|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | On-line chatter detection using servo motor current signal in turning显示文摘Chatter often poses limiting factors on the achievable productivity and is very harmful to machining processes. In order to avoid effectively the harm of cutting chatter,a method of cutting state monitoring based on feed motor current signal is proposed for chatter identification before it has been fully developed. A new data analysis technique,the empirical mode decomposition(EMD),is used to decompose motor current signal into many intrinsic mode functions(IMF) . Some IMF's energy and kurtosis regularly change during the development of the chatter. These IMFs can reflect subtle mutations in current signal. Therefore,the energy index and kurtosis index are used for chatter detection based on those IMFs. Acceleration signal of tool as reference is used to compare with the results from current signal. A support vector machine(SVM) is designed for pattern classification based on the feature vector constituted by energy index and kurtosis index. The intelligent chatter detection system composed of the feature extraction and the SVM has an accuracy rate of above 95% for the identification of cutting state after being trained by experimental data. The results show that it is feasible to monitor and predict the emergence of chatter behavior in machining by using motor current signal. | LIU HongQil CHEN QmgHa LI Bin MAO XinYong MAO KuanMin PENG FangYu | 2011 | Science China(Technological Sciences)2011，54，12： | 15 |
| 2 | Bimetallic Pd-Ni core-shell nanoparticles catalysts for the Suzuki reaction显示文摘 | Ji Xiang Peng Li Hanbao Chong Li Feng Fangyu Fu Zhuang Wang Shilin Zhang Manzhou Zhu | 2014 | Nano Research2014，7，9： | 11 |
| 3 | High precision and efficiency robotic milling of complex parts:Challenges,approaches and trends显示文摘Due to the advantages of large workspace,low cost and the integrated vision/force sensing,robotic milling has become an important way for machining of complex parts.In recent years,many scholars have studied the problems existing in the applications of robotic milling,and lots of results have been made in the dynamics,pose planning,deformation control etc.,which provides theoretical guidance for high precision and high efficiency of robotic milling.From the perspective of complex parts robotic milling,this paper focuses on machining process planning and control techniques including the analysis of the robot-workspace,robot trajectory planning,vibration monitoring and control,deformation monitoring and compensation.As well as the principles of these technologies such as robot stiffness characteristics,dynamic characteristics,chatter mechanisms,and deformation mechanisms.The methods and characteristics related to the theory and technology of robotic milling of complex parts are summarized systematically.The latest research progress and achievements in the relevant fields are reviewed.It is hoped that the challenges,strategies and development related to robotic milling could be clarified through the carding work in this paper,so as to promote the application of related theories and technologies in high efficiency and precision intelligent milling with robot for complex parts. | Zerun ZHU Xiaowei TANG Chen CHEN Fangyu PENG Rong YAN Lin ZHOU Zepeng LI Jiawei WU | 2022 | Chinese Journal of Aeronautics2022，35，2： | 9 |
| 4 | Molecular imaging and therapy targeting coppermetabolism in hepatocellular carcinoma显示文摘Hepatocellular carcinoma(HCC)is the fifth most common cancer worldwide.Significant efforts have been devoted to identify new biomarkers for molecular imaging and targeted therapy of HCC.Copper is a nutritional metal required for the function of numerous enzymatic molecules in the metabolic pathways of human cells.Emerging evidence suggests that copper plays a role in cell proliferation and angiogenesis.Increased accumulation of copper ions was detected in tissue samples of HCC and many other cancers in humans.Altered copper metabolism is a new biomarker for molecular cancer imaging with position emission tomography(PET)using radioactive copper as a tracer.It has been reported that extrahepatic mouse hepatoma or HCC xenografts can be localized with PET using copper-64 chloride as a tracer,suggesting that copper metabolism is a new biomarker for the detection of HCC metastasis in areas of low physiological copper uptake.In addition to copper modulation therapy with copper chelators,short-interference RNA specific for human copper transporter 1(h Ctr1)may be used to suppress growth of HCC by blocking increased copper uptake mediated by h Ctr1.Furthermore,altered copper metabolism is a promising target for radionuclide therapy of HCC using therapeutic copper radionuclides.Copper metabolism has potential as a new theranostic biomarker for molecular imaging as well as targeted therapy of HCC. | Jason Wachsmann Fangyu Peng | 2016 | World Journal of Gastroenterology2016，22，1： | 6 |
| 5 | Comparison of nonhuman primates identified the suitable model for COVID-19显示文摘Identification of a suitable nonhuman primate(NHP)model of COVID-19 remains challenging.Here,we characterized severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection in three NHP species:Old World monkeys Macaca mulatta(M.mulatta)and Macaca fascicularis(M.fascicularis)and New World monkey Callithrix jacchus(C.jacchus).Infected M.mulatta and M.fascicularis showed abnormal chest radiographs,an increased body temperature and a decreased body weight.Viral genomes were detected in swab and blood samples from all animals.Viral load was detected in the pulmonary tissues of M.mulatta and M.fascicularis but not C.jacchus.Furthermore,among the three animal species,M.mulatta showed the strongest response to SARS-CoV-2,including increased inflammatory cytokine expression and pathological changes in the pulmonary tissues.Collectively,these data revealed the different susceptibilities of Old World and New World monkeys to SARS-CoV-2 and identified M.mulatta as the most suitable for modeling COVID-19. | Shuaiyao Lu Yuan Zhao Wenhai Yu Yun Yang Jiahong Gao Junbin Wang Dexuan Kuang Mengli Yang Jing Yang Chunxia Ma Jingwen Xu Xingli Qian Haiyan Li Siwen Zhao Jingmei Li Haixuan Wang Haiting Long Jingxian Zhou Fangyu Luo Kaiyun Ding Daoju Wu Yong Zhang Yinliang Dong Yuqin Liu Yinqiu Zheng Xiaochen Lin Li Jiao Huanying Zheng Qing Dai Qiangming Sun Yunzhang Hu Changwen Ke Hongqi Liu Xiaozhong Peng | 2020 | Signal Transduction and Targeted Therapy2020，5，1： | 5 |
| 6 | Wilson病的食物治疗显示文摘Wilson病属于神经遗传性铜代谢为主的疾病,属少数可以治疗的遗传病,及时治疗大多预后良好。对Wilson病非药物治疗,即主要是肝豆状核变性基高锌低铜与富含巯基以及抗氧化成分比如Vit E的饮食以及中药替代治疗,作一介绍。 | 姚蕾 吴斌 王晓平 Fangyu Peng | 2012 | 微量元素与健康研究2012，29，6： | 4 |
| 7 | Novel hollow Ni0.33Co0.67Se nanoprisms for high capacity lithium storage显示文摘In this work,homogeneous Ni0.33Co0.67Se hollow nanoprisms were synthesized successfully in virtue of Kirkendall effect.It is the first time for bimetallic Ni-Co compounds Ni0.33Co0.67Se to be used in lithium-ion batteries (LIBs).Impressively,the Ni0.33Co0.67Se hollow nanoprisms show superior specific capacity (1,575 mAh/g at the current density of 100 mA/g) and outstanding rate performance (850 mAh/g at 2,000 mA/g) as anode material for LIBs.This work proves the potential of bimetallic chalcogenide compounds as high performance anode materials for LIBs. | Shaohua Zhu Cheng Chen Pan He Shuangshuang Tan Fangyu Xiong Ziang Liu Zhuo Peng Qinyou An Liqiang Mai | 2019 | Nano Research2019，12，6： | 3 |
| 8 | Intelligent learning model-based skill learning and strategy optimization in robot grinding and polishing显示文摘With the rapid advancement of manufacturing in China,robot machining technology has become a popular research subject.An increasing number of robots are currently being used to perform complex tasks during manual operation,e.g.,the grinding of large components using multi-robot systems and robot teleoperation in dangerous environments,and machining conditions have evolved from a single open mode to a multisystem closed mode.Because the environment is constantly changing with multiple systems interacting with each other,traditional methods,such as mechanism modeling and programming are no longer applicable.Intelligent learning models,such as deep learning,transfer learning,reinforcement learning,and imitation learning,have been widely used;thus,skill learning and strategy optimization have become the focus of research on robot machining.Skill learning in robot machining can use robotic flexibility to learn skills under unknown working conditions,and machining strategy research can optimize processing quality under complex working conditions.Additionally,skill learning and strategy optimization combined with an intelligent learning model demonstrate excellent performance for data characteristics learning,multisystem transformation,and environment perception,thus compensating for the shortcomings of the traditional research field.This paper summarizes the state-of-the-art in skill learning and strategy optimization research from the perspectives of feature processing,skill learning,strategy,and model optimization of robot grinding and polishing,in which deep learning,transfer learning,reinforcement learning,and imitation learning models are integrated into skill learning and strategy optimization during robot grinding and polishing.Finally,this paper describes future development trends in skill learning and strategy optimization based on an intelligent learning model in the system knowledge transfer and nonstructural environment autonomous processing. | CHEN Chen WANG Yu GAO ZhiTao PENG FangYu TANG XiaoWei YAN Rong ZHANG YuKui | 2022 | Science China(Technological Sciences)2022，65，9： | 3 |
| 9 | Large-scale identification of potential phase-separation proteins from plants using a cell-free system显示文摘Dear Editor,Biomolecular condensates have emerged as key players in cellular processes and responses to stress(Alberti and Hyman,2021).Recent studies have revealed that most biomolecular condensates arise from liquid-liquid phase separation(Banani et al.,2017;Shin and Brangwynne,2017),a process that has been described in the field of polymer chemistry. | Honghong Zhang Fangyu Peng Chun He Yan Liu Haiteng Deng Xiaofeng Fang | 2023 | Molecular Plant2023，16，2： | 2 |
| 10 | Anisotropic Force Ellipsoid Based Multi-axis Motion Optimization of Machine Tools显示文摘The existing research of the motion optimization of multi-axis machine tools is mainly based on geometric and kinematic constraints, which aim at obtaining minimum-time trajectories and finding obstacle-free paths. In motion optimization, the stiffness characteristics of the whole machining system, including machine tool and cutter, are not considered. The paper presents a new method to establish a general stiffness model of multi-axis machining system. An analytical stiffness model is established by Jacobi and point transformation matrix method. Based on the stiffness model, feed-direction stiffness index is calculated by the intersection of force ellipsoid and the cutting feed direction at the cutter tip. The stiffness index can help analyze the stiffness performance of the whole machining system in the available workspace. Based on the analysis of the stiffness performance, multi-axis motion optimization along tool paths is accomplished by mixed programming using Matlab and Visual C++. The effectiveness of the motion optimization method is verified by the experimental research about the machining performance of a 7-axis 5-linkage machine tool. The proposed research showed that machining stability and production efficiency can be improved by multi-axis motion optimization based on the anisotropic force ellipsoid of the whole machining system. | PENG Fangyu YAN Rong CHEN Wei YANG Jianzhong LI Bin | 2012 | Chinese Journal of Mechanical Engineering2012，25，5： | 2 |
| 11 | A method of general stiffness modeling for multi-axis machine tool显示文摘 | YAN Rong PENG Fangyu LI Bin | 2008 | Intelligent Robotics and Applications2008，5315，： | 1 |
| 12 | Influence mechanism of machining angles on force induced error and their selection in five axis bullnose end milling显示文摘In the machining of complicated surfaces,the cutters with large length/diameter ratios are used widely and the deformation of the machining system is one of the principal error sources.During the process planning stage,the cutting direction angle,the cutter lead and tilt angles are usually optimized to minimize the force induced error.It may lead to a low machining efficiency for bullnose end mills,as the material removal rates are different largely for different machining angles.In this paper,the influence mechanism of the machining angles on the force induced error is studied based on the models of the instantaneous cutting force when the cutter flute traveling through the cutting contact point and the stiffness of the machining system.In order to evaluate the machining angles,the force induced error/efficiency indicator(FEI)is defined as the division of the force induced error and the equal volume sphere of the removed material.FEI is dimensionless,with the lower FEI,the lower force induced error and the higher machining efficiency.For optimal selection of the machining angles,the critical FEI is calculated with the constraint of force induced error and the desired material removal rate,and the critical FEI separate the set of the machining angles into two subsets.After the feed rate scheduling process,the machining angles in the optimal subset would have higher machining accuracy and efficiency,while the machining angles in the other subset have lower machining accuracy and efficiency.Through the machining experiment of five axis machining and freeform surface machining,the effectiveness and superiority of the proposed FEI method is verified with a bullnose end mill,which can improve the machining efficiency with the constraint of force induced error. | Zerun ZHU Fangyu PENG Rong YAN Zepeng LI Jiawei WU Xiaowei TANG Chen CHEN | 2020 | Chinese Journal of Aeronautics2020，33，12： | 1 |
| 13 | Variable eccentric distance-based tool path generation for orthogonal turn-milling显示文摘这研究为基于可变怪癖的距离在直角的拐弯工厂最大化长带宽度建议一个算法。用机器制造的错误模型首先在接触线基于本地切侧面被建立。长带宽度的影响因素然后被调查分析他们的特征并且决定优化策略。为用机器制造长带宽度的最大值的优化模型被采用可变怪癖的距离提出。Hausdorff 距离和 | Fangyu PENG Wei WANG Rong YAN Xianyin DUAN Bin LI | 2015 | Frontiers of Mechanical Engineering2015，10，4： | 1 |
| 14 | A new method of virtual material hypothesis-based dynamic modeling on fixed joint interface in machine tools显示文摘 | Hongliang Tian Bin Li Hongqi Liu Kuanmin Mao Fangyu Peng Xiaolei Huang | 2010 | International Journal of Machine Tools and Manufacture2010，，3： | 1 |
| 15 | Monodispersed Au Pd nanoalloy: composition control synthesis and catalytic properties in the oxidative dehydrogenative coupling of aniline显示文摘A series of Au Pd@C nanoalloy catalysts with tunable compositions were successfully prepared by a co-reduction method. The use of borane-tert-butylamine complex as reductant and oleylamine as both solvent and reductant was very effective for the preparation of the monodispersed nanoalloy. We evaluated the catalytic activity of these Au Pd@C nanoalloys for oxidative dehydrogenative coupling of aniline, which showed better catalytic activity than equal amounts of sole Au@C or Pd@C catalyst. The Au1Pd3@C catalyst exhibited the best performance, indicating that the conversion and selectivity were improved along with the increase of Pd composition. However, if the Pd composition was too high in the Au Pd alloy, Au1Pd7@C achieved only 81% conversion in this reaction. | Fangyu Fu Sen He Sha Yang Chen Wang Xun Zhang Peng Li Hongting Sheng Manzhou Zhu | 2015 | Science China Chemistry2015，58，10： | 0 |
| 16 | Ultrasmall Pd nanoclusters: facile synthesis and versatile catalytic application显示文摘A simple and efficient method for the synthesis of ultrasmall Pd nanoclusters(NCs) has been developed. The as-obtained Pd NCs displayed uniform size with an average diameter of 1.8±0.2 nm. The ultrasmall Pd NCs and carbon nanotubes(CNTs)-supported Pd NCs also showed outstanding catalytic activity for nitrobenzene reduction and Suzuki coupling reactions. Notably, the reactions were conducted under mild conditions with high yield and selectivity. | Ji Xiang Hanbao Chong Jia Tang Li Feng Bin Zhou Fangyu Fu Xin Wang Peng Li Manzhou Zhu | 2015 | Science China Chemistry2015，58，3： | 0 |
| 17 | The olfactory route is a potential way for SARS-CoV-2 to invade the central nervous system of rhesus monkeys显示文摘Neurological manifestations are frequently reported in the COVID-19 patients.Neuromechanism of SARS-CoV-2 remains to be elucidated.In this study,we explored the mechanisms of SARS-CoV-2 neurotropism via our established non-human primate model of COVID-19.In rhesus monkey,SARS-CoV-2 invades the CNS primarily via the olfactory bulb.Thereafter,viruses rapidly spread to functional areas of the central nervous system,such as hippocampus,thalamus,and medulla oblongata.The infection of SARS-CoV-2 induces the inflammation possibly by targeting neurons,microglia,and astrocytes in the CNS.Consistently,SARS-CoV-2 infects neuro-derived SK-N-SH,glial-derived U251,and brain microvascular endothelial cells in vitro.To our knowledge,this is the first experimental evidence of SARS-CoV-2 neuroinvasion in the NHP model,which provides important insights into the CNS-related pathogenesis of SARS-CoV-2. | Li Jiao Yun Yang Wenhai Yu Yuan Zhao Haiting Long Jiahong Gao Kaiyun Ding Chunxia Ma Jingmei Li Siwen Zhao Haixuan Wang Haiyan Li Mengli Yang Jingwen Xu Junbin Wang Jing Yang Dexuan Kuang Fangyu Luo Xingli Qian Longjiang Xu Bin Yin Wei Liu Hongqi Liu Shuaiyao Lu Xiaozhong Peng | 2021 | Signal Transduction and Targeted Therapy2021，6，5： | 0 |
| 18 | Differential Transcriptomic Landscapes of SARS-CoV-2 Variants in Multiple Organs from Infected Rhesus Macaques显示文摘Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)caused the persistent coronavirus disease 2019(COVID-19)pandemic,which has resulted in millions of deaths worldwide and brought an enormous public health and global economic burden.The recurring global wave of infections has been exacerbated by growing variants of SARS-CoV-2.In this study,the virological characteristics of the original SARS-CoV-2 strain and its variants of concern(VOCs;including Alpha,Beta,and Delta)in vitro,as well as differential transcriptomic landscapes in multiple organs(lung,right ventricle,blood,cerebral cortex,and cerebellum)from the infected rhesus macaques,were elucidated.The original strain of SARS-CoV-2 caused a stronger innate immune response in host cells,and its VOCs markedly increased the levels of subgenomic RNAs,such as N,Orf9b,Orf6,and Orf7ab,which are known as the innate immune antagonists and the inhibitors of antiviral factors.Intriguingly,the original SARS-CoV-2 strain and Alpha variant induced larger alteration of RNA abundance in tissues of rhesus monkeys than Beta and Delta variants did.Moreover,a hyperinflammatory state and active immune response were shown in the right ventricles of rhesus monkeys by the up-regulation of inflammation-and immune-related RNAs.Furthermore,peripheral blood may mediate signaling transmission among tissues to coordinate the molecular changes in the infected individuals.Collectively,these data provide insights into the pathogenesis of COVID-19 at the early stage of infection by the original SARS-CoV-2 strain and its VOCs. | Tingfu Du Chunchun Gao Shuaiyao Lu Qianlan Liu Yun Yang Wenhai Yu Wenjie Li Yong Qiao Sun Cong Tang Junbin Wang Jiahong Gao Yong Zhang Fangyu Luo Ying Yang Yun-Gui Yang Xiaozhong Peng | 2023 | Genomics, Proteomics & Bioinformatics2023，21，5： | 0 |
| 19 | Associative learning of a three-terminal memristor network for digits recognition显示文摘Imitating the associative intelligence of the biological brain is attractive but is poorly achieved in hardware because the complex tunable connection in neural networks is difficult to reproduce. We develop a circuit composed of a three-terminal memristor network to reproduce the biological conditioning process artificially. The synaptic weight between co-firing neurons is strengthened simultaneously by generating a feedback signal from the integrate-and-fire neuron to the gate of the synaptic memristor. The network allows the multi-associative capacity of recalling more than one digit in one circuit. Both single and multi-associative learning for recalling digital images are achieved. Furthermore, all 10 digital images from “0” to “9” are successfully recalled in an associative network with such paralleling circuits. Assisted by this associative layer, a typical classification network effectively improves the recognition rate for fragmentary digital images.Our work sheds light on brain-inspired artificial associative memory and provides a strategy for applications,such as object recognition with partial features and similar scenes. | Yiming REN Bobo TIAN Mengge YAN Guangdi FENG Bin GAO Fangyu YUE Hui PENG Xiaodong TANG Qiuxiang ZHU Junhao CHU Chungang DUAN | 2023 | Science China(Information Sciences)2023，66，2： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员