版), 2023, 53(6): 1529-1549.
[9] 张哲,付伟,张军辉,黄超. 循环荷载下冻融路基黏土长期塑性行为[J]. 吉林大学学报(工学版), 2023, 53(6): 1790-1798.
[10] 张青霞,侯吉林,安新好,胡晓阳,段忠东. 基于车辆脉冲响应的路面不平度识别方法[J]. 吉林大学学报(工学版), 2023, 53(6): 1765-1772.
[11] 姜屏,陈业文,陈先华,张伟清,李娜,王伟. 改性石灰土在干湿和冻融循环下的无侧限抗压性能[J]. 吉林大学学报(工学版), 2023, 53(6): 1809-1818.
[12] 司春棣,崔亚宁,许忠印,凡涛涛. 层间粘结失效后桥面沥青铺装层细观力学行为分析[J]. 吉林大学学报(工学版), 2023, 53(6): 1719-1728.
[13] 李岩,张久鹏,陈子璇,黄果敬,王培. 基于PCA-PSO-SVM的沥青路面使用性能评价[J]. 吉林大学学报(工学版), 2023, 53(6): 1729-1735.
[14] 刘状壮,郑文清,郑健,李轶峥,季鹏宇,沙爱民. 基于网格化的路表温度感知技术[J]. 吉林大学学报(工学版), 2023, 53(6): 1746-1755.
[15] 赵晓康,胡哲,张久鹏,裴建中,石宁. 基于光纤传感技术的路面结冰智能监测研究进展[J]. 吉林大学学报(工学版), 2023, 53(6): 1566-1579.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!