In cold region engineering, the impact of coupled compression-shear loading on frozen soil foundations is a critical issue that urgently needs to be addressed, as it often significantly reduces bearing capacity and can cause structural failures. Accurately characterizing the mechanical behavior of frozen soil under dynamic coupled compression-shear loading is essential for enhancing the safety and stability of cold region engineering projects. This study prepared four frozen-soil specimens with varying tilting angles to investigate failure mechanisms and energy evolution under coupled compression-shear impact loading. The impact-compression experiments were conducted on the specimens under different loading strain rates and temperature conditions using a split Hopkinson pressure bar. The results indicated that the strength of frozen soil was effectively enhanced by higher strain rates and lower temperatures, while it was reduced by increased tilting angle. The fracturing morphology of frozen soil was analyzed from both microscopic and macroscopic perspectives to reveal its failure mechanisms. To quantify the strength characteristics of the frozen soil under various loading conditions, damage variables were defined from an energy-based perspective and incorporated into the Zhu-Wang-Tang viscoelastic constitutive model. Hence, a dynamic constitutive model for frozen soil under coupled compression-shear loading was developed. The model's predictive capability was validated through comparisons with the experimental data, which revealed a high level of agreement. The results of this study provide practical insights into the failure mechanisms and construction design of frozen soil foundations under coupled compression-shear impact loading in cold region engineering.
针对传统工业机械臂只能对固定位置的固定目标进行抓取的问题,在YOLOv5的基础上提出了一种基于角度估计的机械臂抓取系统目标检测算法——MAR-YOLOv5.首先,为了满足机械臂抓取过程中对目标物体角度信息的需求,在原算法的基础上添加了角度估计模块,通过环形平滑标签(Circular Smooth Label,CSL)角度分类法精准预测目标物体角度.然后,通过增加目标检测层提高对小目标物体的检测能力.最后,在特征提取C3模块中加入了卷积注意力机制(Convolutional Block Attention Module,CBAM),以增强在复杂环境中特征提取的效果.实验结果表明:本算法在自制的增减材制造数据集上的检测速度达到48 FPS,检测精度(mAP)为92.68%,与只添加角度估计模块的YOLOv5算法相比,mAP提高了4.19%.对于目标密集、遮挡等情况,本算法也可实时、准确地完成检测任务.
近年来随着物联网与通信技术的发展,自动售货机变得随处可见,但是对于散装酒的无人自动售卖目前还没有较为成熟的方案.本文综合运用互联网、单片机以及无线通信等物联网技术设计了一种智能售酒系统,以STM32单片机为控制核心,与流量计模块、电子锁模块、电机模块和液位传感器模块等结合,完成对售酒的测量与控制.该系统通过SIM7600CE通信模块向后台服务器端进行数据交互,记录消费者每次的购买信息及售酒机设备等相关信息,还可实时监测售酒机酒量状态信息,并及时发送缺料预警信息通知商家补货.实验测试结果表明:所设计的售酒机终端能达到基本预定技术要求,系统整体运行稳定,出酒误差百分比能够控制在±2％以内,具有较大的实用价值.
在分析了波纹补偿器异常与正常振动信号后,提出了一种基于GMM训练与HMM变换的振动信号分析方法.首先进行波纹管振动采集实验,保存振动数据,并进行初步时域分析;其次将在自然语言处理领域广泛应用的隐马尔可夫模型应用于波纹补偿器的振动数据分析;最后对提到的故障特征进行基于GMM-HMM算法的波纹补偿器的故障诊断模型构建.通过对实验数据进行测试验证,故障识别率高达96.7%,而传统的算法分析波纹管振动故障,其识别率最高仅为86.7%.此结果表明该算法实现了对波纹补偿器运行状态的准确识别,保证了故障诊断的合理性与高效性.
6005A铝合金材料在交通运输和航空航天等领域的使用中不可避免地会受到高应变率载荷条件的影响.为了研究这种材料的冲击动态力学性能,对6005A铝合金进行了准静态和动态压缩实验.实验结果表明,在高应变率加载下,6005A铝合金具有应变硬化效应、应变率强化效应和热软化效应.基于实验结果,提出了一种改进的Johnson-Cook本构模型,且改进的模型所得结果与实验拟合曲线吻合良好.为了便于工程实际应用,本文使用数值积分算法对改进的模型进行编程实现,用于6005A铝合金的冲击动态压缩数值模拟,进一步证实了改进的模型的合理性.
