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Chin J Eng Design  2022, Vol. 29 Issue (6): 784-792    DOI: 10.3785/j.issn.1006-754X.2022.00.078
Whole Machine and System Design     
Design of a control system of plane machining machine tool based on machine vision
Sheng-hu PAN(),Xiao-jun ZHANG,Dong Lü
School of Mechatronics Engineering, Southwest Petroleum University, Chengdu 610500, China
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Abstract  

In order to solve the problems of long processing cycle and low production efficiency caused by inputting the size information of manually measured paper drawings or model samples into the computer and converting it into electronic processing drawings in garment, packaging and other processing industries, a control system of plane machining machine tool based on machine vision was proposed to realize the rapid detection of paper drawings or model samples. The master-slave motion control system was built by using "ARM+DSP" mode, and the functional modules of each part of the system were designed. A visual detection system of "industrial computer+industrial CCD (charge coupled device) camera+light source control" was built. An improved FAWS (feature adaptive wavelet shrinkage) algorithm was proposed by combining the FAWS algorithm and the sparrow search algorithm to reduce image noise, and the Canny algorithm was used to complete achieve image edge detection so as to achieve the accurate extraction of image contour. The processing programs of image contour extraction, contour data conversion to processing data, data communication, etc. were designed to realize rapid detection based on machine vision and human-computer interaction in the system processing process. Finally, the system was tested and the actual machining effect was evaluated. The results showed that the proposed control system of plane machining machine tool could not only significantly improve the production efficiency, but also reduce the error of image contour. Its performance is stable and reliable, and has certain engineering practical value.



Key wordsplane processing machine tool      visual detection      image processing      FAWS (feature adaptive wavelet shrinkage) algorithm      sparrow search algorithm      Canny algorithm     
Received: 13 October 2021      Published: 06 January 2023
CLC:  TP 274  
Cite this article:

Sheng-hu PAN,Xiao-jun ZHANG,Dong Lü. Design of a control system of plane machining machine tool based on machine vision. Chin J Eng Design, 2022, 29(6): 784-792.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2022.00.078     OR     https://www.zjujournals.com/gcsjxb/Y2022/V29/I6/784


一种基于机器视觉的平面加工机床控制系统的设计

针对服装、包装等加工行业中须将人工测量的纸质图纸或模型样件的尺寸信息录入计算机并转换成电子加工图纸而导致的加工周期长、生产效率低的问题,提出了一种基于机器视觉的平面加工机床控制系统,以实现对纸质图纸或模型样件的快速检测。采用“ARM+DSP”方式搭建了主从式运动控制系统,设计了系统各部分功能模块。构建了“工控机+工业CCD (charge coupled device,电荷耦合器件)相机+光源控制”的视觉检测系统,结合FAWS(feature adaptive wavelet shrinkage, 自适应特征的小波收缩)算法和麻雀搜索算法提出一种改进的FAWS算法进行图像降噪,并采用Canny算法进行图像边缘检测,实现图像轮廓的准确提取。设计了图像轮廓提取、轮廓数据转换为加工数据、数据通信等处理程序,实现了基于机器视觉的快速检测以及在系统加工过程中的人机交互。最后,对系统进行了实验测试,对实际加工效果进行了评价。结果表明,采用所研制的平面加工机床控制系统不仅能显著提高生产效率,而且能减小图像轮廓的误差。其性能稳定可靠,具有一定的工程实用价值。


关键词: 平面加工机床,  视觉检测,  图像处理,  FAWS (feature adaptive wavelet shrinkage,自适应特征的小波收缩)算法,  麻雀搜索算法,  Canny算法 
Fig.1 Control system structure of plane machining machine tool based on machine vision
Fig.2 Function module of control system of plane machining machine tool based on machine vision
Fig.3 Hardware connection of main control unit of motion control module
Fig.4 Communication structure of RS232 standard serial port equipment
Fig.5 Circuit diagram of limit signal control
Fig.6 Circuit diagram of motor control interface
Fig.7 Noise reduction effect of improved FAWS algorithm
Fig.8 Change curve of fitness value of improved FAWS algorithm
Fig.9 Fitness values corresponding to different p and q
Fig.10 Comparison of noise reduction effects between Gaussian filtering and improved FAWS algorithm
指令代表意义参数
IN初始化
SPr选择第r号刀笔r
PU抬刀至(x, y)位置坐标(x, y
PD下刀至(x, y)位置坐标(x, y
DI绝对方向
DR相对方向
Table 1 Common PLT instructions
Fig.11 Experimental platform of plane machining machine tool control system based on machine vision
Fig.12 Test flow of control system of plane processing machine tool
测量组

原图轮廓

间距/mm

加工后轮廓间距/mm

绝对误差/

mm

相对误差/

%

154.0054.20+0.20+0.37
211.5011.65+0.15+1.30
394.0094.30+0.30+0.32
463.0062.90-0.10-0.16
526.0026.25+0.25+0.96
637.5037.55+0.05+0.13
768.0068.20+0.20+0.29
845.0044.70-0.30-0.67
917.0017.10+0.10+0.59
1038.0037.85-0.15-0.39
1142.5042.75+0.25+0.59
1274.0074.30+0.30+0.41
1359.0059.15+0.15+0.25
Table 2 Distance and error of image contour before and after processing
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