Numerical simulation of three-dimensional flow field in three-line rollers and four-line rollers compact spinning systems using finite element method

In this investigation, the airflow velocity principle in the condensing zone of three-line rollers and four-line rollers compact spinning systems has been studied and the relationship between the flow distribution in velocity component and the yarn properties is discussed. The important effect is the accurate description of the yarn track in the condensing zone. The yarns of 9.72tex, 14.58tex and 29.15tex fineness have been spun on three-line rollers and four-line rollers compact spinning systems respectively. The hairiness, the breaking force and the evenness of the spun yarns are tested respectively. With the help of a high-speed video camera, a periodic movement of the fibres in bundle in the condensing zone has been detected firstly and the yarn tracks are described. Numerical simulations are investigated using ANSYS software. The yarn tracks are different. The flow velocity component on transverse condensing direction of fibres in bundle has the direct condensing effect, which is beneficial for ameliorating evenness. The flow velocity component on output and thickness direction of fibres in bundle has the assistant condensing effect and can improve spun yarn strength and reduce yarn hairiness

Properties of knitted fabric made from modified ring-spun yarn

A modified ring spinning system, wherein a kind of airflow twisting device is equipped for improving the twist propagation process of ring spinning system, has been used to spun three different yarns, namely 29.2tex (Ne20), 14.6tex (Ne40), and 9.7tex (Ne60). The properties of corresponding knitted fabric, including the thickness, weight per square meter, distorted angle, bursting strength, and permeability are determined. The results show that the residual torque of spun yarn is reduced with both appropriate anticlockwise and clockwise directions of airflow. It is found that compared to knitted fabric made from conventional ring spinning system, the fabrics spun on modified spinning system show reduced thickness, weight per square meter and spirality angle; increased bursting strength; and improved permeability

Comparison of fibre migration in different yarn bodies

The qualities of yarn have been studied by analyzing the fibre migration in the yarn body. The effects of spinning method and raw fibre property on fibre migration have been studied using the tracer fibre technique. Compact-spun (60s Ne), ring-spun (60s and 10s Ne) and rotor-spun (10s Ne) (cotton) yarns have been prepared. However, for the compact-spun yarns, both pure cotton and polyester/cotton blended yarns have been prepared. Two mixing steps have been used, namely (i) the dyed cotton fibre mass is homogeneously mixed with the undyed cotton fibre mass by hand, and (ii) the mixed fibre agglomerates are then subjected to carding to obtain a more uniform mixture. Finally, five sets of yarns are obtained through the consequent spinning process. Fibre measuring system is used to watch the movement of tracer fibres and to get the migration parameters as well as their envelope lines. The results show that the fibre migration of the ring spinning yarn is the most obvious, followed by the compact spinning yarn. The rotor spinning yarn has so many wrapped structures that the fibre migration is not obvious. Polyester/cotton blended yarn, which has better yarn levelness, higher breaking strength and less hairiness, shows higher degree of fibre migration than the yarn made of pure cotton

Numerical analysis of the slub yarn breaking strength using finite element method

The numerical analysis of the slub yarn breaking strength has been made by using the finite element method (FEM). The slub yarn has been considered as skeletal structures since the yarn longitudinal length is much larger than its horizontal cross-section. Then, the accuracy of the proposed FEM model in calculating the slub yarn breaking strength has been validated by comparing the calculated results with the experimental data. This model can be used to calculate the slub yarn breaking strength normally and provides a theoretical support for product design

Effects of godet wheel position on compact siro-spun core yarn characteristics

Cotton-spandex compact siro-spun core yarns (29.2tex/44.4dtex and 14.6tex/44.4dtex) have been prepared on two kinds of compact spinning, viz complete condensing spinning system (CCSS) and lattice apron compact spinning system (LACSS) respectively. Three godet wheel positions on two kinds of compact system have been selected and corresponding yarn covering effect is studied respectively. Especially, the surface morphology and cross-sections of the core yarns are observed. Then, the covering effects are compared and affecting factors are analyzed. Moreover, other yarn properties including yarn hairiness, strength and evenness are also tested and compared. The results indicate that the covering effect of staple fibres is the most even when the godet wheel position is set on left side for both CCSS and LACSS

On the combination of adaptive neuro-fuzzy inference system and deep residual network for improving detection rates on intrusion detection

Deep Residual Networks (ResNets) are prone to overfitting in problems with uncertainty, such as intrusion detection problems. To alleviate this problem, we proposed a method that combines the Adaptive Neuro-fuzzy Inference System (ANFIS) and the ResNet algorithm. This method can make use of the advantages of both the ANFIS and ResNet, and alleviate the overfitting problem of ResNet. Compared with the original ResNet algorithm, the proposed method provides overlapped intervals of continuous attributes and fuzzy rules to ResNet, improving the fuzziness of ResNet. To evaluate the performance of the proposed method, the proposed method is realized and evaluated on the benchmark NSL-KDD dataset. Also, the performance of the proposed method is compared with the original ResNet algorithm and other deep learning-based and ANFIS-based methods. The experimental results demonstrate that the proposed method is better than that of the original ResNet and other existing methods on various metrics, reaching a 98.88% detection rate and 1.11% false alarm rate on the KDDTrain+ datase