扁平经纱在织机上无捻加工的解决方案

这个项目所取得的结果展示了如何采用扁平经纱织造致密面料的方法,这种方法既可实现高产量和高质量,又可改善材料的各种特性.因此,这种织物的应用领域可进一步拓展.这些改造采用的都是市场上有售的部件,无需特别的手段.改造之后,经轴和织造区之间的自由纱段最小化、经纱张力更均匀.经轴和织造区之间根据扁平纱的几何形状设置导纱器,并应用了特殊的综丝,明显减少或避免了经纱在整个经纱方向出现捻度.     

Application of stitch-bonded multi-plies made by using the extended warp-knitting process: influence of pattern and knitting yarn tension on the geometry of the textile fabric

This paper is part of a series dealing with the application of the extended warp‐knitting process for the production of textile fabrics for composites. Further studies will examine the properties of thermoplastic composites and textile reinforced concrete made of stitch‐bonded multi‐plies. It is known that knitting yarn pattern and knitting yarn tension during fabric production affect the properties of stitch‐bonded multi‐plies and composites made thereof. This paper describes the effects of those two parameters on the fabric as produced with the extended stitch‐bonding process. It can be shown in which way pattern and yarn tension can be chosen to reduce compression of the warp threads in the fabric as well as to avoid unwanted displacement of threads caused by handling.     

Numerical simulation of yarn tensile force for dynamic yarn supply systems of textile machines

During the production of textiles, quality problems arise with increasing machine speed due to high dynamic stresses in the yarn supply system. Based on the large number of influencing factors in this process, an analysis of the cause of the errors is only possible with high experimental effort or, due to sporadic errors, not at all. The yarn tensile force is the critical parameter and its simulation in the entire yarn supply process opens a wide range of opportunities for analysis and optimization. First, a mathematical model based on the invariance of the mass of a yarn piece and the non‐linear elongation behavior of the yarn is constructed and the influencing factors of the essential elements of yarn supply cone, feeder, and eyelet on the yarn tensile force are described. The simulation is carried out using the software package Matlab/Simulink in which the created sub‐elements can be combined optionally and can be duplicated, which allows a simple and quick adjustment of any yarn supply system in textile machinery. On the basis of comparative measurements, it is shown that the simulation predicts the yarn tensile force, for example extreme situations in the yarn supply process, such as the insertion of the yarn into knitting machines, in a very good approximation to reality. The simulation is transferable to other yarn supply systems of the textile technology by extending the yarn supply sub‐element database.     

Olive mill wastewater degradation by Fenton oxidation with zero-valent iron and hydrogen peroxide

The degradation of olive mill wastewater (OMW) with hydroxyl radicals generated from zero-valent iron and hydrogen peroxide has been investigated by means of chemical oxygen demand (COD) and phenolic compounds analyses. The effects of the H2O2 dose, the pH and the organic matter concentration have been studied. The optimal experimental conditions were found to have continuous presence of iron metal, acid pH (2.0-4.0), and relatively concentrated hydrogen peroxide (9.5M). Coloration of OMW disappeared and phenolic compound decreased to 50% of initial concentration after 3h reaction time. The application of zero-valent Fe/H2O2 procedure permitted high removal efficiencies of pollutants from olive mill wastewater. The results show that zero-valent Fe/H2O2 could be considered as an effective alternative solution for the treatment of OMW or may be combined with a classical biological process to achieve high quality of effluent water.     

Prediction of yarn crimp in PES multifilament woven barrier fabrics using artificial neural network

This research was aimed to develop artificial neural network (ANN) models to predict yarn crimp in woven barrier fabrics. For ANN training, 52 polyester (PES) multifilament barrier fabrics were produced by varying weft yarn and filament fineness, yarn type, weft density, weave type, and loom parameters. The supervised training of neural network was performed using Matlab® ANN toolbox function ‘trainbr’ which is the incorporation of Levenberg-Marquardt (LM) optimization and automated Bayesian regularization into backpropagation. From modeling outcomes, it was observed that both warp and weft yarn crimp models have generalized well with excellent coefficient of determination and trivial mean absolute error when tested on novel data. Moreover, input rank analysis of optimized network provided important information about model stability with respect to input variables, and trend analysis elucidated the input-crimp behavior using different input levels.     

Local generic representation for patch uLBP-based face recognition with single training sample per subject

Multimedia Tools and Applications - In this paper, we propose a novel paradigm of Patch uniform Local Binary Patterns (PuLBP) based Local Generic Representation (LGR) for face recognition. Indeed,...