Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (12): 137-143.doi: 10.13475/j.fzxb.20200300607

• Machinery & Accessories • Previous Articles     Next Articles

Fast location of yarn-bars on yarn-cage based on machine vision

ZHANG Wenchang1,2, SHAN Zhongde1(), LU Ying2   

  1. 1. State Key Laboratory of Advanced Forming Technology and Equipment, China Academy of Machinery Science and Technology Group Co., Ltd., Beijing 100083, China
    2. Beijing National Innovation Institute of Lightweight Ltd., Beijing 100083, China
  • Received:2020-03-03 Revised:2020-05-15 Online:2020-12-15 Published:2020-12-23
  • Contact: SHAN Zhongde E-mail:shanzd@cam.com.cn

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Abstract:

In order to realize automatic, digital and intelligent production in textile dyeing industry, a vision based locating method was proposed for an eye-in-hand system aiming at the problem of location of dense yarn-bars on yarn-cage, combing the offline with online detection information. The offline detection unit recognized and located all the yarn-bars on yarn-cage during the machine idle time, and the location information of the yarn-bars was sent to the database. The online detection unit calculated the positions of all the yarn-bars on the yarn-cage, and guided the robot picking or putting objects on the yarn-bars in the productive time. For the online detection a few yarn-bars were detected firstly, and then a least square method were used to calculate the rotation angle and translation vector of the yarn-cage between its online position and offline position. All the positions of yarn-bars on yarn-cage were calculated using the data from the database. Experiment results show that the proposed method offers accuracy, robustness and practicality.

Key words: monocular vision, robot, yarn-cage, yarn-bar, least square method, offline detection, online detection

CLC Number: 

  • TS190.4

Fig.1

Vision robot of yarn-bars on yarn-cage. (a) General design structure; (b) Local structure"

Fig.2

Imaging model"

Fig.3

Yarn-bar recognition"

Fig.4

Manual selection of yarn-bar"

Fig.5

Offline detection flow"

Fig.6

Online detection view"

Fig.7

Online detection flow"

Fig.8

Structure of 120 yarn-bars"

Fig.9

Offline detection photo"

Fig.10

Contrasting figures of offline detection. (a) Picture for error detection and correction; (b) Picture after correction"

Tab.1

Online detection data"

检测
杆号		 数据库离线数据 在线检测结果
x y x y
1 1 764.25 911.10 1 771.43 910.95
13 825.60 1 081.24 832.95 1 080.92
77 499.43 1 958.34 507.62 1 958.27
120 1 103.05 2 696.04 1 112.03 2 695.90
108 2 049.63 2 558.20 2 057.70 2 557.63
44 2 376.87 1 661.00 2 384.67 1 660.22

Tab.2

Error of online detection"

杆号 误差 杆号 误差 杆号 误差 杆号 误差 杆号 误差
1 0.44 25 0.47 49 0.28 73 0.16 97 0.38
2 0.43 26 0.13 50 0.53 74 0.57 98 0.56
3 0.12 27 0.57 51 0.53 75 0.56 99 0.28
4 0.26 28 0.19 52 0.54 76 0.55 100 0.34
5 0.45 29 0.44 53 0.45 77 0.31 101 0.24
6 0.44 30 0.41 54 0.54 78 0.69 102 0.48
7 0.50 31 0.49 55 0.26 79 0.17 103 0.33
8 0.38 32 0.47 56 0.65 80 0.64 104 0.43
9 0.05 33 0.14 57 0.30 81 0.57 105 0.39
10 0.34 34 0.38 58 0.51 82 0.45 106 0.47
11 0.48 35 0.60 59 0.41 83 0.31 107 0.35
12 0.55 36 0.41 60 0.53 84 0.52 108 0.29
13 0.36 37 0.07 61 0.44 85 0.43 109 0.40
14 0.25 38 0.48 62 0.26 86 0.60 110 0.42
15 0.57 39 0.24 63 0.49 87 0.27 111 0.32
16 0.17 40 0.25 64 0.45 88 0.08 112 0.45
17 0.06 41 0.38 65 0.32 89 0.58 113 0.53
18 0.36 42 0.21 66 0.75 90 0.61 114 0.70
19 0.42 43 0.41 67 0.36 91 0.45 115 0.12
20 0.65 44 0.08 68 0.19 92 0.44 116 0.17
21 0.60 45 0.59 69 0.20 93 0.70 117 0.17
22 0.29 46 0.43 70 0.41 94 0.42 118 0.40
23 0.43 47 0.15 71 0.48 95 0.70 119 0.36
24 0.19 48 0.49 72 0.35 96 0.26 120 0.56

Tab.3

Online positioning detection data of yarn-bars with few count"

检测杆号 在线检测计算结果 120杆误差
θ/rad Tx/mm Ty/mm 平均值 最大值
1, 13 0.000 14 7.40 -0.41 1.01 1.95
1, 77 -0.000 43 7.07 0.38 0.45 0.91
1, 120 -0.000 89 6.48 1.13 0.47 0.97
13, 77, 120 -0.000 90 6.45 0.56 0.52 1.08
13, 77, 108 -0.000 40 7.13 0.13 0.43 0.96
13, 108, 44 -0.000 37 7.10 0.08 0.47 1.06
77, 120, 108,44 -0.000 48 7.19 0.34 0.40 0.87
1, 77, 120, 108 -0.000 57 6.95 0.54 0.40 0.82
13, 77, 108, 44 -0.000 39 7.15 0.12 0.43 0.82
1, 13, 77, 108, 44 -0.000 42 7.04 0.25 0.45 0.94
1, 13, 120, 108, 44 -0.000 61 6.79 0.60 0.41 0.75
13, 77, 120,108, 44 0.000 53 7.03 0.35 0.39 0.75
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