Contribution of ring spinning process to the fibre-shedding behaviour of cotton yarn during knitting

The artificial neural network model is used to predict the breaking elongation of polyester/cotton ring spinning yarn in this paper. In order to achieve the objective, a series of trials is conducted. The prediction values and actual test values of which are found to be rather close. Therefore, the artificial neural network model proves to be more feasible in the prediction of breaking elongation of polyester/cotton ring spinning yarn.

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Mathematical Modeling of Dynamic Yarn Path Considering the Balloon Control Ring and Yarn Elasticity in the Ring Spinning Process Based on the Superconducting Bearing Twisting Element

Fibres and Textiles in Eastern Europe ◽

10.5604/01.3001.0012.2528 ◽

2018 ◽

Vol 26 (5(131)) ◽

pp. 32-40 ◽

Cited By ~ 2

Author(s):

Mahmud Hossain ◽

Christian Telke ◽

Anwar Abdkader ◽

Maria Sparing ◽

Tilo Espenhahn ◽

...

Keyword(s):

Magnetic Bearing ◽

Spindle Speed ◽

Frictional Heat ◽

Ring Spinning ◽

German Research Foundation ◽

Yarn Tension ◽

Tension Distribution ◽

Spinning Process ◽

Fundamental Research ◽

Superconducting Magnetic Bearing

The productivity of the conventional ring spinning process is currently limited by the frictional heat that occurs in the ring/traveler twisting system. In the framework of a fundamental research project from the German Research Foundation (DFG), the levitation principle of superconducting magnetic bearing (SMB) was implemented as a twisting element in order to eliminate the frictional problem and thus aim, at least, to double the productivity. A mathematical model of the dynamic yarn path has already been presented considering the friction free SMB system up to an angular spindle speed of 25,000 r.p.m. In this paper, the existing theoretical model, which was developed up to 25,000 r.p.m, was further modified considering the balloon control ring and yarn elasticity at a higher angular spindle speed, such as 50,000 r.p.m. The model was solved numerically using the RUNGE-KUTTA method. With this model, it is possible to estimate the yarn tension distribution and balloon form considering the above-mentioned parameters. The model established was further validated by comparing the yarn tension and balloon forms predicted with measured ones up to an angular spindle speed of 15,000 r.p.m in a ring spinning tester based on superconducting magnetic bearing.

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INfluence of Some Mechanical Factors of Ring Spinning Machine on Cotton Yarn Quality

Journal of Applied Sciences ◽

10.3923/jas.2002.453.456 ◽

2002 ◽

Vol 2 (4) ◽

pp. 453-456 ◽

Cited By ~ 3

Author(s):

Iftikhar Ahmad . ◽

Nisar Ahmad Jamil . ◽

Nadeem Haider .

Keyword(s):

Cotton Yarn ◽

Ring Spinning ◽

Yarn Quality ◽

Mechanical Factors

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Reducing Yarn Hairiness in a Modified Ring Spinning Yarn Path by Various Offsets

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.331.493 ◽

2011 ◽

Vol 331 ◽

pp. 493-497

Author(s):

Xu Zhong Su ◽

Wei Dong Gao ◽

Ting Ting Wu ◽

Xin Jin Liu ◽

Yun Zhang

Keyword(s):

Critical Region ◽

Breaking Force ◽

Ring Spinning ◽

Fiber Tension ◽

Yarn Properties ◽

Spun Yarns ◽

Spinning Process ◽

Spinning Triangle ◽

Yarn Hairiness ◽

The Right

Spinning triangle is a critical region in the spinning process of yarn. Its geometry influences the distribution of fiber tension in the spinning triangle and the properties of spun yarns, such as the yarn breakage and hairiness. In this paper, the relationships between the spinning angle and yarn properties especially the yarn hairiness were investigated under various horizontal offsets. The properties of spun yarns produced by the modified system were evaluated and analyzed. Both left diagonal and right diagonal yarn arrangements were examined. The results indicate that the right diagonal yarn path leads to reduce yarn hairiness but the left diagonal yarn path leads to increase yarn hairiness; the breaking force of yarn changes little; yarn evenness deteriorates slightly with the changes of offset.

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Spinning Process and Mechanical Properties Analysis of PTT Filament Core Spun Yarn

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.239-242.1207 ◽

2011 ◽

Vol 239-242 ◽

pp. 1207-1210

Author(s):

Yuan Xue ◽

En Long Yang

Keyword(s):

Mechanical Properties ◽

Mechanical Property ◽

Elastic Recovery ◽

Staple Fiber ◽

Ring Spinning ◽

The Core ◽

Outer Sheath ◽

Spun Yarn ◽

Two Component ◽

Spinning Process

The two component filament/staple fiber core-spun yarn is spun on FA506 ring spinning frame with PTT filament as interlaced yarn and Tencel staple fiber as outer sheath. The spinning process and process parameters were analyzed. The morphology, mechanical property and wear-resisting property of two component core-spun yarn were tested. Results indicate that elastic recovery rate of core-spun is up to 90.6%; broken strength is up to 20 cN/tex after boiling water treatment. The core-spun yarn can be used as a new kind of knitting yarn for sweater.

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Evolution Regularity of Temperature Filed in Hot Power Backward Spinning for 7075 Cast Aluminium Alloy Tube

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.774-776.1170 ◽

2013 ◽

Vol 774-776 ◽

pp. 1170-1173 ◽

Cited By ~ 1

Author(s):

R.Y. Zhang ◽

S.J. Tu ◽

G.Y. Zhao ◽

J. Wang ◽

Z.H. Guo

Keyword(s):

Aluminium Alloy ◽

Internal Surface ◽

Fe Model ◽

Outer Face ◽

Key Factors ◽

Ring Spinning ◽

Alloy Tube ◽

Temperature Filed ◽

Spinning Process ◽

Lock Ring

The spinning temperature is one of key factors affected the uneven deformation during the hot power backward spinning for brittle material tubes, such as cast 7075 aluminium alloy tube. To analyze the evolution regularity of temperature filed in the spinning process, a 3D thermo-mechanical FE model of the process is developed under ABAQUS/Explicit environment. Then, the evolution of temperature filed during the process is analyzed based on the FE model. The results show that: The contact areas temperatures between lock ring, spinning rollers and tube decrease sharply during the initial spinning stage. The high temperature region is transferred from unformed zone of the tube to the contact area between spinning roller and tube. In the spinning zone, the temperature of internal surface of the tube is apparently higher than that of outer face.

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Analysis of Process and Properties of Stainless Steel Filament Wrapped Yarn Based on Multi-Axial Ring Spinning

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.332-334.743 ◽

2011 ◽

Vol 332-334 ◽

pp. 743-746

Author(s):

Cheng Liang Deng ◽

Zhao Qun Du ◽

Wei Dong Yu

Keyword(s):

Mechanical Properties ◽

Stainless Steel ◽

Process Optimization ◽

Steel Wire ◽

Ring Spinning ◽

Excellent Performance ◽

The Core ◽

Axial Ring ◽

Spinning Process ◽

Core Yarn

A new spinning method was presented to spin three-axial stainless steel filament wrapped yarn by modified ring-spinning, where the stainless steel filament was set as the core yarn and the nylon filament for decoration wrapping the stainless steel filament in the fields of the fabric for Shielding application. A set of process parameters was obtained by the ring spinning frame improvement and spinning process optimization, which realized to spin nylon filament wrapped stainless steel filament yarn. Moreover, the structure, and tensile mechanical properties were measured on the wrapped yarns. The results show that the process can spin stainless steel wire wrapped yarn and acquire the excellent performance of the yarn.

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Applications of Neural Networks in the Hairiness of Ring Spinning Polyester/Cotton Yarn Prediction

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.549.1055 ◽

2012 ◽

Vol 549 ◽

pp. 1055-1059

Author(s):

Bo Zhao

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Model ◽

Neural Network Model ◽

Processing Parameters ◽

Cotton Yarn ◽

Ring Spinning ◽

Artificial Neural ◽

Yarn Hairiness ◽

Bp Neural Network Model

In this paper, back-propagation (BP) neural network model is introduced and established. This work describes the application of the BP artificial neural network model for the purpose of predicting the polyester/cotton yarn hairiness. This approach has been developed and evaluated with the use of multiple sets of data, comprising of a range of processing parameters. The yarn hairiness of ring spinning is strongly related to the processing parameters. However, it is difficult to establish physical models on the relationship between the processing parameters and the yarn hairiness. Due to the artificial neural network can fully approximate any complex nonlinear system and study dynamic behavior of any serious undetermined system. It has a highly parallel calculation ability, strong robustness and fault tolerance. So using the artificial neural network to predict the polyester/cotton yarn hairiness of ring spinning is a very effective way. The experimental results and corresponding analysis show that the BP neural network model is an efficient technique for the yarn hairiness of ring spinning prediction and has wide prospect in the application of ring spinning yarn production system.

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