The Experts below are selected from a list of 150 Experts worldwide ranked by ideXlab platform
Toshihiro Shinohara - One of the best experts on this subject based on the ideXlab platform.
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Automatic construction of weave diagram of warp-knitted fabric using positional information on yarn
Proceedings of SICE Annual Conference 2010, 2010Co-Authors: Toshihiro ShinoharaAbstract:In this paper, a novel method for the automatic construction of weave diagrams of warp-knitted fabrics using positional information on their yarns is proposed. In this study, the yarn positional information corresponds to a sequence of the center points of the yarn and is obtained by using the yarn tracing method proposed in my previous study. The construction of a weave diagram is based on identifying the Stitch Type at each Stitch of the knitted fabric. For constructing a weave diagram, first, the Stitch is detected by determining the points of intersection of the yarns and finding the four points which is related by a certain relationship from them. Then, the Types of Stitches are identified by verifying the existence of the point of intersection of the yarn with itself and investigating the order of these points of intersection of the lower yarn in the Stitch. The validity of the proposed method is experimentally confirmed by using the method along with yarn positional information of a net knitted fabric.
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Automatic weave diagram construction from yarn positional information of weft-knitted fabric
2009 ICCAS-SICE, 2009Co-Authors: Toshihiro ShinoharaAbstract:In this paper, a novel automatic construction method of a weave diagram using yarn positional information of a weft-knitted fabric is proposed. The yarn positional information is a sequence of the center points of the yarn in this study, which is obtained using a yarn tracing method proposed in my previous study. Constructing a weave diagram corresponds to identifying the Stitch Type at each Stitch of the knitted fabric. For constructing a weave diagram, first, the position of each Stitch is detected by investigating the cross points between the yarns. Then, the Types of Stitches are identified by investigating which Stitch the Stitch intersects with. The validity of the proposed automatic weave diagram construction method is confirmed by experimentally applying the method to yarn positional information of a plain knitted fabric.
Thomas Gries - One of the best experts on this subject based on the ideXlab platform.
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Influence of the fabric construction parameters and roving Type on the tensile property retention of high-performance rovings in warp-knitted reinforced fabrics and cement-based composites
Journal of Industrial Textiles, 2016Co-Authors: Till Quadflieg, Oleg Stolyarov, Thomas GriesAbstract:In this work, the tensile property retention characteristics of high-performance glass and carbon rovings in warp-knitted reinforced fabrics and cement-based composites used in structural applications were investigated. Three Types of warp-knitted fabrics, with differing Stitch patterns, and cement-based composites were produced. The tensile strength retention and Young’s modulus retention of the roving in these fabrics and their influence on the properties of cement-based composites were compared on the basis of the Stitch Type. Samples of warp-knitted fabrics composed of glass fibres and carbon fibres exhibit retention of 76–87% and 65–87.6%, respectively, of the initial strength of the rovings. The highest Young’s modulus retention (∼80%) occurs in the case of the fabric sample composed of glass rovings. The retention of the Young’s modulus in the fabric samples composed of carbon rovings was 37–60%. In addition, the translation of strength from the roving to the fabric and retention of the Young’s mod...
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Characterization of shear behavior of warp-knitted fabrics applied to composite reinforcement
Journal of The Textile Institute, 2016Co-Authors: Oleg Stolyarov, Till Quadflieg, Thomas GriesAbstract:Different Types of textile fabrics are now widely used for reinforcing composite structural parts. In this work, three Types of weft-inserted warp-knitted fabrics differing in Stitch pattern and composed of glass roving were produced. The shear behavior of the developed fabrics was determined according to Stitch Type. Three basic Stitch Types were chosen: tricot, cord, and pillar. The shear behavior was examined by the picture frame test method. It was observed that the Stitch Type significantly affects the shear behavior of the fabrics. The deformation phases during the fabric shear test were analyzed. To estimate the changes in the shear stiffness of the fabrics, shear moduli were calculated as a function of the shear angle. In general, the fabric with the tricot Stitch has the greatest shear resistance than that of fabrics with the cord and pillar Stitches. The results of the characterization of shear behavior of the warp-knitted fabrics are presented and discussed.
S. Subbaraman - One of the best experts on this subject based on the ideXlab platform.
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ISED - DCSFPSS assisted morphological approach for grey twill fabric defect detection and defect area measurement for fabric grading
2011 International Symposium on Electronic System Design, 2011Co-Authors: V. Jayashree, S. SubbaramanAbstract:This paper proposes a new optimal morphological filter design using DC suppressed Fourier power spectrum sum (DCSFPSS) plot as a major technique to extract the texture periodicity features of textile fabrics. Periodicity is further used to assist the selection of size of structuring element(SE) for morphological operation(MO) to detect grey twill fabric defects. The performance of the scheme is evaluated on number of homogeneous twill grey fabric images with loose weft and Stitch Type of defects. Computation of number of defects, area of each defect and total defect area in a given fabric image is estimated. Then a simple binary based defect search algorithm is adopted to determine the presence of defects. The performance parameter of the proposed algorithm is firstly obtained in terms of accuracy of correct defect detection (ACD) which is found to be 98\% for Stitch and 94.7\% for loose weft defect samples of two twill grey fabric classes. Secondly, the recognition of defect area less than 1$mm ^2$, which has not been reported in the literature yet, was possible using this algorithm. Further we propose to use this method to grade the fabric based on standard systems adopted for classifying the fabric. The details of the experimentation and the results thereof are presented in this paper.
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DCSFPSS assisted morphological approach for grey twill fabric defect detection and defect area measurement for fabric grading
2011 International Symposium on Electronic System Design, 2011Co-Authors: V. Jayashree, S. SubbaramanAbstract:This paper proposes a new optimal morphological filter design using DC suppressed Fourier power spectrum sum (DCSFPSS) plot as a major technique to extract the texture periodicity features of textile fabrics. Periodicity is further used to assist the selection of size of structuring element(SE) for morphological operation(MO) to detect grey twill fabric defects. The performance of the scheme is evaluated on number of homogeneous twill grey fabric images with loose weft and Stitch Type of defects. Computation of number of defects, area of each defect and total defect area in a given fabric image is estimated. Then a simple binary based defect search algorithm is adopted to determine the presence of defects. The performance parameter of the proposed algorithm is firstly obtained in terms of accuracy of correct defect detection (ACD) which is found to be 98% for Stitch and 94.7% for loose weft defect samples of two twill grey fabric classes. Secondly, the recognition of defect area less than 1mm2, which has not been reported in the literature yet, was possible using this algorithm. Further we propose to use this method to grade the fabric based on standard systems adopted for classifying the fabric. The details of the experimentation and the results thereof are presented in this paper.
Ahmed Saeed - One of the best experts on this subject based on the ideXlab platform.
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Suitability of Conductive Knit Fabric for Sensing Human Breathing
Journal of textile and apparel technology and management, 2019Co-Authors: Aliaa Abdel Aziz Mohamed, Mohamed M. Ezzat, Zaynab M. Abdel Megeid, Ahmed Saeed, Hebatullah A.a. Abdel-hamed, Enas A.h. El-okdaAbstract:This paper studies the suitability of conductive knit fabric in order to produce a reliable breathing sensor. Conductive single jersey knit fabrics was manufactured from silver coated nylon yarn with different production parameters (Stitch Type (ST) - combination ratio (CR) of conductive yarn to the non-conductive one and number of needles (NN)). A cyclic tester was built to simulate the breathing mechanism of a human being and to explore the influence of these parameters on the gauge factor. The results show that the production parameters have a significant effect on the results of the gauge factor. The best sample suited for breathing sensor is the one with normal knit Stitch, less CR and increase in width (NN).
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Suitability of conductive knit fabric for sensing human breathing
Journal of Scientific Research in Science, 2016Co-Authors: Aliaa Abdelrazek Mohamed, Mohamed M. Ezzat, Zaynab M. Abdel Megeid, Ahmed SaeedAbstract:This paper studies the suitability of conductive knit fabric in order to produce a reliable breathing sensor. Conductive single jersey knit fabrics was manufactured from silver coated nylon yarn with different production parameters (Stitch Type (ST)- combination ratio (CR) and number of wales (NW)). A cyclic tester was built to simulate the breathing mechanism of a human being and to explore the influence of these parameters on the electric resistance. The results show that there is a significant effect on the resistance value by the difference in ST and CR, while the width of the sample doesn’t show a significant effect.The best sample suited for breathing sensor is the one with increase in width (NW), less CR and normal Stitch.
V. Jayashree - One of the best experts on this subject based on the ideXlab platform.
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ISED - DCSFPSS assisted morphological approach for grey twill fabric defect detection and defect area measurement for fabric grading
2011 International Symposium on Electronic System Design, 2011Co-Authors: V. Jayashree, S. SubbaramanAbstract:This paper proposes a new optimal morphological filter design using DC suppressed Fourier power spectrum sum (DCSFPSS) plot as a major technique to extract the texture periodicity features of textile fabrics. Periodicity is further used to assist the selection of size of structuring element(SE) for morphological operation(MO) to detect grey twill fabric defects. The performance of the scheme is evaluated on number of homogeneous twill grey fabric images with loose weft and Stitch Type of defects. Computation of number of defects, area of each defect and total defect area in a given fabric image is estimated. Then a simple binary based defect search algorithm is adopted to determine the presence of defects. The performance parameter of the proposed algorithm is firstly obtained in terms of accuracy of correct defect detection (ACD) which is found to be 98\% for Stitch and 94.7\% for loose weft defect samples of two twill grey fabric classes. Secondly, the recognition of defect area less than 1$mm ^2$, which has not been reported in the literature yet, was possible using this algorithm. Further we propose to use this method to grade the fabric based on standard systems adopted for classifying the fabric. The details of the experimentation and the results thereof are presented in this paper.
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DCSFPSS assisted morphological approach for grey twill fabric defect detection and defect area measurement for fabric grading
2011 International Symposium on Electronic System Design, 2011Co-Authors: V. Jayashree, S. SubbaramanAbstract:This paper proposes a new optimal morphological filter design using DC suppressed Fourier power spectrum sum (DCSFPSS) plot as a major technique to extract the texture periodicity features of textile fabrics. Periodicity is further used to assist the selection of size of structuring element(SE) for morphological operation(MO) to detect grey twill fabric defects. The performance of the scheme is evaluated on number of homogeneous twill grey fabric images with loose weft and Stitch Type of defects. Computation of number of defects, area of each defect and total defect area in a given fabric image is estimated. Then a simple binary based defect search algorithm is adopted to determine the presence of defects. The performance parameter of the proposed algorithm is firstly obtained in terms of accuracy of correct defect detection (ACD) which is found to be 98% for Stitch and 94.7% for loose weft defect samples of two twill grey fabric classes. Secondly, the recognition of defect area less than 1mm2, which has not been reported in the literature yet, was possible using this algorithm. Further we propose to use this method to grade the fabric based on standard systems adopted for classifying the fabric. The details of the experimentation and the results thereof are presented in this paper.