Substituting computer vision for human eyes in the practice of fabric defect detection can enhance the detection efficiency, decrease labor force, reduce labor intensity and further improve product quality, and, consequently, can satisfy the demands of society for high-efficiency production as well as high-quality products. 1 There exist multifarious fabric defects that appear on a wide variety of fabrics in terms of material, weave, structure and density. Because Abstract For the purpose of realizing fast and effective detection of defects in woven fabric, and in consideration of the inherent characteristics of fabric texture, i.e., periodicity and orientation, a new approach for fabric texture analysis, based on the modern spectral analysis of a time series rather than the classical spectral analysis of an image, is proposed in this paper. Traditionally, a power spectral estimated by a two-dimensional Fast Fourier transformation (FFT) is usually employed in the detection of fabric defects, which involves a large computational complexity and a relatively low accuracy of spectral estimation. To this effect, this paper makes a one-dimensional power spectral density (PSD) analysis of the fabric image via a Burg-algorithm-based Auto-Regressive (AR) spectral estimation model, and accordingly extracts features capable of effectively differentiating normal textures from defective ones. A support vector data description is adopted as a detector in order to deal with defect detection, a typical task of one-class classification. Experimental results for the detection of defects from several fabric collections with different texture backgrounds indicate that a low false alarm rate and a low missing rate can be simultaneously obtained with less computational complexity. Comparison of the detection results between the AR model and the FFT method confirms the superiority of the proposed method.

A mechanical analysis is made on the changing cross-sectional segment of the fibre band in the condensing zone of compact spinning. By analysing the condensing process of fibre band in the condensing zone, a mechanical model for the changing cross section is established in this article. The model further validates the fact that there exist additional twists in this part of fibre band from both theoretical and numerical points of view. Besides, the three major factors, that is, the friction coefficient between fibre band and the lattice, the underpressure and the length of suction, are also analysed, revealing that the larger the three factors are, the larger the additional twists will be.

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