Wyniki wyszukiwania - BazTech

1

Study on an Optimal Design of Mechanical Properties for PP/PET Nonwovens

Su T. L., Gui-Bing H.

Fibres & Textiles in Eastern Europe

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2012

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Vol. 20, no. 5 (94)

75--79

EN

This study aimed to determine the optimal process parameters of needle-punched nonwoven fabrics, and obtain the maximal strength of needle-punched nonwoven fabrics. The Taguchi approach and grey relational analysis were used to solve the multi-quality optimisation problem and determine the optimal process parameter combination of needlepunched nonwoven fabrics. The L9 orthogonal array was used to design parameters that affect the needle-punched nonwoven fabric process, including the folding machine oscillating speed, folding machine conveying speed, needle-punch depth, and needle-punch density. Then grey relational analysis was used to overcome the single quality characteristic disadvantage of the Taguchi approach, and the optimal process parameter combination of multiple quality characteristics was obtained from the response graph of the analysis. The quality characteristics of this experiment are the nonwoven fabric tearing strength and tensile strength. Signal-to-noise ratios (S/N ratio) were calculated and an analysis of variance (ANOVA) was conducted to analyse the experiment results. The results of ANOVA showed that the factors with a significant effect on the quality characteristics of needlepunched nonwoven fabrics included the needle-punch depth and needle-punch density. In other words, by controlling these factors the quality characteristics of the needle-punched nonwoven fabrics could be controlled effectively. Finally, the 95% confidence interval of the verification experiment proved that this experiment was reliable and reproducible

PL

Celem pracy było wyznaczenie optymalnych parametrów procesu, otrzymywanie włóknin igłowanych dla uzyskania optymalnych właściwości, w tym możliwie jak największej wytrzymałości mechanicznej. Zastosowano metodę Taguchi i analizę zbiorów rozmytych. Jako parametry wyjściowe przyjęto: prędkość oscylacji maszyny igłującej, szybkość transportową, głębokość igłowania oraz gęstość przeigłowań. Optymalizację przeprowadzano pod kątem uzyskania maksymalnej wytrzymałości włókniny oraz odporności na rozrywanie. Przy analizie określano poziom szumów sygnału oraz przeprowadzono analizę wariancji. Stwierdzono, że najistotniejszymi parametrami, które muszą być kontrolowane w czasie produkcji włókniny są głębokość i gęstość przeigłowań.

2

Improving the Quality of Combed Yarn Spun by OE Rotor Spinning Using the Grey-Taguchi Method

Su T. L., Chen H. M., Ma C. M., Lu C. F.

Fibres & Textiles in Eastern Europe

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2011

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Vol. 19, no. 2 (85)

23-27

EN

Open-end (OE) rotor spinning is a high-productive-efciency as well as a space and energy saving method of producing combed yarns with better evenness, regularity and abrasion resistance, as well as a brighter shade and sharpness. However, the setting of process parameters decides yarn quality, which can be done only afer accumulating experience involving tremendous cost, time and manpower. Firstly, the L9(34) orthogonal array is used to plan the process parameters that have an impact on OE rotor spinning. In this study, the experimental quality characteristrics focused on are the strength and unevenness of combed yarns. Aferwards grey relational analysis is used to establish individual quality characteristics, the demerit of the Taguchi Method, and an optimal set of process parameters of multiple quality characteristics obtained from a response graph of the grey relational analysis. Moreover, a signal-to-noise ratio computation and analysis of variance (ANOVA) are conducted to evaluate the results of the experiments. Using ANOVA, the signifcant factors impacting the quality characteristics of combed yarns are obtained; that is, control over the preceding factors indicates valid control over the quality characteristics of combed yarns. Finally, the reliability and reproducibility are verifed at a 95% confdence interval of the confrmation experiments.

3

Automated Vision System for Recognising Lycra Spandex Defects

Su T. L., Lu C. F.

Fibres & Textiles in Eastern Europe

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2011

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Vol. 19, no. 1 (84)

43-46

EN

Fabric defect detection and classifcation plays a very important role in the automatic detection process for fabrics. This paper refers to the seven commonly seen defects of lycra spandex: laddering, end-out, hole, oil spot, dye stain, snag, and crease mark. First of all, the gray level co-occurrence matrix was used to collect the features of the fabric image texture, and then the back-propagation neural network was used to establish faw classifcations of the fabric. In addition, by using the Taguchi method combined with BPNN, the BPNN drawback was improved upon, which requires overly time consuming trial-and-error to fnd the learning parameters, and could therefore converge even faster with an even smaller convergence error and better recognition rate. The experimental results proved that the fnal root-mean-square error convergence of the Taguchi-based BPNN was 0.000104, and that the recognition rate can reach 97.14%.

4

Grey relational analysis of an automatic identifying system for clothing texture

Su T. L., Kuo Y.-L., Chen H.-W., Kung F.-C.

Fibres & Textiles in Eastern Europe

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2010

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Vol. 18, no. 2 (79)

60--64

EN

Fabric quality inspection is important to the textile industry because the price of second-quality fabric is merely 45% to 65% of that of first-quality fabric. Using the wavelet transform, this paper intends to analyse fabric images and establish the different features of fabric texture, and then through grey relational analysis of grey theory, we will attempt to distinguish and classify the texture of fabrics, mainly cotton, polyester, silk, rayon, knitting and linen. The grey relational analysis approach is applied to analyse the correlation in the random factor sequence of feature indexes after some data processing and determine the texture type of the designated fabric on the basis of the highest correlative degree. Experiment findings show that the automatic distinguishing system for the fabric types discussed in this paper is capable of distinguishing six different textile images.

PL

Kontrola jakości płaskich wyrobów włókienniczych jest bardzo ważna w przemyśle tekstylnym ze względu na różnice cenowe pomiędzy tekstyliami wyższej i niższej jakości. Wykorzystując odpowiednie przekształcenia matematyczne przeprowadzono analizę obrazów tekstyliów i na podstawie teorii zbiorów rozmytych zidentyfikowano struktury badanych próbek, w tym tekstyliów z bawełny, poliestru, jedwabiu, sztucznego jedwabiu i lnu. Ostateczną identyfikację badanej struktury przeprowadzono na podstawie współczynnika korelacji. Udowodniono, że automatyczny system rozróżniania rodzajów tekstyliów nadaje się do praktycznego zastosowania.