Wyniki wyszukiwania - BazTech

1

Design and analysis of the ferrite air-gapped cores for a resonant inductor

Zheng J., Wang Ch., Xia D.

Archives of Electrical Engineering

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2018

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Vol. 67, nr 3

579–-589

EN

In this paper, a three-air-gapped structure of a ferrite core for a resonant inductor is proposed. The electromagnetic and thermal field models are built using a 3D finite element method. Compared with the conventional signal-air-gapped structure of a ferrite core, the simulation and analysis results show that the proposed three-air-gapped ferrite core resonant inductor can reduce eddy-current loss and decrease temperature rise. In addition, the optimal position of air-gapped is presented.

2

Warp-knitted Fabric Defect Segmentation Based on the Shearlet Transform

Dong Z., Xia D., Ma P., Jiang G.

Fibres & Textiles in Eastern Europe

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2017

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Vol. 25, no. 5 (125)

87--94

EN

The Shearlet transform has been a burgeoning method applied in the area of image processing recently which, differing from the Wavelet transform, has excellent properties in processing singularities for multidimensional signals. Not only is it similar to the performance of the Curvelet transform, it also overcomes the disadvantage of the Curvelet transform with respect to discretization. In this paper, the Shearlet transform with segmented threshold de-nosing is proposed to segment a warp-knitted fabric defect. Firstly a warp-knitted fabric image of size 512*512 is filtered by the Laplacian Pyramid transform and decomposed into low frequency and high frequency coefficients. Secondly the high frequency coefficients are operated with a pseudo-polar grid and then convoluted by the window function. Thirdly the shearlet coefficients will be obtained through redefining the Cartesian coordinates from the pseudo-polar grid coordinates and de-noised by the segmented threshold method. Then the coefficients which have high energy are selected for reconstruction in an inverse way using the previous steps. Finally the iterative threshold method and object operation based on morphology are applied to segment out the defect profile. The experiment’s result states that the Shearlet transform shows excellent performance in segmenting a common warp-knitted fabric defect, indicating that the segment results can be applied for further defect automatic recognition.

PL

Transformacja Shearleta jest ostatnio dynamicznie rozwijającą się metodą stosowaną w dziedzinie przetwarzania obrazu, która różni się od transformaty Wavelet i ma doskonałe właściwości w przetwarzaniu sygnałów wielowymiarowych. Transformacja Shearleta ma prostszą implementację dyskretną, niż przekształcenie Curveleta w oparciu o rygorystyczne i proste ramy matematyczne. Może także dostarczyć bardziej elastycznego rozkładu na podstawie reprezentacji wieloskalowej i geometrycznej. Ostateczny wynik segmentacji uzyskano poprzez powtarzalną segmentację progową i operację morfologiczną. Wyniki wykazały, że segmentowy profil uszkodzeń jest dość wyraźny i porównywalny w porównaniu z pierwotnymi wadami dzianiny.

3

Warp-Knitted Fabric Defect Segmentation Based on Non-Subsampled Wavelet-Based Contourlet Transform

Xia D., Jiang G., Ma P.

Autex Research Journal

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2017

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Vol. 17, no. 4

319--327

EN

In this paper, a non-subsampled wavelet-based contourlet transform (NWCT) is applied in warp-knitted fabric defect segmentation. Compared with the traditional contourlet transform, wavelet transform takes the place of Laplacian pyramid in NWCT and the directional filter bank is non-subsampled. The wavelet transform with improved wavelet threshold is put to use, and the original fabric image can be decomposed into low-frequency approximate coefficient A and high-frequency detail coefficients V, H, and D. The high-frequency detail coefficients are processed by the non-subsampled directional filter bank to get directional sub-band coefficients. Afterward, the effective sub-band coefficients based on regional energy are chosen to reconstruct V, H, and D. And the reconstructed fabric image will be achieved by inverse non-subsampled wavelet-based contourlet transform. The adaptive threshold method and morphological processing are used to obtain the legible defect profile. The experiment demonstrates that NWCT can achieve the positive segmentation regarding the common defects, such as broken warp, width barrier, and oil, and has excellent performance on these directional defects and regional defects. It is acknowledged that NWCT will provide a new way to detect warp-knitted fabric defects automatically.