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Improvement of High-Speed Detection Algorithm for Nonwoven Material Defects Based on Machine Vision

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Journal of Donghua University(English Edition) 2024年第4期41卷 416-427页

作者： LI Chengzu WEI Kehan ZHAO Yingbo TIAN Xuehui QIAN Yang ZHANG Lu wang rongwu College of Textiles Donghua UniversityShanghai 201620China

Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished ***,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial *** paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus *** the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection *** this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection *** half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection *** comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.

关键词： defect detection nonwoven materials deep learning object detection algorithm transfer learning halfprecision quantization

Controllable diameter of electrospun nanofibers based on the velocity of whipping jets for high-efficiency air filtration

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Science China(Technological Sciences) 2022年第2期65卷 481-489页

作者： LEI SaiLing wang LiMing wang rongwu QIN XiaoHong YU JianYong Key Laboratory of Textile Science&Technology Ministry of EducationCollege of TextilesDonghua UniversityShanghai 201620China Innovation Center for Textile Science and Technology Donghua UniversityShanghai 201620China

Electrospun nanofibers are regarded as a promising candidate for filtration because of their prominent size *** precise control of nanofiber diameter is the key to the material’s outstanding filtration capability,but it remains a ***,an electrohydrodynamic scaling model is established for the accurate prediction of fiber diameter based on the velocity of the whipping *** this model,the velocity reflects jet stretching and is tuned by adding *** theoretical predictions agree well with the experimental *** the proposed diameter model,the filtration property of the membrane is significantly optimized by governing the fiber *** the nanofiber is slenderized to 183 nm,an ultralight (0.521 g m;) membrane exhibits high filtration efficiency (99.93%) and low pressure drop (105.2 Pa) against ultrafine aerosol particles (≤0.26μm) under an airflow face velocity of 5.33 cm s^(-1).These findings demonstrate that the established surface charge-based diameter model provides an excellent platform to timely and accurately control the nanofiber diameter via the velocity of whipping jets for highefficiency air filtration.

关键词： electrospinning jet velocity fiber diameter filtration

Flexible, self-cleaning, and high-performance ceramic nanofiber-based moist-electric generator enabled by interfacial engineering

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Science China(Technological Sciences) 2022年第2期65卷 450-457页

作者： wang LiMing FENG LanLan SUN Zhao Yang HE XinYang wang rongwu QIN XiaoHong YU JianYong Key Laboratory of Textile Science&Technology Ministry of EducationCollege of TextilesDonghua UniversityShanghai 201620China Innovation Center for Textile Science and Technology Donghua UniversityShanghai 201620China

Due to their long-term stability, even under extreme conditions, oxide ceramics have attracted significant attention in emerging fields like moist-electric generation. However, the inherent brittleness and low voltage output of oxide ceramic-based moistelectric generators(MEGs) limit their applications in wearable electronics. Herein, a facile strategy involving the combination of sol-gel electrospinning and calcination is used to fabricate flexible and freestanding Ti O_(2)/Zr O_(2)(TZ) composite nanofiber-based MEGs. The excellent flexibility of the TZ nanofiber membranes can be attributed to the suppression of their crystal structure transformation, dispersion of stress concentration, and reduction of crack propagation via interfacial engineering. The porous structure of the electrospun nanofiber membrane features an abundance of charged narrow channels for the diffusion of water molecules and generates a streaming potential. The optimal voltage output reached ~0.8 V, which is the highest value reported for an oxide ceramic-based MEG. Furthermore, the as-fabricated nanofiber-based MEG exhibits good self-cleaning capability to degrade organic pollutants under ultraviolet irradiation. By integrating mechanical flexibility, high performance, and a selfcleaning effect, this work presents a new idea for exploring diverse, efficient, and wearable oxide ceramic-based MEGs.

关键词： moist-electric generation ceramic nanofiber electrospinning flexible self-cleaning

Shadow–highlight feature matching automatic small crater recognition using high-resolution digital orthophoto map from Chang’E Missions

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Acta Geochimica 2019年第4期38卷 541-554页

作者： Wei Zuo Chunlai Li Lingjie Yu Zhoubin Zhang rongwu wang Xingguo Zeng Yuxuan Liu Yaying Xiong Key Laboratory of Lunar and Deep Space Exploration National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China School of Astronomy and Space Sciences University of Chinese Academy of SciencesBeijing 100049China School of Textile Science and Engineering Xi'an Polytechnic UniversityXi'an 710048China College of Textiles Donghua UniversityShanghai 200051China

This paper introduces a new method of small lunar craters’ automatic identification, using digital orthophoto map(DOM) data. The core of the approach is the fact that the lunar exploration DOM data reveal contrasting highlight and shadow characteristics of small craters under sunlight irradiation. This research effort combines image processing and mathematical modeling. Overall it proposes a new planetary data processing approach, to segment and extract the highlight and shadow regions of small craters,using the image gray frequency(IGF) statistical *** can also be applied to identify the coupling relationships between small craters’ shape and their relative features. This paper presents the highlight and shadow pair matching(HSPM) model which manages to perform highprecision automatic recognition of small lunar *** was performed using the DOM data of Chang’E-2(CE-2). The results have shown that the proposed method has a high level of successful detection rate. The proposed methodology that uses DOM data can complement the drawbacks of the digital elevation model(DEM) that has a relatively high false detection rate. A hybrid fusion model(FUM) that combines both DOM and DEM data, was carried out to simultaneously identify small, medium, and large-sized craters. It has been proven that the FUM generally shows stronger recognition ability compared to previous approaches and it can be adapted for high precision identification of craters on the whole lunar *** results meet the requirements for a reliable and accurate exploration of the Moon and the planets.

关键词： Moon Crater recognition Image processing Space exploration

Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images

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Journal of Donghua University(English Edition) 2022年第3期39卷 185-192页

作者： DONG Gaige wang rongwu LI Chengzu YOU Xiangyin College of Textiles Donghua University Shanghai 201620 China Jiangsu Liyang New Material Co. Ltd. Nantong 226004 China

The three-dimensional(3D)model is of great significance to analyze the performance of ***,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence *** processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction *** on this information,3D models were built in 3D ***,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and *** method with lower cost could reconstruct 3D models of nonwovens conveniently.

关键词： three-dimensional(3D)model reconstruction deep learning microscopy nonwoven image processing

Hybrid Modular Smart Transformer for Asymmetrically Bidirectional Power Flow Operation

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1384-1398页

作者： Kangan wang Youngjong Ko rongwu Zhu Siyu Wu Weimin Wu Marco Liserre Shanghai Maritime University Shanghai 201306China Pukyong National University Busan 48513South Korea Harbin Institute of Technology(Shenzhen) Shenzhen 518000China Kiel University Kiel 24118Germany

The presence of renewable energy resources in LV distribution networks may lead to a distribution transformer,also known as a Smart Transformer(ST),experiencing the bidirectional power ***,the ST must have the capability to operate in both ***,the reverse power is less as compared to the forward power,thus the design of ST with the same capacity in both directions increases the hardware cost and decreases the system *** paper proposes a Hybrid-modular-ST(H-ST),composed of a mixed use of single active bridge-based series resonant converter and dual active bridge instead of complete use of uni-or bi-directional converter adopted in the conventional *** on the proposed H-ST,the impacts of power imbalance among cascaded modules in reverse operation mode are analyzed and then an effective solution based on reactive power compensation combined with the characteristics of the proposed architecture is *** simulation and experimental results clearly validate the effectiveness and feasibility of the theoretical analyses.

关键词： Cascaded H-bridge dual-active bridge series resonant converter smart transformer(ST) three-stage architecture

湿法水刺可分散材料的结构与性能及其发展趋势

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纺织学报 2018年第6期39卷 167-174页

作者：张寅江王荣武靳向煜东华大学产业用纺织品教育部工程研究中心上海201620

针对现有一次性湿纸巾使用后不可降解,且丢入抽水马桶易堵塞城市管道等难题,从制备工艺、纤维构成、材料属性与用途等角度阐述新型可分散可降解湿法成网水力缠结湿纸巾基材,同时比较分析该材料结构特征及其使用性能(湿强,分散和手感)。... 详细信息

针对现有一次性湿纸巾使用后不可降解,且丢入抽水马桶易堵塞城市管道等难题,从制备工艺、纤维构成、材料属性与用途等角度阐述新型可分散可降解湿法成网水力缠结湿纸巾基材,同时比较分析该材料结构特征及其使用性能(湿强,分散和手感)。结果表明:材料由长短纤维缠绕抱合构成,具有非织造材料与纸二者属性,长纤维(短切再生纤维素纤维)缠绕抱合作为纤维增强影响着材料的湿强和分散性,材料手感与梳理水刺材料接近。最后对该材料发展趋势,从短切纤维优化、辅助增强体应用与设备工艺改进等角度进行系统阐述。

关键词：湿法水刺可分散材料结构与性能非织造湿纸巾

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竹浆/ES抗菌非织造擦拭材料的制备及性能

上海纺织科技 2020年第10期48卷 13-18页

作者：陈露王荣武东华大学纺织学院上海201620

为了制备一种成本低、环保、抗菌、综合使用性能好的擦拭材料,将竹浆纤维与ES纤维以不同配比混合梳理成网,经水刺加固、热风黏合制成不同规格的抗菌非织造擦拭材料。竹浆纤维具有抗菌性和吸水性,ES纤维不仅柔软而且经热黏合还能提高材... 详细信息

为了制备一种成本低、环保、抗菌、综合使用性能好的擦拭材料,将竹浆纤维与ES纤维以不同配比混合梳理成网,经水刺加固、热风黏合制成不同规格的抗菌非织造擦拭材料。竹浆纤维具有抗菌性和吸水性,ES纤维不仅柔软而且经热黏合还能提高材料强度,制得的擦拭材料具有一定的抗菌性,大肠埃希菌抑菌率为38.62%,金黄色葡萄球菌抑菌率为38.59%,同时具备高吸污性和良好的柔软性、耐用性,可满足大多数抗菌擦拭材料的要求。在此基础上,针对抗菌要求高的使用环境,选用对人体无害、环保的有机硅季铵盐作为抗菌剂,对材料进行抗菌后整理,可大幅提高材料抗菌性,大肠埃希菌抑菌率为99.1%,金黄色葡萄球菌抑菌率为99.5%,超过GB/T20944.3-2008标准规定的要求。

关键词：竹浆纤维 ES纤维有机硅季铵盐整理抗菌性非织造织物擦拭材料

基于显微光学切片方法的织物绒毛深度信息获取

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东华大学学报（自然科学版） 2018年第3期44卷 391-396,408页

作者：余灵婕王荣武西安工程大学纺织科学与工程学院陕西西安710048 东华大学纺织学院上海201620

在织物绒毛的自动检测中,深度信息是使毛球与织物表面分离的关键信息。基于"显微光学切片"的思想,通过显微镜采集织物表层的同轴序列多焦面图像,并利用聚焦程度获取织物表层各点的深度信息。将序列图层经去噪平滑处理之后,沿图层深度方... 详细信息

在织物绒毛的自动检测中,深度信息是使毛球与织物表面分离的关键信息。基于"显微光学切片"的思想,通过显微镜采集织物表层的同轴序列多焦面图像,并利用聚焦程度获取织物表层各点的深度信息。将序列图层经去噪平滑处理之后,沿图层深度方向搜索各平面点(x,y)的成像最清晰位置z,投影至灰度空间之后建立织物表面及绒毛的深度图像。提出了新的清晰度评价标准——基于自适应区域选择的梯度方差算法,并将此方法与3种传统清晰度评价标准进行比较。试验结果表明,提出的新方法不仅能正确测量像素点清晰度,而且抗噪能力较强。

关键词：织物起毛起球评价深度信息获取显微光学切片聚焦获得深度清晰度评价