Application of high-temperature permanent magnets Sm（Co,Fe, Cu,Zr）z in PPM focusing system

Rare earth permanent magnets Sm（Co, Fe, Cu, Zr）z with outstanding performance and high-temperature thermal stability were fabricated. Optimized by Fe content and process, Sm（Co0.72Fe0.15Cu0.1Zr0.03）7.5 magnet with B1〉0.75 T and Hci〉1300 kA/m at 300 ℃ can be obtained. According to the performance data of Sm（Co0.72Fe0.15Cu0.1Zr0.03）7.5, the magnetic field along central axis Bz in periodic permanent magnet （PPM） focusing system was simulated using electromagnetic field analysis software Maxwell 2D/3D. The Bz exhibited typical cosine curve along central axis, and the peak value of Bz was high enough to meet the demand of PPM focusing system at room temperature even at 200±20 ℃. Additionally, a kind of simple cooling structure for PPM focusing system was designed by setting cooling pipe between polepieces. Simulated results showed that smooth cosine curve of Bz was successfully achieved with good control of the thickness of cooling pipe.     

添加剂Y_2O_3对Mg-PSZ显微结构及力学性能的影响

研究了添加Ｙ２Ｏ３对ＭｇＰＳＺ显微结构及力学性能的影响。结果表明,ＭｇＰＳＺ中引入Ｙ２Ｏ３有利于降低烧结温度,促进立方化完全,但烧结体的力学性能有所降低。在１４００℃下热处理,（Ｍｇ,Ｙ）ＰＳＺ材料与ＭｇＰＳＺ一样发生ｃＺｒＯ２→ｔＺｒＯ２的析出过程,析出纺锤状四方ＺｒＯ２晶体。１４００℃热处理１０ｈ获得最大抗弯强度达６４８ＭＰａ,断裂韧性Ｋ１ｃ为８．３ＭＰａ·ｍ１／２。Ｙ２Ｏ３的加入使获得优异力学性能的热处理范围变宽,因而工艺上容易控制。但Ｙ２Ｏ３加入过多使析出困难。最佳加入量为１．０％（摩尔百分数）。Ｙ２Ｏ３的加入还使材料的Ｗｅｉｂｕｌ模数增高至１８．４６,表明（Ｍｇ,Ｙ）ＰＳＺ经热处理后能消除内部缺陷,使材料可靠性提高。     

乳液润滑剂润湿性与组分相关性研究

润湿性是乳化液的基本性能之一。本文考察了基础油及不同类型极性添加剂等因素对乳化液润湿性的影响,研究表明：乳液组分若能有效降低乳液的表面张力,将有利于增强乳液对金属的润湿性能。     

列车荷载作用下路轨系统及饱和弹性半空间上覆盖土层的动力响应

用解析法研究了移动列车荷载作用下下卧成层地基的路轨系统的动力响应问题。将整个系统分为上覆路轨系统和下卧土体。对于路轨系统,将钢轨简化为无限长弹性Euler梁,将枕木简化为连续质量块,同时考虑由Cosserat模型描述的道渣层。在实际工程中,地下水位往往位于地表以下几米处,因此将下卧土体考虑为成层土,其中,上层为弹性介质,下层为由Biot波动方程描述的饱和弹性半空间。在Fourier变换域内,联立铁路系统和下卧土体的动力方程,求解列车荷载作用下钢轨位移、加速度,土体位移、加速度,孔压表达式。利用数值积分方法对表达式进行Fourier逆变换,得到钢轨位移、加速度,土体位移、加速度,孔压在时域内的表达式。着重研究了弹性层厚度、密度、刚度和道渣层质量对钢轨动力响应的影响。计算结果表明,在低速情况下,这些参数对钢轨动力响应影响都很有限,但在高速情况下,这些参数对钢轨动力响应的影响都很大。     

六次甲基四胺对电镀锌电沉积过程的影响

采用循环伏安法和电化学阻抗谱,分析了六次甲基四胺对锌电沉积过程的影响。循环伏安测试结果表明:六次甲基四胺的加入使得锌的电沉积电位负移,说明六次甲基四胺在金属基体活性位点的吸附,使得锌电沉积的形核和生长需要在更大的阴极过电位下发生。同时六次甲基四胺提高了电沉积锌层在腐蚀介质中的耐蚀性。     

时变异方差不确定影响下的疲劳裂纹在线评估

主动导波结构健康监测能够实时在线地监测结构状态。 但时变因素影响会增加裂纹评估难度,降低评估准确性。 时变 因素的影响使得导波监测信号特征呈现明显的异方差特征,即导波信号特征分布方差随时间变化而改变。 针对此问题,提出了 异方差分位数回归辅助的裂纹在线评估方法,利用 3 条特殊的分位数回归曲线估计时变因素影响下信号特征随时间的分布变 化情况,实现对监测数据中的异方差不确定性的处理。 基于批量缺口梁结构的疲劳与导波监测试验数据对提出方法的有效性 进行验证,实验结果表明,提出的方法能够实现时变影响下的损伤评估,评估最大绝对误差为 1. 1 mm,均方根误差为 0. 4 mm, 并且可以有效处理时变异方差影响,量化其不确定度,为评估结果提供参考价值。     

一种差动式光纤Bragg光栅渗压、温度双参量传感器

设计了一种差动式双光纤Bragg光栅渗压、温度双参量传感器.在渗压作用下,波纹管产生一个轴向位移,并传递给等强度悬臂梁的自由端,使等强度悬臂梁产生一个挠度变化,带动粘贴在悬臂梁上下表面的光纤Bragg光栅的中心波长发生移位.通过检测两只光纤Bragg光栅中心波长的差值来获得渗压;通过检测两只光纤Bragg光栅中心波长的平均值来获得环境温度.传感器测试表明,传感器对渗压的灵敏度为1.982 nm/MPa,线性度约为0.97％,重复性为1.5％;传感器对温度的灵敏度为0.009 5 nm/℃,线性度约为3.4％.该传感器利用差动结构并结合适当的数据处理实现了对渗压与温度的双参量检测.     

初始剪应力与加荷速率耦合作用下饱和软黏土 强度特性试验研究

 对杭州饱和软黏土的不排水三轴压缩试验的静力特性进行研究。重点分析加荷速率与初始剪应力的耦合作用对杭州软黏土静力特性的影响。研究结果表明：随着初始剪应力的增加,土样的总强度增加,但抗剪强度减少;初始剪应力为60 kPa时,衰减幅度可达60%;土样的孔隙水压力表现为降低的趋势,初始剪应力为60 kPa时,衰减幅度可达50%。随着加荷速率的增加,土样的强度有所提高;孔隙水压力随之降低。当不存在初始剪应力时,应力–应变关系表现为硬化型曲线;当存在初始剪应力时,随着初始剪应力的增加,应力–应变关系曲线向软化型曲线发展。通过引入量纲一的峰值剪应力参数s与峰值孔隙水压力参数 对加荷速率与初始剪应力耦合作用下土体的峰值强度与孔隙水压力变化规律进行描述。该参数综合反映了初始剪应力与有效围压的影响。归一化后的结果表明：随着量纲一的应变率增加,s增加, 减少。在半对数坐标下,s, 分别与量纲一的应变率呈直线关系,并且随着初始剪应力的增加,s与 变化并不显著。     

Autonomous Learning System Towards Mobile Intelligence

How to efficiently deploy machine learning models on mobile devices has drawn a lot of attention in both academia and industries, among which the model training is a critical part. However, with increasingly public attention on data privacy and the recently adopted laws and regulations, it becomes harder for developers to collect training data from users and thus they cannot train high-quality models. Researchers have been exploring approaches to training neural networks on decentralized data. Those efforts will be summarized and their limitations be pointed out. To this end, this work presents a novel neural network training paradigm on mobile devices, which distributes all training computations associated with private data on local devices and requires no data to be uploaded in any form. Such training paradigm is named autonomous learning. To deal with two main challenges of autonomous learning, i.e., limited data volume and insufficient computing power available on mobile devices, this paper designs and implements the first autonomous learning system AutLearn. It incorporates the cloud (public data and pre-training)--client (private data and transfer learning) cooperation methodology and data augmentation techniques to ensure the model convergence on mobile devices. Furthermore, by optimization techniques such as model compression, neural network compiler, and runtime cache reuse, AutLearn can significantly reduce the on-client training cost. Two classical scenarios of autonomous learning are implemented based on AutLearn,with a set of experiments carried out. The results show that AutLearn can train the neural networks with comparable or even higher accuracy compared to traditional centralized/federated training mode with privacy preserved. AutLearn can also remarkably cut the computational and energy cost of neural network training on mobile devices.     

Periodic event‐triggered control for distributed networked multiagents with asynchronous communication: A predictive control approach

This paper investigates the periodic event‐triggered control problem for distributed networked multiagent systems with interconnected nonlinear dynamics subject to asynchronous communication. A method of state trajectory estimation for the interconnected neighboring agents over each prediction horizon with guaranteed error bounds is addressed to handle the asynchronous communication. Based on it, a distributed robust model predictive control (MPC) is proposed with a distributed periodic event‐triggered scheme for each agent. According to this algorithm, each subsystem generates presumed state trajectories for all its upstream neighbors and computes its own control locally. By checking the designed triggering condition periodically, the optimization problem of MPC will be implemented and solved when the local error of the subsystem exceeds a specified threshold. Then, the optimized control input will be determined and applied until the next time instant when the triggering condition is invoked. Moreover, sufficient condition for ensuring feasibility of the designed algorithm is conducted, along with the analysis of asymptotic stabilization of the closed‐loop system. The illustrative example for a set of coupled Van der Pol oscillators is reported to verify the effectiveness of the proposed approach.