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Model construction of soybean average diameter and hole parameters of seed-metering wheel based on DEM

International Journal of Agricultural and Biological engineering 2022年第1期15卷 101-110页

作者： Guoqiang Dun Ning Mao Zhiyong Gao Xingpeng Wu Wenhui Liu Cheng Zhou College of Mechanical and electrical engineering Northeast Forestry UniversityHarbin 150040China school of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUCASHangzhou 310012China school of Information engineering Huzhou UniversityHuzhou 313000ZhejiangChina

To satisfy the demands of soybean precision sowing,this article starts with statistics of the physical parameters of soybean seeds in Heilongjiang province,*** filling process of soybean seeds was analyzed,and the ratio relationship between the diameter,depth,chamfer length of seed-metering wheel’s holes and the mean diameter of soybean seeds was *** was used to simulate seeding circumstances of hole seed-metering wheel with different holes’*** hole diameter ratio,hole depth ratio,and chamfer length ratio were the test factors,while the percentage of single multiple and the empty seeds were test *** triple quadratic regression orthogonal rotation combination test was designed,and the mathematical model between test indexes and test factors was *** showed that the influence of hole diameter ratio and hole depth ratio was significant(p0.05).The chamfer length ratio was 0.15,the hole diameter ratio was 1.63-1.73,the hole depth ratio was 0.81-1.20,the quality of seeding index was more than 90,and multiple and missing indexes were less than 6%and 4%,*** soybean hole wheel seeding device was produced under the optimal parameter combination,to perform a comparative verification test with non-optimized *** test showed anastomotic simulation results,verified the validity of the *** seeding device after optimization expressed the best operating performance,which might satisfy the demands of soybean precision *** study results can provide a theoretical reference for the optimization design of soybean seeding devices.

关键词： agricultural machinery soybean seed-metering device hole seed-metering wheel EDEM simulation optimization

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Advances in 3D printing of magnetic materials:Fabrication,properties,and their applications

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Journal of Advanced Ceramics 2022年第5期11卷 665-701页

作者： Xiangxia WEI Ming-Liang JIN Haiqiang YANG Xiao-Xiong WANG Yun-Ze LONG Zhangwei CHEN Institute for Future School of AutomationShandong Key Laboratory of Industrial Control TechnologyQingdao UniversityQingdao 266071China Collaborative Innovation Center for Nanomaterials&Devices College of PhysicsQingdao UniversityQingdao 266071China Additive Manufacturing Institute College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China

Magnetic materials are of increasing importance for many essential applications due to their unique magnetic ***,due to the limited fabrication ability,magnetic materials are restricted by simple geometric ***-dimensional(3D)printing is a highly versatile technique that can be utilized for constructing magnetic *** shape flexibility of magnets unleashes opportunities for magnetic composites with reducing post-manufacturing costs,motivating the review on 3D printing of magnetic *** paper focuses on recent achievements of magnetic materials using 3D printing technologies,followed by the characterization of their magnetic properties,which are further enhanced by ***,the corresponding properties depend on the intrinsic nature of starting materials,3D printing processing parameters,and the optimized structural *** emphasis is placed on the functional applications of 3D-printed magnetic materials in different ***,the current challenges and future opportunities are also addressed.

关键词： three-dimensional(3D)printing hard magnets soft magnets magnetic properties applications

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An Efficient CNN-Based Hybrid Classification and Segmentation Approach for COVID-19 Detection

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Computers, Materials & Continua 2022年第3期70卷 4393-4410页

作者： Abeer D.Algarni Walid El-Shafai Ghada M.El Banby Fathi E.Abd El-Samie Naglaa F.Soliman Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 84428Saudi Arabia Department of Electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Industrial Electronics and control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Electronics and Communications engineering Faculty of EngineeringZagazig UniversityZagazigSharqia 44519Egypt

COVID-19 remains to proliferate precipitously in the *** has significantly influenced public health,the world economy,and the persons’***,there is a need to speed up the diagnosis and precautions to deal with COVID-19 *** this explosion of this pandemic,there is a need for automated diagnosis tools to help specialists based onmedical *** paper presents a hybrid Convolutional Neural Network(CNN)-based classification and segmentation approach for COVID-19 detection from Computed Tomography(CT)*** proposed approach is employed to classify and segment the COVID-19,pneumonia,and normal CT *** classification stage is firstly applied to detect and classify the input medical CT ***,the segmentation stage is performed to distinguish between pneumonia and COVID-19 CT *** classification stage is implemented based on a simple and efficient CNN deep learning *** model comprises four Rectified Linear Units(ReLUs),four batch normalization layers,and four convolutional(Conv)*** layer depends on filters with sizes of 64,32,16,and 8.A2×2windowand a stride of 2 are employed in the utilized four max-pooling layers.A soft-max activation function and a Fully-Connected(FC)layer are utilized in the classification stage to perform the detection *** the segmentation process,the Simplified Pulse Coupled Neural Network(SPCNN)is utilized in the proposed hybrid *** proposed segmentation approach is based on salient object detection to localize the COVID-19 or pneumonia region,*** summarize the contributions of the paper,we can say that the classification process with a CNN model can be the first stage a highly-effective automated diagnosis *** the images are accepted by the system,it is possible to perform further processing through a segmentation process to isolate the regions of interest in the *** region of interest can be assesses both automatically and through ***

关键词： COVID-19 segmentation classification CNN SPCNN CT images

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Morphologies and Properties of Micro-Arc Oxidation on Plate and Cylinder 2024 Al Alloy

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Journal of Rare Earths 2004年第Z2期22卷 50-52页

作者： Zhu Xiaowen Han Jianmin Cui Shihai Li Ronghua Li Weijing Wang Jinhua school of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China

Samples with two different shapes of 2024 aluminum alloy were treated with micro-arc oxidation (MAO), and the formation process and mechanism of oxidation film was analyzed. The results show that different geometrical... 详细信息

关键词： micro-arc oxidation ceramic film aluminum alloy rare earths

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Amplitude-frequency-aware deep fusion network for optimal contact selection on STN-DBS electrodes

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Science China(Information Sciences) 2022年第4期65卷 48-63页

作者： Linxia XIAO Caizi LI Yanjiang WANG Weixin SI Hai LIN Doudou ZHANG Xiaodong CAI Pheng-Ann HENG College of control Science and engineering China University of Petroleum (East China) Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Department of Neurosurgery Shenzhen Second People's Hospital school of Medicine Shenzhen University Department of Computer Science and engineering The Chinese University of Hong Kong

Parkinson’s disease(PD) is treated effectively by deep brain stimulation(DBS) of the subthalamic nucleus(STN), using an electrode inserted into the head of a PD patient. The electrode has multiple electrical contacts along its length, so the best may be chosen for selectively stimulating the STN. Neurosurgeons usually determine the optimal stimulated contact via the clinical experience of the neurosurgeon and the motor improvement of PD patients. This is a time-consuming and labor-intensive trial-and-error process. The selection of optimal stimulated contact highly depends on the locations of sweet spots, which are manually identified by the characteristic features of microelectrode recordings(MERs). This paper presents an amplitude-frequency-aware deep fusion network for optimal contact selection on STN-DBS *** method first obtains the amplitude-frequency fusion features by combining the MERs time sequence features and the amplitude sequence features, and then uses the convolutional neural network(CNN) with convolutional block attention module(CBAM) to identify both the border of the STN and the sweet spots to implant the electrode. The optimal stimulated contact can be selected according to the distribution of the sweet spots. Experimental results indicate that, for successful surgeries, neurosurgeons and the proposed AI solution selected the same optimal contacts. Furthermore, the proposed method outperforms the state-of-the-art methods for STN and sweet spot identification. The proposed method shows great potential for optimal contact selection to improve the efficiency of STN-DBS surgery and reduce the dependence on clinicians’ experience.

关键词： Microelectrode recordings optimal contact selection sweet spots microelectrode recordings Optimal contact selection amplitude-frequency feature Amplitude-frequency feature Deep fusion network deep fusion network

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A spintronic memristive circuit on the optimized RBF-MLP neural network

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Chinese Physics B 2022年第11期31卷 272-283页

作者：葛源李杰蒋文武王丽丹段书凯 school of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint engineering Laboratory of Intelligent Transmission and control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set ***,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as *** view of this,a novel radial basis neural network(RBF-MLP)is proposed in this *** connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating ***,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number *** addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin *** is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified National Institute of Standards and Technology(MNIST)dataset classification *** experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

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Evolution and maintenance of cooperation via inheritance of neighborhood relationship

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Chinese Science Bulletin 2013年第28期58卷 3491-3498页

作者： TAN ShaoLin Lü JinHu YU XingHuo HILL David John The Key Laboratory of System and control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences school of electrical and Computer engineering RMIT University Department of electrical and Electronic engineering The University of Hong Kong school of electrical and Information engineering University of Sydney

Cooperative behaviors are ubiquitous in nature and human *** is very important to understand the internal mechanism of emergence and maintenance of *** we know now,the offsprings inherit not only the phenotype but also the neighborhood relationship of their *** recent research results show that the interactions among individuals facilitate survival of cooperation through network reciprocity of clustering *** paper aims at introducing an inheritance mechanism of neighborhood relationship to explore the evolution of *** detail,a mathematical model is proposed to characterize the evolutionary process with the above inheritance *** analysis and numerical simulations indicate that high-level cooperation can emerge and be maintained for a wide variety of cost-to-benefit ratios,even if mutation happens during the evolving process.

关键词：合作机制邻里关系维护演变进化过程人类社会遗传机制数学模型

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Modeling method of sequence admittance for three-phase voltage source converter under unbalanced grid condition

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Journal of Modern Power Systems and Clean Energy 2018年第3期6卷 595-606页

作者： Yang CEN Meng HUANG Xiaoming ZHA school of electrical engineering Wuhan University

The admittance is a strong tool for stability analysis and assessment of the three-phase voltage source converters(VSCs) especially in grid-connected ***, the sequence admittance is hard to calculate when the VSC is operating under unbalanced grid voltage conditions. In this paper, a simple and direct modeling method is proposed for a three-phase VSC taking the unbalanced grid voltage as a new variable for the *** coupling in the three-phase system can be calculated by applying the harmonic linearization method. The calculated admittance of three-phase VSCs is verified by detailed circuit simulations.

关键词： Unbalanced grid voltage Three-phase voltage source converter Harmonic linearization Positive and negative sequence admittance Stability

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Position Errors and Interference Prediction-Based Trajectory Tracking for Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1810-1821页

作者： Dongfang Li Yilong Zhang Ping Li Rob Law Zhengrong Xiang Xin Xu Limin Zhu Edmond Q.Wu IEEE school of electrical engineering and Automation Fuzhou UniversityFuzhou 350108 the Sino-US Global Logistics Institute Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory for Agricultural Machinery Intelligent control and Manufacturing of Fujian Education Institutions Fuzhou 350108China school of Biological Science and Medical engineering and the Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education Beihang UniversityBeijing 100191China University of Macao Macao 999078China school of Automation Nanjing University of Science and TechnologyNanjing 210094China College of Intelligence Science and Technology National University of Defence TechnologyChangsha 410073China school of Mechanical engineering Shanghai Jiao Tong UniversityShanghai 200240China Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China

This work presents a trajectory tracking control method for snake *** method eliminates the influence of time-varying interferences on the body and reduces the offset error of a robot with a predetermined *** optimized line-of-sight(LOS)guidance strategy drives the robot’s steering angle to maintain its anti-sideslip ability by predicting position errors and ***,the predictions of system parameters and viscous friction coefficients can compensate for the joint torque control *** compensation is adopted to enhance the compatibility of a robot within ever-changing *** and experimental outcomes show that our work can decrease the fluctuation peak of the tracking errors,reduce adjustment time,and improve accuracy.

关键词： Anti-sideslip compensation snake robot trajectory tracking

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A predictive controller for induction motors using an unknown input observer for online rotor resistance estimation and an update technique for load torque

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控制理论与应用（英文版） 2013年第3期11卷 367-375页

作者： Hanen CHEHIMI Salim HADJ SAD Faouzi MSAHLI Department of electrical engineering National Engineering School of Monastir

This paper deals with the design of an output feedback predictive controller for induction motors. The fundamental interest of the proposed controller is the capability of decoupling the mechanical speed and the rotor fluxes, without degradation against the variation of rotor resistance and load torque. Hence, the contribution is to apply two estimation procedures in order to achieve this goal. Namely, an unknown input observer （UIO） is used for the constant time estimation whereas a heuristic solution is exploited for the load torque update. Moreover, rotor flux components are recovered as an unavailable state of the system. Effectiveness of the proposed observers and the performance of the controller are confirmed by simulation results.

关键词： Predictive controlle UIO Induction motors Parameters estimation

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