Optimization of acquisition parameters of slurry coating characteristics based on multiple yarn simultaneous detection

2021 ◽  
pp. 004051752110408
Author(s):  
Wenjun Yan ◽  
Bo Zhu ◽  
Weidong Gao
Keyword(s):  
Image Processing ◽  
Spatial Resolution ◽  
Detection Method ◽  
Simultaneous Detection ◽  
Processing Parameters ◽  
Threshold Method ◽  
Illumination Time ◽  
Slurry Coating ◽  
Coating Characteristics ◽  
Efficiency Test

A simultaneous detection method was proposed to detect slurry coating characteristics based on the same spatial resolution of starch-based sized and raw yarns. A dynamic image acquisition device was improved to capture the apparent images of multiple yarns simultaneously after the starch–iodine color reaction. The slurry coating characteristics were calculated utilizing image-processing technology. For the sake of effective and stable detection, the effects of illumination conditions on the concentration of I2-KI solution were studied through the absorbance value test. The effects of image-processing parameters on the experimental results were analyzed respectively by measuring six kinds of yarn of different counts and size pick-up. The results showed that the illumination conditions within an illumination time of 0–60 min, illumination intensity of 0–80,000 lux and illumination distance of 0.01–0.20 m had no significant effects on the concentration of I2-KI solution. Eight rows of pixels in the central axis areas of the yarn were determined as the effective statistical areas. It was determined that the sample size can meet the needs of stability test in 200 pieces. A dynamic threshold method, which served the intersection of the gray histogram of sized and raw yarn under the same spatial resolution as the threshold, can effectively segment the slurry coating areas. On the above basis, the optimization acquisition parameters of the detection method were obtained. The proposed method can meet the requirements of the efficiency test, common applicability and ease of operation.

A novel method for evaluating the slurry coating characteristics of sized yarns based on the starch-iodine color reaction principle and image processing

2020 ◽  
pp. 004051752098080
Author(s):  
Wenjun Yan ◽  
Bo Zhu ◽  
Jianli Liu ◽  
Weidong Gao
Keyword(s):  
Image Processing ◽  
Immersion Time ◽  
Test System ◽  
Color Reaction ◽  
Textile Mills ◽  
Slurry Coating ◽  
Acquisition Device ◽  
Coating Characteristics ◽  
Low Efficiency ◽  
The Stability

The slurry coating characteristics of sized yarns directly impact warp weavability. Due to the damage to sized films, the conventional methods of detecting sized-yarn coating characteristics have drawbacks of low efficiency and poor repeatability. A novel detecting method of slurry coating characteristics was proposed based on image processing. Through the starch-iodine color reaction principle, a self-made dynamic image acquisition device was developed in this paper, in which the apparent images of starch-based sized yarns after color reaction were captured consecutively. The slurry coating percentage ( SCP), slurry coating depth ( SCD) and slurry coating unevenness ( SCU), respectively reflecting the sizing coating integrity, sizing coating thickness and thickness unevenness, were extracted by image processing. The effects of experimental parameters, including immersion time and concentration of I2-KI solution, on slurry coating characteristics were analyzed, and central composite design was adopted to optimize the stability of the test system. Sized yarns commonly used in textile mills were characterized by the proposed method. The experimental results indicated that immersion time of 3.56 min and I2-KI concentration of 0.11‱ (‱ represents that the mass of the solute is one ten-thousandth of solution) led to the optimal stability of slurry coating characteristics (the CV of SCP, CV of SCD and CV of SCU were 3.32%, 5.56% and 9.37%, respectively). The much lower CV of the proposed method compared with conventional ones confirmed that the method was useful for evaluating slurry coating characteristics.

Image detection and parameterization for different components in cross-sections of radial tires

2021 ◽  
pp. 095440702110236
Author(s):  
Chen Liu ◽  
Yude Dong ◽  
Yanli Wei ◽  
Jiangtao Wang ◽  
Hongling Li
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Cross Sections ◽  
Digital Image ◽  
Detection Method ◽  
Detection System ◽  
Practical Significance ◽  
Vehicle Safety ◽  
Wire Steel ◽  
Good Detection

The internal structure analysis of radial tires is of great significance to improve vehicle safety and during tire research. In order to perform the digital analysis and detection of the internal composition in radial tire cross-sections, a detection method based on digital image processing was proposed. The research was carried out as follows: (a) the distribution detection and parametric analysis of the bead wire, steel belt, and carcass in the tire section were performed by means of digital image processing, connected domain extraction, and Hough transform; (b) using the angle of location distribution and area relationship, the detection data were optimized through coordinate and quantity relationship constraints; (c) a detection system for tire cross-section components was designed using the MATLAB platform. Our experimental results showed that this method displayed a good detection performance, and important practical significance for the research and manufacture of tires.

Enhanced photocatalytic activity of CeO2 using β-cyclodextrin on visible light assisted decoloration of methylene blue

2013 ◽  
Vol 69 (1) ◽  
pp. 113-119 ◽  
Author(s):  
Sakthivel Pitchaimuthu ◽  
Ponnusamy Velusamy
Keyword(s):  
Methylene Blue ◽  
Photocatalytic Activity ◽  
Visible Light ◽  
Inclusion Complexation ◽  
Processing Parameters ◽  
Operational Parameters ◽  
Illumination Time ◽  
Operational Conditions ◽  
Electron Microscopy Analysis ◽  
Initial Ph

An attempt has been made to enhance the photocatalytic activity of CeO2 for visible light assisted decoloration of methylene blue (MB) dye in aqueous solutions by β-cyclodextrin (β-CD). The inclusion complexation patterns between host and guest (i.e., β-CD and MB) have been confirmed with UV–visible spectral data. The interaction between CeO2 and β-CD has also been characterized by field emission scanning electron microscopy analysis. The photocatalytic activity of the catalyst under visible light was investigated by measuring the photodegradation of MB in aqueous solution. The effects of key operational parameters such as initial dye concentration, initial pH, CeO2 concentration as well as illumination time on the decolorization extents were investigated. Among the processing parameters, the pH of the reaction solution played an important role in tuning the photocatalytic activity of CeO2. The maximum photodecoloration rate was achieved at basic pH (pH 11). Under the optimum operational conditions, approximately 99.6% dye removal was achieved within 120 min. The observed results indicate that the decolorization of the MB followed a pseudo-first order kinetics.

scholarly journals Seasonal cycle of cloud cover analyzed using Meteosat images

1998 ◽  
Vol 16 (3) ◽  
pp. 331-341 ◽  
Author(s):  
J. Massons ◽  
D. Domingo ◽  
J. Lorente
Keyword(s):  
Spatial Resolution ◽  
Seasonal Cycle ◽  
Cloud Cover ◽  
High Spatial Resolution ◽  
Detection Method ◽  
Cloud Amount ◽  
Cloud Detection ◽  
Total Cloud Amount ◽  
Cloud Parameters ◽  
Cloud Properties

Abstract. A cloud-detection method was used to retrieve cloudy pixels from Meteosat images. High spatial resolution (one pixel), monthly averaged cloud-cover distribution was obtained for a 1-year period. The seasonal cycle of cloud amount was analyzed. Cloud parameters obtained include the total cloud amount and the percentage of occurrence of clouds at three altitudes. Hourly variations of cloud cover are also analyzed. Cloud properties determined are coherent with those obtained in previous studies.Key words. Cloud cover · Meteosat

Detection of Microbubbles Using the Hough Transform

2013 ◽  
Vol 378 ◽  
pp. 478-482
Author(s):  
Yoshihiro Mitani ◽  
Toshitaka Oki
Keyword(s):  
Image Processing ◽  
Error Rate ◽  
Hough Transform ◽  
Detection Method ◽  
Experimental Results ◽  
Average Error ◽  
Image Processing Techniques ◽  
Average Error Rate ◽  
Processing Techniques

The microbubble has been widely used and shown to be effective in various fields. Therefore, there is an importance of measuring accurately its size by image processing techniques. In this paper, we propose a detection method of microbubbles by the approach based on the Hough transform. Experimental results show only 4.49% of the average error rate of the undetected microbubbles and incorrectly detected ones. This low percentage of the error rate shows the effectiveness of the proposed method.

Application of Improved Back Propagation Neural Network for the Recognition of Composite Insulator Hydrophobicity Grade

2013 ◽  
Vol 373-375 ◽  
pp. 1155-1158
Author(s):  
Kang Yan ◽  
Zhong Yuan Zhang
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Median Filter ◽  
Back Propagation ◽  
Histogram Equalization ◽  
Back Propagation Neural Network ◽  
Threshold Method ◽  
Safe Operation ◽  
Composite Insulator ◽  
Adaptive Median Filter

The detection of hydrophobicity is an important way to evaluate the performance of composite insulator, which is helpful to the safe operation of composite insulator. In this paper, the image processing technology and Back Propagation neural network is introduced to recognize the composite insulator hydrophobicity grade. First, hydrophobic image is preprocessed by histogram equalization and adaptive median filter, then the image was segmented by Ostu threshold method, and four features associated with hydrophobicity are extracted. Finally, the improved Back Propagation neural network is adopted to recognize composite insulator hydrophobicity grade. The experimental results show that the improved Back Propagation neural network can accurately recognize the composite insulator hydrophobicity

scholarly journals Cement Pavement Surface Crack Detection Based on Image Processing

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Hongwei Lei ◽  
Jianlian Cheng ◽  
Qi Xu
Keyword(s):  
Image Processing ◽  
Laplace Operator ◽  
Image Recognition ◽  
Surface Crack ◽  
Iteration Method ◽  
Crack Detection ◽  
Binary Image ◽  
Threshold Method ◽  
Otsu Method ◽  
Pavement Crack Detection

This article introduces the application of image recognition technology in cement pavement crack detection and put forward to method for determining threshold about grayscale stretching. the algorithm is designed about binarization which has a self-adaptive characteristic. After the image is preprocessed, we apply 2D Wavelet and Laplace operator to process the image. According to the characteristic of pixel of gray image, an algorithm designed on binarization for Binary image. The feasibility of this method can be verified the image processed by comparing with the results of three algorithms: Otsu method, iteration method and fixed threshold method.

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