Hairiness

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Xungai Wang - One of the best experts on this subject based on the ideXlab platform.

  • An Experimental Study of the Effect of Test Speed on Yarn Hairiness
    Textile Research Journal, 2016
    Co-Authors: Xungai Wang, Lingli Chang
    Abstract:

    In this paper, we examine the Hairiness of ring and rotor spun yarns at four different speeds of 20, 60, 100, and 140 m/min using the latest Shirley SDL096/98 Hairiness/ friction meter. Contrary to previous results obtained for similar yarns using other com mercial Hairiness meters, we observe a reduction in yarn Hairiness with increased test speed. We also examine the effects of yarn guide, yarn angle, and rewinding on yarn Hairiness. The results indicate that hair direction, air drag on hairs, and frictional rub bing of the yam being tested have a significant effect on yarn Hairiness. We postulate that the different trends of speed effects on yarn Hairiness from different Hairiness meters may stem from differing contact conditions between the yarns and the various yam guides on the respective Hairiness meters. Such different trends also suggest that reconciling Hairiness results from different Hairiness meters may be difficult.

  • Recent research and developments on yarn Hairiness
    Textile Research Journal, 2014
    Co-Authors: Noman Haleem, Xungai Wang
    Abstract:

    Hairiness is an important quality parameter of spun yarns. It not only affects the quality of yarns, but also the weaving and knitting performance of yarns as well as the quality of the resultant fabrics. Various developments regarding yarn Hairiness have been reported in the last decade. These cover aspects such as Hairiness measurement, modeling, simulation, spinning modifications and post spinning treatments to reduce Hairiness. This study is an attempt to critically review all significant recent developments regarding yarn Hairiness. Further possibilities of research and future work are also briefly discussed.

  • A comparative study on yarn Hairiness results from manual test and two commercial Hairiness metres
    Journal of The Textile Institute, 2013
    Co-Authors: Noman Haleem, Xungai Wang
    Abstract:

    The true Hairiness (actual hair number and length) of ring, compact and rotor spun yarns was measured by means of a tedious manual method. The Hairiness results were then compared with yarn Hairiness results obtained from two commercial instruments (Uster tester and Zweigle Hairiness Meter). The comparative analysis between the measurement methods has revealed very significant discrepancy between the true Hairiness results and that from commercial instruments, not only just in terms of the number of hairs, but also in terms of the hair-length distribution. The hair numbers obtained from manual method are much greater than that obtained from the Hairiness metres, and the true hair-length distribution does not follow the well-known exponential decay. This study shows that the two existing Hairiness measuring systems, while essential for rapid assessment of yarn Hairiness, are not accurately measuring the true Hairiness of spun yarns.

  • an artificial neural network based Hairiness prediction model for worsted wool yarns
    Textile Research Journal, 2009
    Co-Authors: Z A Khan, Xungai Wang, Allan E K Lim, Lijing Wang, Rafael Beltran
    Abstract:

    This study evaluated the performance of multilayer perceptron (MLP) and multivariate linear regression (MLR) models for predicting the Hairiness of worsted-spun wool yarns from various top, yarn and processing parameters. The results indicated that the MLP model predicted yarn Hairiness more accurately than the MLR model, and should have wide mill specific applications. On the basis of sensitivity analysis, the factors that affected yarn Hairiness significantly included yarn twist, ring size, average fiber length (hauteur), fiber diameter and yarn count, with twist having the greatest impact on yarn Hairiness.

  • a controlled experiment on yarn Hairiness and fabric pilling
    Textile Research Journal, 2007
    Co-Authors: Rafael Beltran, Lijing Wang, Xungai Wang
    Abstract:

    This study focused on the Hairiness of worsted wool yarns and how it affects the pilling propensity of knitted wool fabrics. Conventional worsted ring spun yarns were compared with comparable SolospunTM yarns and yarns modified with a Hairiness reducing air nozzle in the winding process (JetWind). Measurements of yarn Hairiness (S3) on the Zweigle G565 Hairiness meter showed a reduction in the S3 value of approximately 46% was achieved using SolospunTM ring spinning attachment and a 33% reduction was achieved using the JetWind process. Interestingly, subsequent evaluation of the pilling performance of fabrics made from the SolospunTM spun yarn and JetWind modified yarn showed a half grade and full grade improvement, respectively over a similar fabric made from conventional ring spun yarns. This result suggested that a relatively large reduction in yarn Hairiness was needed to achieve a moderate improvement in fabric pilling, and that the nature of yarn Hairiness was also a key factor in influencing fabric pilling propensity. It is postulated that the wrapping of surface hairs by the air vortex in the JetWind process may limit the ability of those surface fibers to form fuzz and reach the critical height required for pill formation.

Lingli Chang - One of the best experts on this subject based on the ideXlab platform.

  • An Experimental Study of the Effect of Test Speed on Yarn Hairiness
    Textile Research Journal, 2016
    Co-Authors: Xungai Wang, Lingli Chang
    Abstract:

    In this paper, we examine the Hairiness of ring and rotor spun yarns at four different speeds of 20, 60, 100, and 140 m/min using the latest Shirley SDL096/98 Hairiness/ friction meter. Contrary to previous results obtained for similar yarns using other com mercial Hairiness meters, we observe a reduction in yarn Hairiness with increased test speed. We also examine the effects of yarn guide, yarn angle, and rewinding on yarn Hairiness. The results indicate that hair direction, air drag on hairs, and frictional rub bing of the yam being tested have a significant effect on yarn Hairiness. We postulate that the different trends of speed effects on yarn Hairiness from different Hairiness meters may stem from differing contact conditions between the yarns and the various yam guides on the respective Hairiness meters. Such different trends also suggest that reconciling Hairiness results from different Hairiness meters may be difficult.

  • Investigation of yarn Hairiness
    2010
    Co-Authors: Lingli Chang
    Abstract:

    In this study, a novel approach of reducing yarn Hairiness, and a theoretical model of yarn Hairiness and energy consumption in ring spinning have been developed. The factors affecting yarn Hairiness and the Hairiness of newly developed yarns have also been examined.

  • the Hairiness of worsted wool and cashmere yarns and the impact of fiber curvature on Hairiness
    Textile Research Journal, 2006
    Co-Authors: Xungai Wang, Lingli Chang, A Mcgrego
    Abstract:

    In this study, a range of carefully selected wool and cashmere yarns as well as their blends were used to examine the effects of fiber curvature and blend ratio on yarn Hairiness. The results indicate that yarns spun from wool fibers with a higher curvature have lower yarn Hairiness than yarns spun from similar wool of a lower curvature. For blend yarns made from wool and cashmere of similar diameter, yarn Hairiness increases with the increase in the cashmere content in the yarn. This is probably due to the presence of increased proportion of the shorter cashmere fibers in the surface regions of the yarn, leading to increased yarn Hairiness. A modified Hairiness composition model is used to explain these results and the likely origin of leading and trailing hairs. This model highlights the importance of yarn surface composition on yarn Hairiness.

  • effect of yarn Hairiness on energy consumption in rotating a ring spun yarn package
    Textile Research Journal, 2003
    Co-Authors: Lingli Chang, Zhengxue Tang
    Abstract:

    The effect of yarn Hairiness on energy consumption when rotating a ring-spun yarn package is investigated theoretically and experimentally. A theoretical model is developed to calculate the energy required to rotate hair fibers, based on hair length and number as well as package speed and size. A single spindle test rig is used to verify the theoretical prediction. The experimental results confirm the theoretical prediction that the package power increases with increased yarn Hairiness level and spindle speed.

  • comparing the Hairiness of solospun and ring spun worsted yarns
    Textile Research Journal, 2003
    Co-Authors: Lingli Chang, Xungai Wang
    Abstract:

    This paper compares the Hairiness of Solospun yarns with conventional ring spun worsted yams of the same specifications. A 24-spindles worsted ring spinning frame is used to spin the Solospun and conventional ring spun yarns at the same time, and yarn Hairiness is measured. The total Hairiness number (Tp), the number of hairs longer than or equal to 3mm (S3), the percentage of longer hairs in total hairs (100S3/Tp), and the total hair length per unit yarn length (K' ) are used to compare the Hairiness of these yams. The results indicate that the Solospun yarn exhibits less Hairiness in each of the hair length groups and has lower variations in yarn Hairiness. The hair-length distribution of the Solospun yarn follows an exponential law just like conventional ring spun yams. There is a statistically significant difference between the Solospun and conventional ring spun yams for T p, S3, and K', but the difference in 1 00S 3/Tp is not statistically significant for these yams. In addition, the Tp, S3, and K' values of the Solospun yarn decrease with twist increase and increase with spindle speed increase, but the 100S3/Tp values of the Solospun and conventional ring spun yarns in this study behave differently in that they are affected by twist level and spindle speed.

Ezzatollah Haghighat - One of the best experts on this subject based on the ideXlab platform.

  • Study of the Hairiness of Polyester-Viscose Blended Yarns. Part IV - Predicting Yarn Hairiness Using Fuzzy Logic
    Fibres & Textiles in Eastern Europe, 2012
    Co-Authors: Ezzatollah Haghighat, M. Safar Johari, Seyed Mohammad, M. Amani Tehran
    Abstract:

    This paper is a continuation of studies on the Hairiness of polyester-viscose blended ring spun yarns. The aim of this study is to predict the Hairiness of polyester-viscose blended yarns using a fuzzy logic system. For this purpose, based on the ANOVA statistical test, some parameters that have more influence on yarn Hairiness were selected: spindle speed, traveller count, and yarn count, which are taken into account as the inputs, and yarn Hairiness is counted as the output in the fuzzy set. The Hairiness of ring spun polyester-viscose blended yarns was successfully modelled using fuzzy logic. The results showed that the correlation coefficient between the predicted and experimental values of Hairiness is acceptable (R2 = 0.931).

  • study of the Hairiness of polyester viscose blended yarns part iii predicting yarn Hairiness using an artificial neural network
    Fibres & Textiles in Eastern Europe, 2012
    Co-Authors: Ezzatollah Haghighat, Seyed Mohammad, Safar M Johari, Amani M Tehran
    Abstract:

    The Hairiness of blended yarns is influenced by several parameters at the ring frame. For this reason, it is necessary to develop a model based on experimental evidence that includes all known processing factors. The generalised from of this model is a candidate for predicting yarn Hairiness. In this paper, an artificial neural network and multiple linear regression were used for modelling and predicting the Hairiness of polyester-viscose blended yarns based on various process parameters. The models developed were assessed by applying PF/3, the Mean Square Error (MSE), and the Correlation Coefficient (R-value) between the actual and predicted yarn Hairiness. The results indicated that the artificial neural network has better performance (R = 0.967) in comparison with multiple linear regression (R = 0.878).

  • a study of the Hairiness of polyester viscose blended yarns part i drafting system parameters
    Fibres & Textiles in Eastern Europe, 2008
    Co-Authors: Ezzatollah Haghighat, Majid Safar Johari, Seyed Mohammad Etrati
    Abstract:

    The influences of drafting system parameters of a ring frame and yarn parameters on the Hairiness of polyester-viscose blended yarns are examined. Samples of 80/20 polyester/ viscose blended yarns were produced by a SKF Lab Spinner and the Hairiness was measured by a Shirley Yarn Friction/Hairiness Meter. Statistical analysis of the results show that yarn Hairiness is significantly influenced by the drafting system angle, the overhang of the top delivery roller , the covering of the top delivery roller, the back zone setting, the break draft, the yarn count and yarn twist. Moreover, it was observed that the distance clips and top roller pressure do not have a significant effect on the yarn Hairiness. The origin of the improving factors and decreasing factors of Hairiness are discussed.

Huang Xinxi - One of the best experts on this subject based on the ideXlab platform.

  • Surface characteristics of low-twist worsted yarns and knitted fabrics
    The Hong Kong Polytechnic University, 2016
    Co-Authors: Huang Xinxi
    Abstract:

    PolyU Library Call No.: [THS] LG51 .H577P ITC 2016 Huangxxxii, 259 pages :color illustrationsWool apparel and other textile products are of high value and popularity in the market all the time because of their aesthetic quality and comfort. With the increasing demand of light, thin and comfortable knitted fabrics, it is desirable to have wool yarns in medium to high counts with better yarn evenness, less Hairiness, soft handle and reasonable tenacity, etc. By literature review, ring spinning continues to predominate in worsted yarn manufacturing industry because of its high quality of yarns and good flexibility in materials and yarn count. Many modifications have been conducted to enhance the control of fibers in spinning triangle and reduce yarn hairs, but nearly have no improvement on yarn soft handle and evenness. However,over ten years ago, a modified technology on the ring frame was developed by employing a false twisting device and a strand separator, which was named as Nu-torqueTM or low-torque or low-twist spinning. Since then, the technology has evolved in five versions. The low-twist cotton yarns exceed other types of modified ring spun yarns with respect to softer handle, lower residual torque, and outweigh the conventional ring yarns in aspects of higher tenacity, lower Hairiness, etc. Previous versions of low-twist worsted yarn technology have produced low-twist worsted yarns in median and coarse count, however, some problems were found such as worse yarn optical evenness, more neps and tight wrapper fibers, as well as lower yarn tenacity, among which, the wrapper fibers give rise to obvious "bar effect" on the dyed knitted wool fabrics. Hence, this thesis is aimed at investigating these problems and exploring possible solutions from both theoretical and practical points of views. The surface structure of 24Nm low-twist worsted yarns are examined under Microscope Lecia M165 in details and classified into five types including three kinds of wrapping structures and two kinds of unwrapped structures. In particular, the tightly wrapping structures take up almost 60% on the low-twist yarns. These tightly wrapping structures not only bring about quite compact yarn structures resulting in harsh handle of yarns and fabrics,but also deteriorate yarn optical evenness resulted from obviously smaller diameters than conventional yarn structures and higher variations. Using high speed camera system, the formation of wrapper fibers on the low-twist yarn surface has been investigated. It is found that the abrasion between yarns or the protruding fiber ends and the upper false-twister or the lower false-twister, the fiber security of yarns in A zone, as well as the false-twisting effects exerted by the two false-twisters, have effects on the wrapper fiber formation; more importantly, the wrapper fibers have roots in the long protruding fiber ends in A zone on the low-twist spinning system, namely, the Hairiness of 3mm and longer of the yarn segment between the spinning triangle and the false-twister. Besides, the bulked yarn segment resulted from excessive twists in A zone is reckoned as the reason for the formation of the curved yarns with tight wrapper fibers.Hypothesizing that the structure of yarn segment in A zone on the low-twist spinning system is similar to that of ring-spun yarns of a high twist without buckling, a Hairiness model of such ring yarns is beneficial to understand the origin of Hairiness and wrapper fibers as well as the formation of neps. The number of all fiber ends in the out-most layer of ring-spun yarn cross-section, which are already or have potentials to become hairs, is first defined as maximum Hairiness in unit length of yarn. Based on Brown and Ly's work on the number of fiber ends in twist-less fiber assembly, a statistical model of the maximum Hairiness of ring yarns has been established by considering yarn twist geometry and the contributing surface layer for hairs. In particular, fiber length, fiber cross-section and the number of fibers have been revised with the consideration of yarn twist. Moreover, Hairiness contribution factor (h0) is proposed for model development as the ratio of the number of fiber ends having potentials for Hairiness and the total number of fiber ends in yarn cross-section. From the developed model, it can be seen that the maximum Hairiness of ring yarns, or the number of long protruding fiber ends in A zone of the low-twist spinning system, relates to fiber length distribution, fiber diameter, yarn count, yarn twist,measured hair length etc. Moreover, the present model provides the length of the predicted maximum Hairiness, whereas previous related models fail to do so. The verification by experiments demonstrates that the predicted values of 1mm and longer are in the same order of magnitude as the measured values, which are more accurate than the predicted values from other related models. Whereas, the predicted maximum Hairiness of 3mm and longer, that is, the long protruding fiber ends, is almost 1~2 order of magnitude higher than the measured S3 values. Alternatively, there are some other ways to further reduce the number of long protruding fiber ends in A zone, like combining Siro-spinning or Solo-spinning with low-twist spinning, because it is generally believed that surface fiber trapping between the two substrands in Siro-spinning triangle or among several substrands in Solo-spinning triangle contributes to the significant decrease of yarn Hairiness. Accordingly, the maximum Hairiness model of ring yarns is revised for Siro-spun yarns and Solo-spun yarns with respect to fiber trapping and yarn geometry, respectively. Also, experiments have been carried out to verify the developed Hairiness models.As aforementioned before, the fiber security of the yarn segment in A zone also influence the wrapper fiber formation and the resultant yarn surface; and the degree of fiber ends being tucked into yarn bodies directly determines the number of protruding hair of yarns. Whereas, the existing related parameters only describe fiber ends already protruding out of yarns. Similar to the theoretical limit of yarn evenness CVlim, the real yarn Hairiness can approach but is always lower than the maximum Hairiness of ring yarns. A Relative Hairiness Index (RHI) is accordingly proposed, which has two forms:the theoretical one and the actual one. The theoretical RHI is the ratio of maximum Hairiness of certain type of yarn to the maximum Hairiness of ring yarns, which can theoretically reveal the effectiveness of different spinning methods in tucking fiber ends into yarn bodies; and the so-called actual RHI is the ratio of the measured yarn Hairiness and the maximum Hairiness of ring yarns, which can actually demonstrate the degree of fiber ends potential for Hairiness being tucked into yarns resulted from various spinning system or their spinning parameters. Both the theoretical RHI and the actual RHI demonstrate that Siro-spinning can most effectively tuck fiber ends into yarn bodies, therefore Siro-spun feeding will give rise to the least long protruding fiber ends. Additionally, winding is employed to mimic the abrasion that yarn will experience, and it is found that the Hairiness of ring yarns obviously increases with the increasing winding times and reaches a plateau after the fourth winding, therefore the number of hairs of yarns after four-time winding, is termed as stable Hairiness. By analyzing the increment rate of the actual RHI of various yarns in the states of cop, cone and stable, which are the yarns experience zero-time, one-time and four-time winding, respectively, Siro-pun yarns also present the best fiber security.Hence, Siro-spun feeding with a normal roving gap of 14mm is combined with the lately 5th version of low-twist spinning system for further reducing the wrapper fibers and improving the surface of low-twist yarns. However, aiming at yarn evenness and tenacity, as well as proper twists in A zone to avoid bulking as described before, the spinning parameters of 36Nm low-twist yarns (36LT) is first systematically optimized by means of the combination of Fractional Factorial Methodology and Response Surface Methodology, respectively. With a twist multiplier reduced by around 15%, the optimized 36LT yarns show comparable tenacity and similar Hairiness, but still a bit worse evenness and more neps than the conventional yarns. Actually, the number of neps (+140%) has been reduced about one order of magnitude on the present low-twist yarns by comparing with that of yarns produced on the previous versions of low-twist spinning system. The blackboard evenness of the optimized 36LT yarns exhibits half grade lower than the conventional yarns with a twist multiplier higher by about 15%, but half grade higher than the counterparts with the same level of twist multiplier, respectively. Then, the spinning parameters of 36Nm low-twist yarns with double-roving feeding (36LT+Siro) are also optimized by using Response Surface Methodology. The tightly wrapped structures on the optimized 36LT yarns only account for 8.9%, whereas the ones on the optimized 36LT+Siro yarns even reduce to 5.8%.Moreover, nearly no tightly wrapped structures with a curved yarn body are found on the two optimized yarn surfaces. Therefore, the optimized spinning parameters of low-twist spinning system, as well as the incorporation of Siro-spinning not only facilitate the reduction of wrapper fibers on the resultant yarns, but also provide suitable twists in A zone to avoid producing buckling and curved yarn segments. Nevertheless, the optimized 36LT yarn has an obviously higher actual RHI than the conventional ring yarns, and it presents similar increment rate when enduring abrasion to that of its counterpart, which indicates that the optimized 36LT yarns possess low fiber tucking and security, in other words, the fiber deformation resulted from false-twisting effect fails to be held in yarns. But the actual RHI of the optimized 36LT+Siro yarn and its increment rate by abrasion are markedly lower than the ones of the conventional yarn, particularly, its increment rate is even similar to that of Solo-spun yarns. It is demonstrated that the fiber tucking and security of low-twist yarns can also be improved by integrating Siro-spinning system.Finally, using the Kawabata Evaluation System of Fabric (KES-F), the knitted fabrics made of the optimized 36LT yarns are examined in terms of fabric surface property, tensile and shear, as well as bending and compression. There are no statistically significant differences in surface property,tensile, shear, bending, compression and bursting strength between the low-twist fabrics and the conventional fabrics made of the worsted yarns with a higher twist multiplier by around 15% (at a significant level of 0.05). However, the low-twist fabric possesses better pilling performance and air permeability, but lower thermal conductivity than its counterpart. Besides, nearly no "bar effect" is found on the resultant fabrics made of the optimized 36LT yarns.Institute of Textiles and ClothingPh.D., Institute of Textiles and Clothing, The Hong Kong Polytechnic University, 2016Doctorat

  • Surface characteristics of low-twist worsted yarns and knitted fabrics
    The Hong Kong Polytechnic University, 2016
    Co-Authors: Huang Xinxi
    Abstract:

    PolyU Library Call No.: [THS] LG51 .H577P ITC 2016 Huangxxxii, 259 pages :color illustrationsWool apparel and other textile products are of high value and popularity in the market all the time because of their aesthetic quality and comfort. With the increasing demand of light, thin and comfortable knitted fabrics, it is desirable to have wool yarns in medium to high counts with better yarn evenness, less Hairiness, soft handle and reasonable tenacity, etc. By literature review, ring spinning continues to predominate in worsted yarn manufacturing industry because of its high quality of yarns and good flexibility in materials and yarn count. Many modifications have been conducted to enhance the control of fibers in spinning triangle and reduce yarn hairs, but nearly have no improvement on yarn soft handle and evenness. However,over ten years ago, a modified technology on the ring frame was developed by employing a false twisting device and a strand separator, which was named as Nu-torqueTM or low-torque or low-twist spinning. Since then, the technology has evolved in five versions. The low-twist cotton yarns exceed other types of modified ring spun yarns with respect to softer handle, lower residual torque, and outweigh the conventional ring yarns in aspects of higher tenacity, lower Hairiness, etc. Previous versions of low-twist worsted yarn technology have produced low-twist worsted yarns in median and coarse count, however, some problems were found such as worse yarn optical evenness, more neps and tight wrapper fibers, as well as lower yarn tenacity, among which, the wrapper fibers give rise to obvious "bar effect" on the dyed knitted wool fabrics. Hence, this thesis is aimed at investigating these problems and exploring possible solutions from both theoretical and practical points of views. The surface structure of 24Nm low-twist worsted yarns are examined under Microscope Lecia M165 in details and classified into five types including three kinds of wrapping structures and two kinds of unwrapped structures. In particular, the tightly wrapping structures take up almost 60% on the low-twist yarns. These tightly wrapping structures not only bring about quite compact yarn structures resulting in harsh handle of yarns and fabrics,but also deteriorate yarn optical evenness resulted from obviously smaller diameters than conventional yarn structures and higher variations. Using high speed camera system, the formation of wrapper fibers on the low-twist yarn surface has been investigated. It is found that the abrasion between yarns or the protruding fiber ends and the upper false-twister or the lower false-twister, the fiber security of yarns in A zone, as well as the false-twisting effects exerted by the two false-twisters, have effects on the wrapper fiber formation; more importantly, the wrapper fibers have roots in the long protruding fiber ends in A zone on the low-twist spinning system, namely, the Hairiness of 3mm and longer of the yarn segment between the spinning triangle and the false-twister. Besides, the bulked yarn segment resulted from excessive twists in A zone is reckoned as the reason for the formation of the curved yarns with tight wrapper fibers.Hypothesizing that the structure of yarn segment in A zone on the low-twist spinning system is similar to that of ring-spun yarns of a high twist without buckling, a Hairiness model of such ring yarns is beneficial to understand the origin of Hairiness and wrapper fibers as well as the formation of neps. The number of all fiber ends in the out-most layer of ring-spun yarn cross-section, which are already or have potentials to become hairs, is first defined as maximum Hairiness in unit length of yarn. Based on Brown and Ly's work on the number of fiber ends in twist-less fiber assembly, a statistical model of the maximum Hairiness of ring yarns has been established by considering yarn twist geometry and the contributing surface layer for hairs. In particular, fiber length, fiber cross-section and the number of fibers have been revised with the consideration of yarn twist. Moreover, Hairiness contribution factor (h0) is proposed for model development as the ratio of the number of fiber ends having potentials for Hairiness and the total number of fiber ends in yarn cross-section. From the developed model, it can be seen that the maximum Hairiness of ring yarns, or the number of long protruding fiber ends in A zone of the low-twist spinning system, relates to fiber length distribution, fiber diameter, yarn count, yarn twist,measured hair length etc. Moreover, the present model provides the length of the predicted maximum Hairiness, whereas previous related models fail to do so. The verification by experiments demonstrates that the predicted values of 1mm and longer are in the same order of magnitude as the measured values, which are more accurate than the predicted values from other related models. Whereas, the predicted maximum Hairiness of 3mm and longer, that is, the long protruding fiber ends, is almost 1~2 order of magnitude higher than the measured S3 values. Alternatively, there are some other ways to further reduce the number of long protruding fiber ends in A zone, like combining Siro-spinning or Solo-spinning with low-twist spinning, because it is generally believed that surface fiber trapping between the two substrands in Siro-spinning triangle or among several substrands in Solo-spinning triangle contributes to the significant decrease of yarn Hairiness. Accordingly, the maximum Hairiness model of ring yarns is revised for Siro-spun yarns and Solo-spun yarns with respect to fiber trapping and yarn geometry, respectively. Also, experiments have been carried out to verify the developed Hairiness models.As aforementioned before, the fiber security of the yarn segment in A zone also influence the wrapper fiber formation and the resultant yarn surface; and the degree of fiber ends being tucked into yarn bodies directly determines the number of protruding hair of yarns. Whereas, the existing related parameters only describe fiber ends already protruding out of yarns. Similar to the theoretical limit of yarn evenness CVlim, the real yarn Hairiness can approach but is always lower than the maximum Hairiness of ring yarns. A Relative Hairiness Index (RHI) is accordingly proposed, which has two forms:the theoretical one and the actual one. The theoretical RHI is the ratio of maximum Hairiness of certain type of yarn to the maximum Hairiness of ring yarns, which can theoretically reveal the effectiveness of different spinning methods in tucking fiber ends into yarn bodies; and the so-called actual RHI is the ratio of the measured yarn Hairiness and the maximum Hairiness of ring yarns, which can actually demonstrate the degree of fiber ends potential for Hairiness being tucked into yarns resulted from various spinning system or their spinning parameters. Both the theoretical RHI and the actual RHI demonstrate that Siro-spinning can most effectively tuck fiber ends into yarn bodies, therefore Siro-spun feeding will give rise to the least long protruding fiber ends. Additionally, winding is employed to mimic the abrasion that yarn will experience, and it is found that the Hairiness of ring yarns obviously increases with the increasing winding times and reaches a plateau after the fourth winding, therefore the number of hairs of yarns after four-time winding, is termed as stable Hairiness. By analyzing the increment rate of the actual RHI of various yarns in the states of cop, cone and stable, which are the yarns experience zero-time, one-time and four-time winding, respectively, Siro-pun yarns also present the best fiber security.Hence, Siro-spun feeding with a normal roving gap of 14mm is combined with the lately 5th version of low-twist spinning system for further reducing the wrapper fibers and improving the surface of low-twist yarns. However, aiming at yarn evenness and tenacity, as well as proper twists in A zone to avoid bulking as described before, the spinning parameters of 36Nm low-twist yarns (36LT) is first systematically optimized by means of the combination of Fractional Factorial Methodology and Response Surface Methodology, respectively. With a twist multiplier reduced by around 15%, the optimized 36LT yarns show comparable tenacity and similar Hairiness, but still a bit worse evenness and more neps than the conventional yarns. Actually, the number of neps (+140%) has been reduced about one order of magnitude on the present low-twist yarns by comparing with that of yarns produced on the previous versions of low-twist spinning system. The blackboard evenness of the optimized 36LT yarns exhibits half grade lower than the conventional yarns with a twist multiplier higher by about 15%, but half grade higher than the counterparts with the same level of twist multiplier, respectively. Then, the spinning parameters of 36Nm low-twist yarns with double-roving feeding (36LT+Siro) are also optimized by using Response Surface Methodology. The tightly wrapped structures on the optimized 36LT yarns only account for 8.9%, whereas the ones on the optimized 36LT+Siro yarns even reduce to 5.8%.Moreover, nearly no tightly wrapped structures with a curved yarn body are found on the two optimized yarn surfaces. Therefore, the optimized spinning parameters of low-twist spinning system, as well as the incorporation of Siro-spinning not only facilitate the reduction of wrapper fibers on the resultant yarns, but also provide suitable twists in A zone to avoid producing buckling and curved yarn segments. Nevertheless, the optimized 36LT yarn has an obviously higher actual RHI than the conventional ring yarns, and it presents similar increment rate when enduring abrasion to that of its counterpart, which indicates that the optimized 36LT yarns possess low fiber tucking and security, in other words, the fiber deformation resulted from false-twisting effect fails to be held in yarns. But the actual RHI of the optimized 36LT+Siro yarn and its increment rate by abrasion are markedly lower than the ones of the conventional yarn, particularly, its increment rate is even similar to that of Solo-spun yarns. It is demonstrated that the fiber tucking and security of low-twist yarns can also be improved by integrating Siro-spinning system.Finally, using the Kawabata Evaluation System of Fabric (KES-F), the knitted fabrics made of the optimized 36LT yarns are examined in terms of fabric surface property, tensile and shear, as well as bending and compression. There are no statistically significant differences in surface property,tensile, shear, bending, compression and bursting strength between the low-twist fabrics and the conventional fabrics made of the worsted yarns with a higher twist multiplier by around 15% (at a significant level of 0.05). However, the low-twist fabric possesses better pilling performance and air permeability, but lower thermal conductivity than its counterpart. Besides, nearly no "bar effect" is found on the resultant fabrics made of the optimized 36LT yarns.Institute of Textiles and ClothingPh.D., Institute of Textiles and Clothing, The Hong Kong Polytechnic University, 2016Doctoratepublished_fina

Filomena Soares - One of the best experts on this subject based on the ideXlab platform.

  • yarn Hairiness determination using image processing techniques
    Emerging Technologies and Factory Automation, 2011
    Co-Authors: Vitor Carvalho, Rosa Vasconcelos, Filomena Soares, M Belsley, Nuno Goncalves
    Abstract:

    This paper presents a method to automatically determine yarn Hairiness using Image Processing (IP) techniques. After image acquisition, the samples are analyzed and processed by a custom-made application developed in Lab VIEW from National Instruments with the IMAQ Vision toolkit. The results show that a reliable quantification of the yarn Hairiness index can be obtained. This methodology can be used as an efficient alternative to the traditional commercial Hairiness testers suppressing their constraints. Step-by-step algorithms used to isolate the yarn core, to highlight the fibres and to measure the Hairiness index are described.

  • yarn Hairiness characterization using two orthogonal directions
    IEEE Transactions on Instrumentation and Measurement, 2009
    Co-Authors: Vitor Carvalho, Paulo Cardoso, Rosa Vasconcelos, M Belsley, Filomena Soares
    Abstract:

    We demonstrate that one can adequately characterize yarn Hairiness by imaging the yarn along a single projection direction using coherent optical processing. A system that simultaneously characterizes the yarn Hairiness along two orthogonal projection directions was constructed. Provided that a sufficiently high number of yarn segments are sampled, a strong statistical correlation is obtained between the results in each direction. The resulting images are generated using coherent optical signal processing with a Fourier high-pass spatial filter. This filter blocks the yarn core and produces a signal that highlights the sharp transitions in the transmission of the yarn. Essentially, only the small fibers responsible for the Hairiness and the yarn core contours are present. Experimental results are presented for a 62-g/km yarn possessing a high degree of Hairiness.

  • yarn Hairiness parameterization using a coherent signal processing technique
    Sensors and Actuators A-physical, 2008
    Co-Authors: Vitor Carvalho, Paulo Cardoso, Rosa Vasconcelos, M Belsley, Filomena Soares
    Abstract:

    Abstract The aim of this paper is to present an automatic yarn Hairiness parameterization method based on optical sensors. Hairiness measurements are performed using a coherent signal processing technique for higher resolution. Using this optical technique together with electronic instrumentation and custom developed software, it is possible to quantify all traditional Hairiness parameters (i.e. Hairiness (H), its coefficient of variation (CVH) and standard deviation (sH)) used in the textile industry, as well as determine several others, such as mean deviation coefficient (U), deviation rate (DR) and its integral (IDR). The overall goal of the current project is to develop an integrated automatic yarn system characterization: evenness analysis determination using capacitive sensors, Hairiness analysis using coherent optics technique and finally, image processing for yarn production characteristics.

  • optical yarn Hairiness measurement system
    International Conference on Industrial Informatics, 2007
    Co-Authors: Vitor Carvalho, Paulo Cardoso, Rosa Vasconcelos, Filomena Soares, M Belsley
    Abstract:

    This paper presents a system developed for measuring yarn Hairiness using a coherent optical signal processing technique, in steps of 1 mm. The system hardware is divided into two main parts: optical, for establishing an image regarding yarn Hairiness and electronic, which converts the optical signal to a proportional voltage signal. Additionally, software using LabVIEWTM was also designed to acquire the output voltage with a data acquisition board (DAQ) and to perform the corresponding data processing. This system is able to quantify the traditional commercial hairniness parameters, as sH (%), CVH (%), H and spectral analysis based on FFT. In addition several other parameters, novel in textile characterization, such as DRH (%), IDRH (%), UH (%) and spectral analysis based on FWHT and FDFI are readily available. The results obtained using this system to characterize a 4.20 g/Km cotton yarn are presented.

  • optical quantification of yarn Hairiness using projections along a single direction
    International Conference on Control Applications, 2007
    Co-Authors: Vitor Carvalho, Paulo Cardoso, Rosa Vasconcelos, M Belsley, Filomena Soares
    Abstract:

    This paper presents a system which is able to measure yarn Hairiness using coherent optical signal processing, plus the associated electronics and custom software. By placing a spatial high-pass optical filter in the Fourier plane, to remove the low spatial frequency information (yarn core and light that does not hit the yarn). High spatial frequencies, which correspond to Hairiness and the yarn borders, are transmitted. To quantify Hairiness, a photodiode, plus a trans-impedance amplifier were used to obtain a voltage proportional to the Hairiness signal. A data acquisition system controlled by an application developed in Lab VIEW is used to acquire and process the measured data. However, an open question remains as to whether one can obtain a valid characterization of the yarn properties using a single projection direction. The results reported here demonstrate that in the case that the Hairiness is randomly orientated a single projection measures on average 0.64 of the Hairiness present on the yarn.

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