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回火温度对5Cr5MoSiV1钢显微组织和性能的影响

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机械工程材料 2024年第5期48卷 15-19页

作者：郭志凯连明洋曹培泽王超锋原晓伟中铁工程装备集团有限公司郑州450016

对球化退火态5Cr5MoSiV1钢进行1050℃×1 h的淬火以及不同温度(515,530,560,590,620℃)保温1 h的回火处理,研究了回火温度对该钢显微组织、硬度、冲击韧性和耐磨性能的影响。结果表明:不同温度回火后5Cr5MoSiV1钢的组织均为回火索氏体... 详细信息

对球化退火态5Cr5MoSiV1钢进行1050℃×1 h的淬火以及不同温度(515,530,560,590,620℃)保温1 h的回火处理,研究了回火温度对该钢显微组织、硬度、冲击韧性和耐磨性能的影响。结果表明:不同温度回火后5Cr5MoSiV1钢的组织均为回火索氏体和少量碳化物,随着回火温度升高,碳化物增多并发生聚集长大,当回火温度超过560℃时,基体回复和再结晶加剧,马氏体板条状特征逐渐模糊;随着回火温度的升高,5Cr5MoSiV1钢的硬度降低,冲击吸收能量先基本不变后升高,磨损质量损失呈先波动下降后升高的趋势。5Cr5MoSiV1钢合适的回火温度为590℃,此时该钢兼具良好的冲击韧性和耐磨性能,硬度为51.1 HRC,冲击吸收能量为25.7 J,磨损质量损失为3.864 g。

关键词： 5Cr5MoSiV1钢回火温度显微组织冲击韧性耐磨性能

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射频/红外波束复合器边齿设计与分析方法

空天防御 2020年第4期3卷 73-80页

作者：田义王超峰李艳红张励上海机电工程研究所上海201109

为了抑制射频/光学波束复合器的边缘绕射效应对工作区场均匀性的影响,在几何绕射理论、口径场积分理论基础上提出了一种射频/光学波束复合器的边齿设计与分析方法。首先,为了区分直达波和绕射波,将空间域及频域的场分布通过傅里叶逆变换... 详细信息

为了抑制射频/光学波束复合器的边缘绕射效应对工作区场均匀性的影响,在几何绕射理论、口径场积分理论基础上提出了一种射频/光学波束复合器的边齿设计与分析方法。首先,为了区分直达波和绕射波,将空间域及频域的场分布通过傅里叶逆变换,转换为角频域和时域分布;然后,给出了典型的边齿设计案例,通过分析比较场在空域、时域及角频域内边齿处理前后的场均匀性,发现场的幅度和相位起伏从边齿处理前的2.87 dB、18.76°下降到1 dB、8.41°。分析结果表明,通过边齿处理,场的均匀性可获得较大的改善。

关键词：波束复合器边齿设计场均匀性分析几何绕射理论口径场积分

Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng Zheng wang Ruisong Zhu Ruijie Liu Jiang Ma Lina Hu Weihua wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and Control Engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

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低功耗无线门锁控制器的设计与研制

微型机与应用 2015年第20期34卷 87-89页

作者：刘炯肖秀华王砚陈磊王超峰苏州大学应用技术学院江苏苏州215006 奈特力斯电子(苏州)有限公司江苏苏州215006

设计并研制了一款用于高档住宅的无线掌纹门锁控制器,采用无线编解码技术实现无线发射和无线接收,由Microchip公司的纳瓦级别微处理器PIC16F684作为系统控制器;4节干电池作为无线接收模块的电源,可保证5 000次以上锁的正常开启。该门锁... 详细信息

设计并研制了一款用于高档住宅的无线掌纹门锁控制器,采用无线编解码技术实现无线发射和无线接收,由Microchip公司的纳瓦级别微处理器PIC16F684作为系统控制器;4节干电池作为无线接收模块的电源,可保证5 000次以上锁的正常开启。该门锁控制器实现了低功耗的设计,满足了市场对门锁安全性的需求。

关键词：低功耗无线门锁控制器掌纹识别设计与研制

Local-contrastive-learning machine with both generalization and adversarial robustness: A statistical physics analysis

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 109-123页

作者： Mingshan Xie Yuchen wang Haiping Huang PMI Lab School of Physics Sun Yat-sen University Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices Sun Yat-sen University

Distinct from human cognitive processing, deep neural networks trained by backpropagation can be easily fooled by adversarial examples. To design a semantically meaningful representation learning, we discard backpropagation, and instead, propose a local contrastive learning, where the representations for the inputs bearing the same label shrink(akin to boson) in hidden layers,while those of different labels repel(akin to fermion). This layer-wise learning is local in nature, being biologically plausible.A statistical mechanics analysis shows that the target fermion-pair-distance is a key parameter. Moreover, the application of this local contrastive learning to MNIST benchmark dataset demonstrates that the adversarial vulnerability of standard perceptron can be greatly mitigated by tuning the target distance, i.e., controlling the geometric separation of prototype manifolds.

关键词： machine learning statistical mechanics adversarial robustness neural networks

球化退火等温时间对高碳H13钢组织和性能的影响

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金属热处理 2022年第9期47卷 103-107页

作者：郭志凯连明洋卓兴建叶蕾曹培泽王超锋商秋月中铁工程装备集团有限公司河南郑州450016

采用不同的等温时间对高碳H13钢进行球化退火处理,并进行后续的淬火+回火处理,通过扫描电镜观察、硬度测试、冲击性能测试等方法,研究了等温时间对高碳H13钢组织和性能的影响。结果表明,随着等温时间的延长,淬回火处理后的高碳H13钢硬... 详细信息

采用不同的等温时间对高碳H13钢进行球化退火处理,并进行后续的淬火+回火处理,通过扫描电镜观察、硬度测试、冲击性能测试等方法,研究了等温时间对高碳H13钢组织和性能的影响。结果表明,随着等温时间的延长,淬回火处理后的高碳H13钢硬度先升高后降低,冲击性能先降低后升高,耐磨性先升高后降低。等温时间为2 h时,淬回火处理后高碳H13钢的晶界处分布较多条状和粒状碳化物,使其冲击性能下降。等温时间为3 h时,淬回火处理后高碳H13钢的晶粒内分布较多较大尺寸的粒状碳化物,使其耐磨性显著提高。等温时间为3 h时,高碳H13钢具有良好的综合性能。

关键词：高碳H13钢球化退火等温时间冲击性能耐磨性能

Flexible Graphene Field‑Effect Transistors and Their Application in Flexible Biomedical Sensing

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Nano-Micro Letters 2025年第2期17卷 252-313页

作者： Mingyuan Sun Shuai wang Yanbo Liang Chao wang Yunhong Zhang Hong Liu Yu Zhang Lin Han Institute of Marine Science and Technology Shandong UniversityQingdao 266237ShandongPeople’s Republic of China State Key Laboratory of Crystal Materials Shandong UniversityJinan 250100ShandongPeople’s Republic of China School of Integrated Circuits Shandong UniversityJinan 250100ShandongPeople’s Republic of China Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application Jinan250100ShandongPeople’s Republic of China

Flexible electronics are transforming our lives by making daily activities more *** to this innovation are field-effect transistors(FETs),valued for their efficient signal processing,nanoscale fabrication,low-power consumption,fast response times,and ***,known for its exceptional mechanical properties,high electron mobility,and biocompatibility,is an ideal material for FET channels and *** combination of graphene and FETs has given rise to flexible graphene field-effect transistors(FGFETs),driving significant advances in flexible electronics and sparked a strong interest in flexible biomedical ***,we first provide a brief overview of the basic structure,operating mechanism,and evaluation parameters of FGFETs,and delve into their material selection and patterning *** ability of FGFETs to sense strains and biomolecular charges opens up diverse application *** specifically analyze the latest strategies for integrating FGFETs into wearable and implantable flexible biomedical sensors,focusing on the key aspects of constructing high-quality flexible biomedical ***,we discuss the current challenges and prospects of FGFETs and their applications in biomedical *** review will provide valuable insights and inspiration for ongoing research to improve the quality of FGFETs and broaden their application prospects in flexible biomedical sensing.

关键词： Flexible Graphene Field-effect transistor Wearable Implantable Biosensor

MixerKT:A Knowledge Tracing Model Based on Pure MLP Architecture

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Computers, Materials & Continua 2025年第1期82卷 485-498页

作者： Jun wang Mingjie wang Zijie Li Ken Chen Jiatian Mei Shu Zhang Key Laboratory of Education Informatization for Nationalities Ministry of EducationYunnan Normal UniversityKunming650000China Yunnan Key Laboratory of Smart Education Yunnan Normal UniversityKunming650000China

In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant *** tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional *** knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential ***,these models may neglect crucial short-term dynamics and other relevant *** paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)*** proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature *** architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key *** evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge *** results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.

关键词： Knowledge tracing multilayer perceptron channel mixer sequence mixer

Hierarchical CNNPID Based Active Steering Control Method for Intelligent Vehicle Facing Emergency Lane-Changing

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Chinese Journal of Mechanical Engineering 2023年第4期36卷 355-371页

作者： Wensa wang Jun Liang chaofeng Pan Long Chen Automotive Engineering Research Institute Jiangsu UniversityZhenjiang 212013China

To resolve the response delay and overshoot problems of intelligent vehicles facing emergency lane-changing due to proportional-integral-differential(PID)parameter variation,an active steering control method based on Convolutional Neural Network and PID(CNNPID)algorithm is ***,a steering control model based on normal distribution probability function,steady constant radius steering,and instantaneous lane-change-based active for straight and curved roads is ***,based on the active steering control model,a three-dimensional constraint-based fifth-order polynomial equation lane-change path is designed to address the stability problem with supersaturation and sideslip due to emergency lane *** addition,a hierarchical CNNPID Controller is constructed which includes two layers to avoid collisions facing emergency lane changing,namely,the lane change path tracking PID control layer and the CNN control performance optimization *** scaled conjugate gradient backpropagation-based forward propagation control law is designed to optimize the PID control performance based on input parameters,and the elastic backpropagation-based module is adopted for weight ***,comparison studies and simulation/real vehicle test results are presented to demonstrate the effectiveness,significance,and advantages of the proposed controller.

关键词： Intelligent vehicle Rear-end collision avoidance Steering control Dynamics model Neural Network PID control