A variational approach for free vibrating micro-rods with classical and non-classical new boundary conditions accounting for nonlocal strengthening and temperature effects

Abstract

Transverse vibration of a circular cross sectional micro-rod subjected to a new kind of boundary constraints with elastic torsional springs is presented based on nonlocal elasticity. A nonlocal strengthening beam model is utilized and the effect of temperature changing is taken into consideration. The variational method and Hamilton’s principle are applied to derive the governing equation of motion and corresponding boundary conditions. A higher-order partial differential equation that is a typical characteristic of nonlocal strengthening model is developed, and the boundary conditions contain not only classical conditions but also non-classical higher-order conditions. Unlike previous studies which were only concerned with some conventional boundary constraints, we consider more general boundary conditions named elastic torsional spring supports. Such boundary conditions are between the simply supported and clamped ones, and they are closer to the actual constraints of existing engineering structures. Natural frequencies of micro-rods with new boundary constraints are determined via an eigenvalue method and compared with other results in the literature. It is shown that the nonlocal scale factor, thermal parameter, rigidity parameter and torsional spring coefficient play significant roles in free vibration of micro-rods. The research can provide a reference for a large class of boundary conditions ranging from simply supported to clamped micro-rods.     

脉冲电流对6016-T4铝合金板材力学性能的影响

为研究在电流辅助成形时脉冲电流的电流密度、占空比和脉冲频率3个因素对6016-T4铝合金板材力学性能的影响规律,设计了3因素5水平的正交实验。实验表明,对6016-T4铝合金力学性能影响的主次因素是:电流密度>占空比>脉冲频率。在此基础上,选用主次2个因素,即电流密度和脉冲频率,使用控制变量法进行进一步的实验研究。实验结果表明,电流密度对6016-T4铝合金力学性能影响较大,改变电流密度的同时带来了明显的焦耳热效应,该效应对材料有明显的软化作用,降低了材料的流动应力,但是,同时也降低了铝合金板的伸长率,这是因为过大的电流密度加剧了试样的主应变演化,进而促进了试样的断裂。而脉冲频率的变化对6016-T4铝合金板材的力学性能影响很小,这也印证了正交实验的结论。     

基于深度网络迁移学习的致痫区脑电识别* .txt

摘要：致痫区脑电识别能够为癫痫外科手术提供重要的参考价值。提出了一种基于深度网络迁移学习的致痫区脑电识别算法。首先利用连续小波变换（CWT）对脑电信号进行时频分析，获得脑电信号时频图；然后迁移学习AlexNet网络模型，调整网络结构使之适应于致痫区脑电识别，将模型第7层全连接层输出作为脑电信号时频图的特征表示，最后利用支持向量机（SVM）、BP神经网络、长短期记忆网络（LSTM）、基于稀疏表达分类算法（SRC）、线性判别分析（LDA）等分类算法进行特征分类。基于开源脑电数据集采用十折交叉验证的方法对算法进行了验证,比较6种分类器的效果，得到SVM算法的平均特异性为8881%，灵敏度为8807%，准确率为8844%，证明了该方法识别致痫区脑电信号的有效性。 .txt     

基于人工神经网络的柴油机失火故障诊断

车载诊断系统在诊断失火故障时,采用基于曲轴段角加速度和阈值规则相结合的方法,该方法在内燃机高速轻载运行时诊断单缸完全失火工况存在一定的局限性。通过对比分析失火和正常工况下曲轴瞬时转速的幅频和相频特征,提取不同谐次的幅值和相位信息,结合人工神经网络作为故障模式识别工具,得到了一种改善方法。通过台架实验,对此改善方法进行了单缸完全失火、两缸完全失火和单缸一定程度失火的故障诊断测试。结果表明,在实验条件下该方法可以有效识别不同的失火模式,并可在单缸失火模式下实现失火程度判别。同时,该方法通过少量工况数据训练神经网络,即可实现一定转速范围内的失火诊断,可行性强,可用于发动机失火故障在线诊断。     

基于差分进化算法的手眼标定方法

针对眼在手机器人视觉系统的手眼标定问题，提出了一种基于差分进化算法的手眼标定方法。首先建立了眼在手机器人视觉系统手眼标定的数学模型，通过李群李代数理论，将手眼标定问题转化为误差函数的优化问题，同时保证了优化问题的最优解落在特殊欧氏群ＳＥ（３）上。通过差分进化算法对优化问题进行求解，避免了求解过程中的局部最优问题。最后在实物平台上进行了手眼标定实验，实验结果验证了算法的可行性和有效性。     

低能量密度炸药连续装药光面爆破技术研究

为了提高光面爆破成型质量，提出了一种低能量密度炸药连续装药光面爆破技术，利用LS DYNA进行数值模拟，对比2#岩石乳化炸药间隔装药和低能量密度炸药连续装药的应力场，然后将此技术用于长九（神山）灰岩矿四号隧洞控制爆破和露天边坡光面爆破。结果表明：2#岩石乳化炸药间隔装药模型中，装药段与非装药段测点应力峰值相差很大；而在低能量密度炸药连续装药模型中，沿炮孔轴向相同爆心距的测点应力峰值保持一致；使用低能量密度炸药进行连续装药，能够避免装药段的过度破坏和非装药段的欠挖，提高残孔率，且省去了导爆索捆绑时间，提高周边孔装药效率，节省了爆破成本。     

波浪荷载作用下海上新型潜式浮式风力机运动特性研究

以适用于中等水深(50~200 m)的新型潜式浮式风力机为研究对象,该风力机基础综合Spar式、半潜式及张力腿(TLP)3类浮式风力机基础的优点,运行时基础主体淹没在水下,具有较小的水线面(如同Spar平台),受波浪影响较小;平台通过张紧式系泊线与海床相连(如同TLP平台),具有良好的垂荡和摇摆运动特性;拖航状态下,浮式平台处于半潜状态,水线面面积大(如同半潜式平台),具有良好的浮稳性。通过分析不同波况下的潜式浮式风力机耦合动力响应得到潜式浮式基础的横荡、纵荡、垂荡及纵摇运动响应,以及发电功率、叶片根部弯矩、塔筒顶部和底部弯矩、锚链张力时程曲线。研究结果表明:波浪对于结构的纵摇运动的影响最为明显,对发电功率、叶片根部弯矩和塔筒顶部弯矩影响较小,对塔筒底部弯矩和系泊线张力影响较大。     

浅谈船用主机使用低硫燃油面临的挑战与应对措施

介绍了低硫燃油和传统的船用高硫燃油在化学成分和物理特性方面存在的诸多不同;指出:IMO2020限硫令对船舶运营带来了很大的挑战。基于两大主机制造商的相关文件和实际服务经验，归纳总结了船用主机使用低硫燃油运营时应注意的事项及应对措施，为船舶安全稳定运营提供参考。     

低比转速压气机轮毂轮缘型线多目标优化设计

对电动增压器用低比转速离心压气机轮毂轮缘进行优化设计。采用NUMECA/FINE Design 3D对压气机进行几何参数化,生成数据库样本,利用人工神经网络和遗传算法对轮毂轮缘型线进行优化,并进行流场分析。仿真结果表明,在设计转速为40000 r/min时,优化后设计点压比和效率分别提高6.59%和3.73%。     

Allocation and sizing of battery energy storage system for primary frequency control based on bio-inspired methods: A case study

This paper presents a new procedure for optimal allocation and optimal sizing of a battery energy storage system (BESS) for primary frequency support in an isolated power system. For the BESS allocation, a transmission bus system with larger frequency decline is recognized and the BESS sizing is performed by a constrained optimization strategy based on a new modified metaheuristic, called Developed Harris Hawks Optimization (DHHO). The simulation results of the suggested DHHO are compared with Bat Optimization Algorithm (BOA) and Genetic Algorithm (GA) from the literature to show the method efficiency. The final results showed higher precision with lower required iterations for the suggested DHHO method. Also, the proposed DHHO gives lower investment costs for BESS with lower power and energy requirement toward the other compared methods.