scholarly journals Adaptive Algorithm for the Quality Control of Braided Sleeving

2014 ◽  
Vol 6 ◽  
pp. 812060 ◽  
Author(s):  
Miha Pipan ◽  
Andrej Kos ◽  
Niko Herakovic
Keyword(s):  
Quality Control ◽  
Machine Vision ◽  
Adaptive Algorithm ◽  
Vision System ◽  
Robot Vision ◽  
Measuring Method ◽  
Industrial Applications ◽  
Visual Observation ◽  
Pipe Surface ◽  
Different Types

We describe the development and application of a robot vision based adaptive algorithm for the quality control of the braided sleeving of high pressure hydraulic pipes. With our approach, we can successfully overcome the limitations, such as low reliability and repeatability of braided quality, which result from the visual observation of the braided pipe surface. The braids to be analyzed come in different dimensions, colors, and braiding densities with different types of errors to be detected, as presented in this paper. Therefore, our machine vision system, consisting of a mathematical algorithm for the automatic adaptation to different types of braids and dimensions of pipes, enables the accurate quality control of braided pipe sleevings and offers the potential to be used in the production of braiding lines of pipes. The principles of the measuring method and the required equipment are given in the paper, also containing the mathematical adaptive algorithm formulation. The paper describes the experiments conducted to verify the accuracy of the algorithm. The developed machine vision adaptive control system was successfully tested and is ready for the implementation in industrial applications, thus eliminating human subjectivity.

MACHINE VISION 1992–1996, TECHNOLOGY PROGRAM IN FINLAND

1996 ◽  
Vol 10 (01) ◽  
pp. 3-13 ◽  
Author(s):  
ANTTI J. SOINI
Keyword(s):  
Machine Vision ◽  
Manufacturing Industry ◽  
Technology Development ◽  
New Technology ◽  
Robot Vision ◽  
Industrial Applications ◽  
Technology Program ◽  
Research Organizations ◽  
Innovative Products ◽  
New Business

Machine vision technology has attracted a strong interest among Finnish research organizations, which has resulted in many innovative products for industry. Despite this goal users were very skeptical towards machine vision and its robustness in harsh industrial environments. Therefore the Technology Development Centre, TEKES, which funds technology related research and development projects in universities and individual companies in Finland, decided to start a national technology program, "Machine Vision 1992–1996". Led by industry, the program boosts research in machine vision technology and seeks to put the research results to work in practical industrial applications. The emphasis is on nationally important, demanding applications. The program will create new business for machine vision producers and encourage the process and manufacturing industry to take advantage of this new technology. So far 60 companies and all major universities and research centers in Finland are working on our forty different projects. The key themes are Process Control, Robot Vision and Quality Control.

Vision Based Fault Detection of Automated Assembly Equipment

2011 ◽  
Author(s):  
Greg Szkilnyk ◽  
Kevin Hughes ◽  
Brian Surgenor
Keyword(s):  
Machine Vision ◽  
Manufacturing Industry ◽  
Vision System ◽  
Machine Vision System ◽  
Automated Assembly ◽  
Central Controller ◽  
Different Types ◽  
Machine Health ◽  
Future Work ◽  
Overall Effectiveness

Machine faults and breakdowns are a concern for the manufacturing industry. Automated assembly machines typically employ many different types of sensors to monitor machine health and feedback faults to a central controller for review by a technician or engineer. This paper describes progress with a project whose goal is to examine the effectiveness of using machine vision to detect ‘visually cued’ faults in automated assembly equipment. Tests were conducted on a laboratory scale conveyor apparatus that assembles a simple 3-part component. The machine vision system consisted of several conventional webcams and image processing in LabVIEW. Preliminary results demonstrated that the machine vision system could identify faults such as part jams and feeder jams; however the overall effectiveness was limited as this technique can only detect faults known prior to creating the vision system. Future work to create a more robust system is currently underway.

A Fast and Precise Measuring Method for Large Workpiece Based on Machine Vision

2010 ◽  
Vol 139-141 ◽  
pp. 2076-2081 ◽  
Author(s):  
Hu Zhou ◽  
Jian Guo Yang
Keyword(s):  
Machine Vision ◽  
Template Matching ◽  
Vision System ◽  
Measuring Method ◽  
Search Space ◽  
Field Of View ◽  
Image Mosaic ◽  
Machine Vision System ◽  
Stop Criterion ◽  
Machine Parts

Image measurement based on machine vision is a promising method for the precise measurements of machine parts. As for a large sized workpiece that exceeds the FOV (field of view) of the camera, image mosaic must be performed to implement measurement. While traditional template matching algorithms will lead to long runtime consumption, a combination of algorithms with precise mechanical positioning function using motion control was proposed and applied in the machine vision system. The manufacturing and installing errors have been taken into account to improve the positioning accuracy. This method minimized the search space and thereby reduced the runtime substantially. In addition, a stop criterion of the computation for the algorithms was applied to save a considerable amount of time in the process. Experimental results show that the precision of the image mosaic meets the requirements while speeding up the process significantly.

A Machine Vision System for Inspecting Hydraulic Hose Assemblies

1994 ◽  
Author(s):  
Sudhir I. Mehta ◽  
Bruce B. Chenoweth
Keyword(s):  
Quality Control ◽  
Machine Vision ◽  
Human Error ◽  
Vision System ◽  
Control Process ◽  
Shop Floor ◽  
Machine Vision System ◽  
Quality Control Process

Abstract This paper describes a machine vision system for inspecting hydraulic hose assemblies. At present the inspection in this industry is done manually and is prone to human error. A specially designed hose gripping mechanism, a mandrel system, and a camera and lighting fixture allows the system to be integrated on a shop floor and is able to inspect various parameters of a fitting. The system allows the inspection to be done more accurately and improves the quality control process.

Research on Boundary Detection for Turnout Rail Components Based on Machine Vision

2013 ◽  
Vol 303-306 ◽  
pp. 617-620 ◽  
Author(s):  
Yan Dou ◽  
Yu Qian Zheng
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Boundary Detection ◽  
Detection Algorithm ◽  
Visual Observation ◽  
Machine Vision System ◽  
Human Beings ◽  
Size Measurement ◽  
Energy Diagram ◽  
Binarization Method

Boundary detection is very important in the size measurement of the turnout rail components using machine vision. A new algorithm about boundary detection based on machine vision system is proposed. First an improved median filtering algorithm was used to noise reduction an image. Second Gabor operator energy diagram is generated. Then an elliptical-butterfly surround inhibition was designed to suppress the textures and enhance the boundary. Last a new binarization method and boundary detection algorithm is put forward according to the human beings visual observation. Experimental results show that the algorithm has good feasibility and effectiveness.

Study on the Detection and Selection of Bearing Diameter Based on Machine Vision System

2014 ◽  
Vol 533 ◽  
pp. 298-302
Author(s):  
Fu Sheng Yu ◽  
Sheng Jiang Yin ◽  
Teng Fei Li ◽  
Zhong Guo Sun ◽  
Wei Kang Shi
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Three Dimensional ◽  
Movement Control ◽  
Ccd Camera ◽  
Measuring Method ◽  
Machine Vision System ◽  
Technology Roadmap ◽  
Precision Measuring ◽  
Control Units

A new method and system for inspecting the bearing diameter is developed. The mechanical and movement control units, as well as its machine vision system, are designed. A precision measuring method based on machine vision system is developed to measure bearing diameter. Computer outputs the bearing edge contour and its three-dimensional coordinates after image processing software process the image of bearings which are collected by CCD camera. The controller controls the operation of motor by ball screws and drives the movement of individual parts which can crawls the gripper in the three-dimensional coordinates. Inductive gage is used to measure bearing diameter. Besides, a technology roadmap of image edge character detection is analyzed .Gaussian filter is used to noise reduction of the image and canny operator is used to edge detection. Template match is adapted to the automatic recognition of bearing characteristics. The paper may be helpful to those who work on the same subject in future.

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