Textile Research Journal

We have developed analysis tools to characterize nonwoven web structures based on image analysis techniques. Six analysis modules we previously reported are integrated into one automated instrument system. In this paper, we discuss hardware and software designs used to achieve instrument flexibility, automated operation, and multifunctional analysis capability. We hope this discussion will be useful to other people interested in textile instrument development and automated testing.

Theoretical considerations of changes in fiber length during technological processes are presented along with an experimental study. Special attention is paid to the combing process. A comparison of fiber length results measured by AFIS and MShU is given at different stages along the particular technological processes.

Low temperature plasma treatments of wool modify only the cuticle surface of the fibers, improving their surface wettability, dyeability, fiber cohesion, and shrink resistance. The shrink-resist properties obtained with plasma treatment do not impart a machine-washable finish, which is an important end-user demand. However, the shrink resistance of air plasma. treated wool is suitably enhanced by a subsequent biopolymer chitosan application. Using a qualitative colorimetric method, chitosan adsorption is shown to increase after treatment with air plasma. SEM observations yield information about the etching effect and chitosan adsorp tion. Given that both kinds of treatments, air plasma and chitosan, are environmentally acceptable, a new ecological shrink-proofing process is proposed.

Our early model for predicting nonwoven fabric stress-strain behavior by the finite element method is generalized to include the effects of fiber curl, which is shown to have a great effect on the tensile behavior of the fabric. A numerical method to characterize the lateral contraction of nonwovens during tensile deformation is presented. The effects of fiber arrangement characteristics on the mechanical properties of nonwovens are studied through laboratory experiments and theoretical analysis. The effects of varying thick nesses within the nonwovens on fabric strength, modulus, and stress-strain distribution are also examined. Tensile testing of several nonwoven fabrics verifies the theoretical results.

We investigate the dyeing characteristics of silk proteins produced by silkworms reared entirely on an artificial (A) diet, and compare them with those of worms raised entirely on a mulberry leaf (M) diet. The artificial diet has tofu-cake as its main component. Two kinds of cocoons (A and M) are used as the original sample materials. The A and M raw silk samples are prepared from cocoon samples by the usual filature process. Sericin contents of the A and the M raw silk samples are 26% and 23.7%, respectively. The A and the M fibroin samples are prepared from each raw silk sample by extracting the sericin proteins with 0.5% sodium carbonate at the boil for 30 minutes. Dyeing experiments on the raw silk and the fibroin samples using an acid dye (CI Acid Orange 7, O-7) at pH 3.9 and 60°C show that the dyeing rate and dye concentration on the A fibroin are almost the same as those on the M fibroin samples. On the other hand, dye concentration on the A raw silk is much higher than that on the M raw silk samples, meaning that the dye concentration on the A sericin is much higher than that on the M sericin.

The theoretical basis of a technique for real time defect detection in fabrics is presented using a joint transform correlator. This correlation technique is an extension of Fourier transform analysis and is extremely useful for real time pattern recognition. The regular periodic nature of a woven fabric makes it possible to use the Fourier transform technique to detect defects. However, classifying various defect types is difficult from the Fourier analytical and experimental results. A solution to this problem is to use a joint Fourier transform of a reference pattern and the test pattern, and the joint power spectrum is further processed. Cross- and auto-correlation peaks, generated after the execution of the second Fourier transform on the filtered joint power spectrum, indicate the existence of a particular defect type. Because of the parallel processing ability of the optical system, implementing the joint transform correlation technique in an optical domain is advanta geous. A fractional power fringe adjusted filter is used for efficient detection of defects. The mathematical formulation of the technique is supported by the simulated results for identifying some defects such as the existence of thick yarns, knots, and missing yarns.

A new quantitative method to evaluate seam pucker with five shape parameters is proposed using three-dimensional image analysis and artificial intelligence. The shape parameters include the number of wave generating points, the wave amplitudes, and the wavelengths on the line next to the seam and on the edge line. Measured shapes of puckered fabrics are converted into numerical data in the three-dimensional coordinate system, and the data are transformed into power spectra using fast Fourier transformation. Also, artificial intelligence techniques, including neural networks and fuzzy logic (or neurofuzzy algorithm), are used to recognize the characteristics of seam pucker. To obtain better quantitative evaluations of seam pucker, 300 neurofuzzy engines are constructed and trained using reference puckered shapes produced by the simulator described in Part I. Power spectra of the measured data are transformed into specified fuzzy patterns through the fuzzification process to train the neurofuzzy engines. The five shape param eters of puckered shapes are obtained from pattern recognition by the trained neurofuzzy engines through the defuzzification process.

Low temperature plasma treatments are applied to linen with oxygen and argon at various discharge power levels and exposure times. Their effects on bulk structure, surface morphology, flax fiber properties, and related fabric properties are investigated with a range of analytical methods. X-ray photoelectron spectroscopy reveals that the surface oxygen content of the plasma treated samples increases, which is supported by the results from fabric whiteness tests. Formation of voids and cracks on fiber surfaces is revealed by scanning electron microscopy. There is no significant change in x-ray crystallinity and cuprammonium fluidity, but there is a slight reduction in moisture regain for all plasma treated samples. Fabric weight loss increases with exposure time. Fabric water uptake and strength first increase and then decrease with prolonged exposure, whereas fabric bending rigidity, hysteresis, and wrinkle recovery improve slightly.

The scanning electron microscope is able to provide excellent differentiation between endangered Tibetan antelope and currently used Ibex goat hair fibers for "Shahtoosh" shawls. Although there are differences in the features of the fine hair fibers from these animals, the best differentiation is accomplished by using the significant differences found in the guard hair fibers that are inextricably mixed with the softer, smaller diameter hairs. The larger diameter antelope guard hairs have extremely thin walls, a cuticle structure, and a unique scale pattern that is totally different from those of the Ibex goat. Some of this important information is not as vividly apparent in a light microscope study.

A device for wrinkle recovery measurements involves the installation of a laser sensor. The shapes of fabric wrinkles are described by magnitude and sharpness using power spectra obtained from two-dimensional fast Fourier transformation and the distribution of fabric surface angles obtained from spline interpolation and vector operation. For the objective evaluation of wrinkle recovery, artificial neural networks are used rather than the AATCC subjective evaluation method. Five kinds of input patterns are categorized from the characterizations of wrinkle shape, and these are supplied to the neural networks for evaluation. Objective results from the neural networks are compared with subjective ones from human experts. The relationship is good with a correction coefficient of 0.95, but wrinkle rank depends somewhat on the color or pattern of the fabric.

This is a review article of the various experimental approaches used for measuring fabric mechanical properties important in apparel handling, including the biaxial tension and in-plane shear parameters. First, the paper discusses the important issues encountered during such a fabric test. Then most existing biaxial tension and shear fabric testers are introduced and critically analyzed. Based on this information, a new tester concept is proposed in which tensile and shear forces can be applied simultaneously.

Spectrometer measurements of the color of cotton based on CIE standards are investi gated and compared with high volume instrumentation (HVI) methods. Additionally, color imaging and spatial interpretation are examined with the intent of demonstrating the importance of color uniformity, trash content, and yellow spots on classer color grading. The result is that agreement between HVI color grading and the cotton classer can likely be enhanced by including the CIE color space redness parameter α*, trash content, and yellowness variability.