Knitting needle fault detection system for hosiery machine based on laser detection and machine vision

2020 ◽  
Vol 91 (1-2) ◽  
pp. 143-151
Author(s):  
Zhouqiang Zhang ◽  
Sihao Bai ◽  
Guang-shen Xu ◽  
Xuejing Liu ◽  
Jiangtao Jia ◽  
...  
Keyword(s):  
Fault Detection ◽  
Machine Vision ◽  
Detection System ◽  
Production Quality ◽  
Image Region ◽  
Charge Coupled Device ◽  
Laser Detection ◽  
Laser Signal ◽  
A Charge ◽  
Size Classifier

The knitting needle cylinder is one of the core parts of a hosiery machine. The operation of its needles can directly affect the production quality and efficiency of the hosiery machine. To reduce the production loss of a hosiery machine caused by knitting needle faults, a knitting needle fault detection system for hosiery machines based on a synergistic combination of laser detection and machine vision is proposed in this paper. When the system was operating normally, a photoelectric detector collected the laser signal reflected by the knitting needle and the system monitored the operation of the knitting needle using the ratio of adjacent peak-to-peak distances of the signals. When a fault signal was detected, the hosiery machine was stopped by the system immediately, and a charge-coupled device camera was used to take an image of the faulty knitting needle. After image preprocessing, the faulty knitting needle could be identified quickly and accurately using an image region size classifier based on a decision tree. The experimental results showed that a single image classification by the classifier could be performed in as little as 0.002 s.

scholarly journals The Inspection of Raw- Silk Defects Using Image Vision

2018 ◽  
Vol 13 (3) ◽  
pp. 155892501801300 ◽  
Author(s):  
Qingtian Pan ◽  
Miao Chen ◽  
Baoqi Zuo ◽  
Yucai Hu
Keyword(s):  
Detection System ◽  
Image Sensor ◽  
Support Vector ◽  
Technological Parameters ◽  
Image Capture ◽  
Charge Coupled Device ◽  
The Moment ◽  
A Charge ◽  
Ccd Image

The inspection of defects is one of the most important aspects in the quality inspection of raw silk. We introduce a raw-silk defect detection system based on image vision and image analysis that is accurate and objective. In the experimental phase, we develop an image-acquisition section—which includes a charge-coupled device (CCD) image sensor, a telecentric lens, a light source, and a raw-silk winding device to capture the raw silk images steadily. After the image capture stage, an image-processing section tasked with threshold segmentation and morphology operations is carried out to obtain the defects of raw silk. To classify the raw-silk defects accurately and quickly, we propose an area method for the classification of raw-silk defects into five categories: larger defects, large defects, common defects, small defects, and smaller defects. Meanwhile, in order to recognize the common raw-silk defects—e.g., Bavella silk, nodes, and loose ends—that cannot be detected by the Uster evenness tester, the moment invariants of each segmented region of the images are extracted and used as the input of support vector machine(SVM).A SVM is designed as a classifier to recognize the samples. The experimental results show that the proposed method can recognize these common raw-silk defects effectively. According to the new classification and accurate recognition of raw-silk defects using the proposed method, we can improve the inspection standards for raw silk and advise raw-silk reeling enterprises seeking to optimize the technological parameters.

Use of a CCD-Based Area Detection System on a Fibre Diffractometer

1994 ◽  
Vol 38 ◽  
pp. 503-510 ◽  
Author(s):  
S. Hanna ◽  
A.H. Windle
Keyword(s):  
Detection System ◽  
Single Point ◽  
Video Camera ◽  
Reciprocal Space ◽  
Charge Coupled Device ◽  
X Ray ◽  
Complete Section ◽  
Ewald Sphere ◽  
Pros And Cons ◽  
A Charge

Abstract We describe a new X-ray fibre diffractometer, consisting of a commercial X-ray sensitive video camera coupled to a conventional 3-circle goniometer in place of a more traditional single-point detector. The active element of the video camera is a charge-coupled device (CCD). Diffraction images, obtained at various goniometer settings, are transformed into reciprocal space, and combined to give a complete section through the origin and parallel to the symmetry axis of cyiindrically averaged reciprocal space. A greater density of measurements is needed in the vicinity of the reciprocal fibre axis in order to avoid information loss due to the curvature of the Ewald sphere. The pros and cons of using CCD's as X-ray detectors are discussed and sample results from polymer fibres are shown.

A new machine-vision-based approach for rapid dimensional inspection of an integrated circuit carrier tape

2009 ◽  
Vol 223 (3) ◽  
pp. 145-154
Author(s):  
S-H Chen ◽  
T-T Liao ◽  
C-T Chen
Keyword(s):  
Machine Vision ◽  
Integrated Circuit ◽  
Ccd Camera ◽  
Light Sources ◽  
Charge Coupled Device ◽  
Lighting Conditions ◽  
Environmental Lighting ◽  
Canny Edge ◽  
Edge Detection Method ◽  
A Charge

This study presents a rapid and reliable machine vision technique for measuring the principal features of interest in an integrated circuit carrier tape, namely the diameters of the circular sprocket perforations and centre hole, the width of the carrier tape, and the width and length of the centre cavity. In performing the measurement process, the quality of the image acquisition process is enhanced by using two auxiliary light sources to suppress the effects of natural variations in the environmental lighting conditions. Having acquired the image using a charge coupled device (CCD) camera, the features of interest are separated from the background region of the image using a two-threshold algorithm based on the Otsu threshold selection method. The edge of each feature is then extracted from the binary image using the Canny edge detection method. The dimensions of the circular features are obtained by fitting four right-angle triangles within the periphery of the extracted circular edge and then computing the circle diameter by taking the mean of the hypotenuse values of the four triangles as computed using the Pythagorean theorem.

Development and characterization of a charge‐coupled device detection system for ion microscopy

1989 ◽  
Vol 60 (5) ◽  
pp. 886-894 ◽  
Author(s):  
Lisa K. Turner ◽  
David S. Mantus ◽  
Yong‐Chien Ling ◽  
Mark T. Bernius ◽  
George H. Morrison
Keyword(s):  
Detection System ◽  
Charge Coupled Device ◽  
Ion Microscopy ◽  
A Charge

Machine Vision-Based Automatic Placement System for Solenoid Housing

2015 ◽  
Vol 649 ◽  
pp. 9-13 ◽  
Author(s):  
Chao Ching Ho ◽  
You Min Chen ◽  
Tien Yun Chi ◽  
Tzu Hsin Kuo
Keyword(s):  
Machine Vision ◽  
Target Object ◽  
Solenoid Coil ◽  
Charge Coupled Device ◽  
Image Preprocessing ◽  
Automatic Placement ◽  
Operator Fatigue ◽  
Delta Robot ◽  
A Charge ◽  
Homography Transformation

This paper proposes a machine vision-based, servo-controlled delta robotic system for solenoid housing placement. The system consists of a charge-coupled device camera and a delta robot. To begin the placement process, the solenoid housing targets inside the camera field were identified and used to guide the delta robot to the grabbing zone according to the calibrated homography transformation. To determine the angle of solenoid housing, image preprocessing was then implemented in order to rotate the target object to assemble with the solenoid coil. Finally, the solenoid housing was grabbed automatically and placed in the collecting box. The experimental results demonstrate that the proposed system can help to reduce operator fatigue and to achieve high-quality placements.

Surface Roughness Measuring System Design for Cutting Workpiece Based on Machine Vision Technology

2011 ◽  
Vol 128-129 ◽  
pp. 434-438
Author(s):  
Ming Zhu ◽  
Qi Yong Zeng ◽  
Kai Wu ◽  
Tao Hong ◽  
Xiao Feng Zheng
Keyword(s):  
Surface Roughness ◽  
Machine Vision ◽  
Ccd Camera ◽  
Measuring System ◽  
Charge Coupled Device ◽  
Workpiece Surface ◽  
Surface Image ◽  
Processing Module ◽  
Image Characteristic ◽  
A Charge

A new method for workpiece surface roughness measuring system based on machine vision technology was designed. A Charge-coupled Device （CCD） camera was used to take workpiece surface image. Then median filtering, image enhancement and image binarization techniques were used for image preprocessing. And then useful information was extracted from image characteristic parameters. The surface roughness of cutting workpiece was calculated out. Researching emphasis was focused on the hardware design and software programming of the main two parts, image acquisition module and image processing module. This measuring system was used to measure cutting workpiece surface roughness, and perform very well.

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