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2022 International Symposium on design Studies and Intelligence engineering, DSIE 2022

作者： Ni, Jialu Shi, Wenhui Xu, Pinghua Wei, Qiuju Sun, Xiaowan Zhou, Yanmo School of Fashion Design and Engineering Zhejiang Sci-Tech University Hangzhou Zhejiang310018 China Clothing Engineering Research Center of Zhejiang Province Hangzhou Zhejiang310018 China Key Laboratory of Silk Culture Inheriting and Products Design Digital Technology Ministry of Culture and Tourism Hangzhou Zhejiang310018 China School of Fashion Design and Engineering Zhejiang Sci-Tech University Xiasha Higher Education Park 928 2nd Street Qiantang New Area Zhejiang Province Hangzhou310018 China

ISBN: (纸本)9781643683720

In order to reduce the interference of stripe signal on the density automatic measurement of woven fabric and extend the the application scope, an adaptive Gaussian Notch Filtering (GNF) algorithm based on Fast Fourier transform is proposed. In the pre-proceesing stage, the Fourier transform was utilized to transform the woven fabric bitmap to spectral image, as to obtain the spectral characteristics of the striped fabric. The improved GNF algorithm was used to identify the peak of stripe signal, which determined the bandwidth radius and locate the stripe bright area. Based on the fused Fourier and GNF spectral map, interference frequency information was accurately removed and spatial map was restored to approximate pure color fabric image. Finally, the Morlet wavelet is utilized to analysis the density of the striped printed fabric. The experimental results show that the average subjective-objective consistency rate (AS-OCR) of the designed sample is 99.34%, and the range is 97.33%â 100%. The AS-OCR of the actual sample is 98.73%, ranging from 95.00% to 100%. The proposed method can effectively obtain the density of stripe printed woven fabric and expand the application scope of fabric density automatic detection. © 2023 The authors and IOS Press.

关键词： Wavelet transforms

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Analysis of Decoupling Between Economic Development and Carbon Emissions in the Textile Industry in zhejiang province, China 8th

Analysis of Decoupling Between Economic Development and Carb...

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8th International Conference on Energy and Environmental Science, ICEES 2024

作者： Zhang, Ying Chen, Shuang Dong, Xueyu Huang, Qianwen Wang, Laili School of Fashion Design and Engineering Zhejiang Sci-Tech University Zhejiang Hangzhou310018 China Zhejiang Provincial Research Center of Clothing Engineering Technology Zhejiang Sci-Tech University Zhejiang Hangzhou310018 China Silk and Fashion Culture Research Center of Zhejiang Province Zhejiang Sci-Tech University Zhejiang Hangzhou310018 China Key Laboratory of Silk Culture Heritage and Products Design Digital Technology Ministry of Culture and Tourism Zhejiang Hangzhou310018 China

ISBN: (纸本)9783031639005

Based on the annual consumption data of terminal energy and economic output, this study calculated the carbon emissions, carbon emission intensity and carbon productivity of fashion industry in zhejiang province from 2006 to 2019, and analyzed the factors affecting the changes of carbon emissions and the relationship between the economic development of fashion industry and carbon emissions over the years by using LMDI method and decoupling theory. The results indicated that the total carbon emissions of fashion industry in zhejiang province showed fluctuations from 2006 to 2019, in which textile industry made the largest contribution to carbon emissions, followed by chemical fiber manufacturing industry. Meanwhile, Textile industry had the largest carbon emission intensity. Industrial technology was the main factor inhibiting the growth of carbon emission research in fashion industry in zhejiang province. The overall trend of decoupling between industrial economy and environmental pollution in zhejiang province is from non-decoupling to absolute decoupling, indicating that zhejiang province has adopted effective environmental protection policies and management measures and achieved good results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Carbon emission Decomposition Decoupling Fashion industry

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Texture characteristics parsing of basic stitch in simulation embroidery

Texture characteristics parsing of basic stitch in simulatio...

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2022 International Symposium on design Studies and Intelligence engineering, DSIE 2022

作者： Shi, Wenhui Ni, Jialu Xu, Pinghua Sun, Xiaowan Cai, Na School of Fashion Design and Engineering Zhejiang Sci-Tech University Hangzhou310018 China Clothing Engineering Research Center of Zhejiang Province Hangzhou310018 China Key Laboratory of Silk Culture Inheriting and Products Design Digital Technology Ministry of Culture and Tourism Hangzhou310018 China School of Fashion Design and Engineering Zhejiang Sci-Tech University 928 2nd Street Xiasha Higher Education Park Qiantang New Area Zhejiang Province Hangzhou310018 China

ISBN: (纸本)9781643683720

In order to fast identify and realistic simulate embroidery art, the respective texture characteristics of basic stitch in Simulation embroidery were extracted and preferred. Concretely, three feature extraction methods-gray co-occurrence matrix method (GLCM), Tamura method and gray difference statistics method (GDS), are combined to extract the features of embroidery needlework, and the best respected characteristics were compared and verified. Results shows that the best feature combination of needle texture in this paper is energy standard deviation, energy mean, standard deviation of moment of inertia, and mean of moment of inertia, which is defined as energy-moment of inertia feature. The proposed method effectively solves the inaccurate problem with single feature in the recognition of needle texture features, can be help for needlework recognition and virtual simulation. © 2023 The authors and IOS Press.

关键词： Textures

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Polynomial Improved Convolution Kernel Graph Network For Fault Diagnosis

Polynomial Improved Convolution Kernel Graph Network For Fau...

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Neural Networks, Information and Communication engineering (NNICE), International Conference on

作者： Huang Zhang Zili Wang Lemiao Qiu Shuyou Zhang Gaopeng Yang Feifan Xiang The State Key Laboratory of Fluid Power and Mechatronic System College of Mechanical Engineering Zhejiang University Hangzhou China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province Hangzhou China

Diagnosis is widely performed using convolutional neural networks (CNN). There are, however, limitations to CNN in non-Euclidean space. Based on the superiority of the graph convolutional neural networks (GCN) in non-Euclidean space, the GCN was adopted in this paper. In order to optimize the convolution process, the convolution kernel is approximated by four orthogonal polynomials, Chebyshev, Legendre, Laguerre, and Hermite. Then, ChebyNet, LegenNet, LargerNet, and HermiNet models are constructed using these four polynomials. According to the experimental results, HermiNet is superior when time-domain vibration signals are used as input, and LargerNet is superior when frequency-domain vibration signals are used.

关键词： Vibrations Fault diagnosis Convolution Frequency-domain analysis Chebyshev approximation Graph neural networks Convolutional neural networks

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design and performance of an air inflatable suit in enhancing personal thermal management

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Science China(Technological Sciences) 2023年第9期66卷 2637-2650页

作者： HE JiaZhen LU YeHu SU WenZhen WANG FangMing SONG WenFang WANG LaiLi WANG Min College of Textile and Clothing Engineering Soochow UniversitySuzhou 215021China Key Laboratory of Clothing Design and Technology Ministry of EducationDonghua UniversityShanghai 200051China Nantong Textile and Silk Industrial Technology Research Institute Nantong 226300China Suzhou Xingfengqiang Textile Technology Co. Ltd.Suzhou 215227China Garment Digital Engineering Center School of Art and DesignGuangdong University of TechnologyGuangzhou 510000China School of Fashion Design&Engineering Zhejiang Sci-Tech UniversityHangzhou 310018China

Maintaining human thermal comfort in cold indoor environments is crucial but usually involves excessive energy consumption and massive greenhouse gas emissions. Thermoregulating the human body by using advanced clothing is emerging as a promising solution to effectively and energy-efficiently achieve personal thermal management. An air inflatable suit(AirST)using a series of air chambers as the thermal insert was developed for the purpose of adjusting clothing thermal insulation and hence improving personal thermal comfort. The thermal insulation regulating performance of AirST was investigated through thermal manikin tests and wear trials. Compared with the AirST without air inflation, AirST after inflation with air had a desired effect, which could not only increase local clothing thermal insulation by a range from 4.5% to 24.8% but also alleviate cold strain and provide significantly higher local skin temperatures, mean skin temperature and mean body temperature. After inflation, AirST successfully improved the whole-, upper-and lower-body thermal sensations in a cool environment. The acceptable heating setpoint temperature by the air conditioner could be decreased while using AirST with inflation, which saved approximately 30% of building energy consumption. As the AirST without air inflation can also be worn as regular windproof clothing, this versatility saved approximately 12 kg CO_(2)e emissions in the production process.

关键词： air inflatable suit thermal comfort thermal insulation thermal management energy saving perceptual response

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Enhanced Energy Absorption of a Novel Skeletal-United Tubular Metamaterial Exhibiting Negative Poisson's Ratio

SSRN

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SSRN 2024年

作者： Fu, Mengyu Wang, Zili Zhang, Shuyou Gu, Yuchen Tan, Jianrong State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province Zhejiang University Hangzhou310027 China

The study introduces a novel approach to balancing energy absorption (EA) and negative Poisson’s ratio (NPR) in metamaterial design, which typically present desired properties and conflicting objectives. This is achieved by developing a skeletal-united tubular metamaterial (SUTM), created by splitting and reconstituting a central in-line skeleton within the unit structure of a traditional re-entrant tubular metamaterial (RETM). The innovation design from unit to tubular structure enables SUTM to achieve a compromise between high EA and improved NPR by leveraging the generated re-entrant skeleton. Experimental and numerical comparisons demonstrate that the SUTM outperforms the RETM in both EA and auxetic properties. Additionally, the tube adopts an uncommon out-plane configuration of metamaterials, so the study investigates the effects of various tubular geometric parameters, including tube thickness, diameter, and height, on EA and NPR. Furthermore, a series of SUTM variants are proposed and examined, highlighting the advantageous role of the skeleton generated from the corner of the unit cell in enhancing EA. © 2024, The Authors. All rights reserved.

关键词： Energy absorption

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Towards High-Accuracy Axial Springback: Mesh-Based Simulation of Metal Tube Bending Via Geometry/Process-Informed Graph Neural Networks

SSRN

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SSRN 2023年

作者： Wang, Zili Wang, Caicheng Zhang, Shuyou Qiu, Lemiao Lin, Yaochen Tan, Jianrong Sun, Chang State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province Zhejiang University Hangzhou310027 China

Springback has always been a stubborn defect that affects the axial accuracy of metal bending. The finite element simulation of springback enables effective control and precise compensation to improve the forming quality. Affected by the material, size, and forming process, the generation pattern of the springback defect remains further exploration. Graph-based deep learning techniques support differentiable high-dimensional physics simulations with significantly lower computational resources and comparable accuracy. In this paper, a framework based on Graph Neural Networks (GNN) informed by geometry and process is presented for simulating axial springback of mesh-based metal bending, with a specific focus on the tube bending. The framework adopts an encode-process-decode structure, equipped with parallel graph network blocks and data augmentation strategy, to capture the axial springback information with high fidelity in a form of mesh. Comparative experiments reveal that our framework achieves an accuracy comparable to that of finite elements method, yielding an average nodal error below 1 mm and outperforming three representative GNN baselines. The framework remarkably enhances the simulation efficiency, exhibiting a four-order-of-magnitude improvement on CPU and a six-order-of-magnitude improvement on GPU compared to finite elements method. Furthermore, we successfully apply the proposed framework to simulate the springback of plate V-bending, showcasing its robust generalization ability. These results illustrate the capability of our GNN framework to achieve the accurate and real-time springback simulation, with significant implications for digital twin development and bent tube quality optimization. © 2023, The Authors. All rights reserved.

关键词： Bending (forming)

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Mechanical Properties and Energy Absorption Characteristics of a Novel Skeletal-United Tubular Metamaterial with Negative Poisson's Ratio

SSRN

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SSRN 2024年

This study proposed a new skeletal-united tubular metamaterial (SUTM), derived from the splitting and reconstitution of a middle in-line skeleton inside the unit of traditional re-entrant tubular metamaterial (RETM). The mechanical properties and energy absorption characteristics of the proposed structures were investigated using quasi-static compression tests and finite element analysis. The experimental results and numerical results were in good agreement. The comparison results indicated that the SUTM outperformed the RETM in terms of energy absorption capacity and auxetic property. Subsequently, the influences of tubular geometric parameters on the energy absorption and negative Poisson’s ratio were investigated, including tube thickness, diameter, and height. Furthermore, a study on the energy absorption capacity of tubular materials with different skeleton structures was carried out. The numerical results demonstrated that the skeleton not generated from the corner of the re-entrant structure is less helpful for energy absorption. © 2024, The Authors. All rights reserved.

关键词： Metamaterials

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Self-morphing of elastic bilayers induced by mismatch strain: Deformation simulation and bio-inspired design

arXiv

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arXiv 2023年

作者： Song, Junjie Feng, Yixiong Hong, Zhaoxi Hu, Bingtao Tan, Jianrong Song, Xiuju State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province Zhejiang University Hangzhou310027 China

The process of self-morphing in curved surfaces found in nature, such as with the growth of flowers and leaves, has generated interest in the study of self-morphing bilayers, which has been used in many soft robots or switchers. However, previous research has primarily focused on materials or bilayer fabrication technologies. The self-morphing mechanism and process have been rarely investigated, despite their importance. This study proposed a new deformation simulation method for self-morphing bilayers based on a checkerboard-based discrete differential geometry approach. This new method achieved higher efficiency than traditional finite element methods while still maintaining accuracy. It was also effective in handling complex finite strain situations. Finally, the simulation model was used to design three self-morphing bilayers inspired by folding flowers, spiral grass, and conical seashells. These designs further prove the effectiveness of the proposed method. The results of this study propose a good method for predicting deformation and designing self-morphing bilayers and provide a useful viewpoint for using geometrical methods to solve mechanical problems. Copyright © 2023, The Authors. All rights reserved.

关键词： Geometry

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Physical Logic Enhanced Network for Small-Sample Bi-Layer Metallic Tubes Bending Springback Prediction

arXiv

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arXiv 2022年

作者： Sun, Chang Wang, Zili Zhang, Shuyou Wang, Le Tan, Jianrong State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province Zhejiang University Hangzhou310027 China

Bi-layer metallic tube (BMT) plays an extremely crucial role in engineering applications, with rotary draw bending (RDB) the high-precision bending processing can be achieved, however, the product will further springback. Due to the complex structure of BMT and the high cost of dataset acquisition, the existing methods based on mechanism research and machine learning cannot meet the engineering requirements of springback prediction. Based on the preliminary mechanism analysis, a physical logic enhanced network (PE-NET) is proposed. The architecture includes ES-NET which equivalent the BMT to the single-layer tube, and SP-NET for the final prediction of springback with sufficient single-layer tube samples. Specifically, in the first stage, with the theory-driven pre-exploration and the data-driven pretraining, the ES-NET and SP-NET are constructed, respectively. In the second stage, under the physical logic, the PE-NET is assembled by ES-NET and SP-NET and then fine-tuned with the small sample BMT dataset and composite loss function. The validity and stability of the proposed method are verified by the FE simulation dataset, the small-sample dataset BMT springback angle prediction is achieved, and the method potential in interpretability and engineering applications are demonstrated. Copyright © 2022, The Authors. All rights reserved.

关键词： Bending (forming)

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