Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,maki...Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within 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 accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance 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.展开更多
The practical condition of needle-punched filters applied in coal-fired power plants is investigated. According to the actual operating conditions, two common filters (glass fiber filter and polyphenylene sulfide (PPS...The practical condition of needle-punched filters applied in coal-fired power plants is investigated. According to the actual operating conditions, two common filters (glass fiber filter and polyphenylene sulfide (PPS) filter) are selected for experiment. The performance of these two kinds of filter is compared based on a series of tests such as resistance to the acid and alkali, oxidation resistance,hydrolysis resistance,and wear resistance. Experimental results show that PPS filter materials have better properties than those of glass filter material except oxidation resistance. Composite filter mixed glass fiber and PPS is recommended for polluters because of its good properties in all aspects.展开更多
Melt-blown polybutylene terephthalate (PBT) nonwoven materials treated by usingplasma is regarded as one of the excellent materials to filter white blood cells (WBC) from blood.In this paper, dielectric barrier discha...Melt-blown polybutylene terephthalate (PBT) nonwoven materials treated by usingplasma is regarded as one of the excellent materials to filter white blood cells (WBC) from blood.In this paper, dielectric barrier discharge (DBD) plasma source at an improved quasi-stable at-mospheric pressure is achieved when discharge voltage, discharge current, and gap between theelectrodes are carefully controlled. This plasma source has been used to modify the surface ofPBT melt-blown nonwoven materials. Experimental results indicate that both the wettablity andpermeation of treated PBT melt-blown nonwoven materials are greatly improved.展开更多
Phase change materials have a key role for wearable thermal management,but suffer from poor water vapor permeability,low enthalpy value and weak shape stability caused by liquid phase leakage and intrinsic rigidity of...Phase change materials have a key role for wearable thermal management,but suffer from poor water vapor permeability,low enthalpy value and weak shape stability caused by liquid phase leakage and intrinsic rigidity of solid–liquid phase change materials.Herein,we report for the first time a versatile strategy for designed assembly of high-enthalpy flexible phase change nonwovens(GB-PCN)by wet-spinning hybrid grapheneboron nitride(GB)fiber and subsequent impregnating paraffins(e.g.,eicosane,octadecane).As a result,our GB-PCN exhibited an unprecedented enthalpy value of 206.0 J g^(−1),excellent thermal reliability and anti-leakage capacity,superb thermal cycling ability of 97.6%after 1000 cycles,and ultrahigh water vapor permeability(close to the cotton),outperforming the reported PCM films and fibers to date.Notably,the wearable thermal management systems based on GB-PCN for both clothing and face mask were demonstrated,which can maintain the human body at a comfortable temperature range for a significantly long time.Therefore,our results demonstrate huge potential of GB-PCN for human-wearable passive thermal management in real scenarios.展开更多
The technical parameters and the structural factors of melt-blown nonwovens used as filteringmedium are analysed,the orientation of particles filtered in a filter is described,and the optimalparameters for air filtrat...The technical parameters and the structural factors of melt-blown nonwovens used as filteringmedium are analysed,the orientation of particles filtered in a filter is described,and the optimalparameters for air filtration are obtained.The results are shown as follows:the ratio of tenacity oflongitudinal to cross direction has a close agreement with the random coefficient of fiber arrange-ment in practice;large particles are most likely trapped on the surface of a filter,and smaller parti-cles are filtered throughout the depth of a filter,and the deeper,the smaller;moreover,higher fil-tering efficiency and lower pressure drop can be effected through the optimization of parameters.展开更多
基金National Key Research and Development Program of China(Nos.2022YFB4700600 and 2022YFB4700605)National Natural Science Foundation of China(Nos.61771123 and 62171116)+1 种基金Fundamental Research Funds for the Central UniversitiesGraduate Student Innovation Fund of Donghua University,China(No.CUSF-DH-D-2022044)。
文摘Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within 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 accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance 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.
文摘The practical condition of needle-punched filters applied in coal-fired power plants is investigated. According to the actual operating conditions, two common filters (glass fiber filter and polyphenylene sulfide (PPS) filter) are selected for experiment. The performance of these two kinds of filter is compared based on a series of tests such as resistance to the acid and alkali, oxidation resistance,hydrolysis resistance,and wear resistance. Experimental results show that PPS filter materials have better properties than those of glass filter material except oxidation resistance. Composite filter mixed glass fiber and PPS is recommended for polluters because of its good properties in all aspects.
基金The project supported by Dong Hua University Shanghai Science and Technological Research Council (No. 0252nm110), "Dawn Project" of Shanghai Municipal Education Commission (No. 02SG28) and Ministry of Education Science and Technological Research Emphasis
文摘Melt-blown polybutylene terephthalate (PBT) nonwoven materials treated by usingplasma is regarded as one of the excellent materials to filter white blood cells (WBC) from blood.In this paper, dielectric barrier discharge (DBD) plasma source at an improved quasi-stable at-mospheric pressure is achieved when discharge voltage, discharge current, and gap between theelectrodes are carefully controlled. This plasma source has been used to modify the surface ofPBT melt-blown nonwoven materials. Experimental results indicate that both the wettablity andpermeation of treated PBT melt-blown nonwoven materials are greatly improved.
基金supported by the National Natural Science Foundation of China(Nos.21903082,22003065,22125903,51872283,22075279,21805273,22273100)Dalian Innovation Support Plan for High Level Talents(2019RT09)+3 种基金Dalian National Laboratory For Clean Energy(DNL),CAS,DNL Cooperation Fund,CAS(DNL201912,DNL201915,DNL202016,DNL202019)DICP(DICP I2020032,DICP I202036,I202218)The Joint Fund of the Yulin University and the Dalian National Laboratory for Clean Energy(YLU-DNL Fund 2021002,YLU-DNL 2021007,YLU-DNL 2021009)Q.Shi would like to thank Dalian Outstanding Young Scientific Talent Program(Grant 2019RJ10).
文摘Phase change materials have a key role for wearable thermal management,but suffer from poor water vapor permeability,low enthalpy value and weak shape stability caused by liquid phase leakage and intrinsic rigidity of solid–liquid phase change materials.Herein,we report for the first time a versatile strategy for designed assembly of high-enthalpy flexible phase change nonwovens(GB-PCN)by wet-spinning hybrid grapheneboron nitride(GB)fiber and subsequent impregnating paraffins(e.g.,eicosane,octadecane).As a result,our GB-PCN exhibited an unprecedented enthalpy value of 206.0 J g^(−1),excellent thermal reliability and anti-leakage capacity,superb thermal cycling ability of 97.6%after 1000 cycles,and ultrahigh water vapor permeability(close to the cotton),outperforming the reported PCM films and fibers to date.Notably,the wearable thermal management systems based on GB-PCN for both clothing and face mask were demonstrated,which can maintain the human body at a comfortable temperature range for a significantly long time.Therefore,our results demonstrate huge potential of GB-PCN for human-wearable passive thermal management in real scenarios.
文摘The technical parameters and the structural factors of melt-blown nonwovens used as filteringmedium are analysed,the orientation of particles filtered in a filter is described,and the optimalparameters for air filtration are obtained.The results are shown as follows:the ratio of tenacity oflongitudinal to cross direction has a close agreement with the random coefficient of fiber arrange-ment in practice;large particles are most likely trapped on the surface of a filter,and smaller parti-cles are filtered throughout the depth of a filter,and the deeper,the smaller;moreover,higher fil-tering efficiency and lower pressure drop can be effected through the optimization of parameters.
