基于图像处理的集料级配在线检测方法

doi:10.13229/j.cnki.jdxbgxb.20211347

Abstract

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

CLC Number:

U416.2

Xin RONG,Hong-hai LIU,Zuo-yao YIN,Hai-xiang LIN,Qing-hua BIAN. On-line detection method of aggregate gradation based on image processing[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(10): 2847-2855.

Figures/Tables 18

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Table 1

Relationship between belt speed and distance of distributor plate for the same sampling ratio"

序号	速度/（ $m ? s - 1$ ）	分料板距离/m	取样占比/%
1	1.0	0.11	25.01
2	1.2	0.12	24.44
3	1.4	0.13	25.44
4	1.6	0.14	26.02

Table 1

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Table 2

AC-13 different grades of aggregate screening and detection gradation"

筛孔尺寸/mm	4~7 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/%	$I g$
16.0	100	100	100	100	100	100	0
13.2	100	100	100	100	99.08	100	0.92
9.5	100	100	99.5	100	47.85	49.52	2.17
4.75	99.72	100	66.95	69.24	1.14	2.62	4.06
2.36	36.81	39.24	1.26	3.32	0.61	1.24	5.11
1.18	2.64	4.12	0.86	1.93	0.6	0.8	2.75

Table 2

Table 3

AC-13 synthetic gradation detection value"

筛孔尺寸/mm	筛分试验/%	图像检测方法/%	$I g$
16.0	100	100	0
13.2	92.28	94.9	2.62
9.5	74.66	76	1.34
4.75	51.14	50.1	1.04
2.36	32.02	33	0.98
1.18	23.46	22.9	0.56

Table 3

Table 4

SMA-16 different grades of aggregate screening and detection gradation"

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/%	$I g$
16.0	100	100	100	100	0
13.2	100	100	98.89	99.99	1.1
9.5	99.81	100	64.84	67.01	2.36
4.75	72.48	74.9	3.97	4.57	3.02
2.36	1.87	3.24	0.76	1.23	1.84
1.18	1.21	2.62	0.51	1.01	1.91

Table 4

Table 5

SMA-16 synthetic grade detection value"

筛孔尺寸/mm	筛分试验/%	图像检测方法/%	$I g$
16.0	100	100	0
13.2	79.81	84.11	4.3
9.5	56.71	54.5	2.21
4.75	28.6	29.13	0.53
2.36	21.82	21.6	0.22
1.18	17.31	18.23	0.92

Table 5

References 15

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.

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

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