基于输送带及视觉跟踪的机器人分拣包装工作站仿真

目的 提高分拣包装工作站的生产效率和柔性,并探索在早期设计阶段利用虚拟仿真技术进行验证。方法 以某食品公司巧克力饼干产品的生产为例,提出结合输送带跟踪和视觉识别技术搭建分拣包装仿真工作站。在ABB公司离线编程与仿真软件Robotstudio开发环境下,首先对相关设备进行了三维建模,并根据任务要求完成工作站的空间布局。其次,需要完成输送带创建、动态Smart组件设计、工作站逻辑连接、输送带跟踪功能启用、相机数据记录和机器人控制程序编写。最后,分析工作站结构得到生产节拍的参数设定公式。结果 仿真工作站实现了对持续移动输送带上杂乱摆放物料的动态跟踪分拣装盒,能依据理论计算方式调节参数满足生产节拍的需求。结论 工作站达到了预期功能目标,可以为各行各业里以机器人为中心的分拣包装系统高效、柔性生产研究提供参考与借鉴。     

Improved Tribocorrosion Properties of Ti6Al4V Alloy by Anodic Plasma Electrolytic Oxidation

Ti6Al4V alloy has good corrosion resistance due to the formation of the passive oxide films on the surface of Ti6Al4V alloy. However, Ti6Al4V alloy has poor tribocorrosion resistance in the seawater environment. Herein the present work, plasma electrolytic oxidation (PEO) with the electrolyte of glycerol and sodium borate is used to generate PEO coatings on the surface of Ti6Al4V alloy to improve its tribocorrosion properties. The microstructure and tribocorrosion properties of PEO coatings are investigated by using scanning electron microscopy, X-ray diffraction, and tribometer, respectively. The growth kinetics and the tribocorrosion mechanisms of PEO coatings are discussed in detail. It is shown in the results that PEO coatings deposited on the surface of Ti6Al4V alloy are composed of rutile and anatase phases. The surface hardness and thickness of PEO coatings are enhanced with the increase of the voltage and time. The wear rate of Ti6Al4V alloy with PEO coatings is significantly reduced in artificial seawater.     

Fine-Grained Multivariate Time Series Anomaly Detection in IoT

Sensors produce a large amount of multivariate time series data to record the states of Internet of Things (IoT) systems. Multivariate time series timestamp anomaly detection (TSAD) can identify timestamps of attacks and malfunctions. However, it is necessary to determine which sensor or indicator is abnormal to facilitate a more detailed diagnosis, a process referred to as fine-grained anomaly detection (FGAD). Although further FGAD can be extended based on TSAD methods, existing works do not provide a quantitative evaluation, and the performance is unknown. Therefore, to tackle the FGAD problem, this paper first verifies that the TSAD methods achieve low performance when applied to the FGAD task directly because of the excessive fusion of features and the ignoring of the relationship’s dynamic changes between indicators. Accordingly, this paper proposes a multivariate time series fine-grained anomaly detection (MFGAD) framework. To avoid excessive fusion of features, MFGAD constructs two sub-models to independently identify the abnormal timestamp and abnormal indicator instead of a single model and then combines the two kinds of abnormal results to detect the fine-grained anomaly. Based on this framework, an algorithm based on Graph Attention Neural Network (GAT) and Attention Convolutional Long-Short Term Memory (A-ConvLSTM) is proposed, in which GAT learns temporal features of multiple indicators to detect abnormal timestamps and A-ConvLSTM captures the dynamic relationship between indicators to identify abnormal indicators. Extensive simulations on a real-world dataset demonstrate that the proposed algorithm can achieve a higher F1 score and hit rate than the extension of existing TSAD methods with the benefit of two independent sub-models for timestamp and indicator detection.     

Achieving sustainable customer loyalty in airports: The role of waiting time satisfaction and self-service technologies

Waiting time appears to be an unavoidable part of the service industry, particularly at the airport, where you may encounter delays due to check-in, screening, and other activities. This waiting experience can vex customers, affecting their perception of the service provider and, consequently, their loyalty. Our study aimed to determine the effect of waiting time satisfaction and the use of self-service technology on the long-term sustainability of customer loyalty. 750 structured questionnaires were distributed to travelers at two international airports in Turkey. PLS-SEM was used to analyses the models. Our findings indicate that customer satisfaction with waiting times and the use of self-service technologies are critical for the long-term sustainability of customer loyalty. Additionally, we discovered that waiting time satisfaction partially mediates the relationship between self-service technology use and long-term customer loyalty. Finally, the managerial implications were discussed, including future research suggestions.     

霍泉灌区作物需水量实时预报

采用联合国粮农组织最新推荐的修正Ｐｅｎｍａｎ公式分析计算了霍泉灌区长系列参考作物的腾发量及其变化规律,在此基础上提出了该灌区冬小麦、夏玉米需水量预报模型．分析了预报模型中参数Ａ０的变化规律,并在预报过程中进行调整．运用实测资料检验表明,修正后的模型在逐日作物需水量预报中更符合实际,具有比较高的精度．     

图示评审技术中资金的时间价值的费用探析

在图示评审技术（ＧＥＲＴ）网络模型的基础上,考虑资金的时间价值,探析费用参数求解的两种方法：一是利用信号流图理论的方法,二是利用模拟技术的模拟解法．并用算例求解,另外,对三峡左岸机组安装施工费用进行了研究．     

太阳能全玻璃真空集热管参数方程及测算

论述了太阳能全玻璃真空集热管的热损系数ＵＬ、保温率ηＢ、时间常数τＣ的参数方程并给出了测算方法。     

马尔科夫排队过程

马尔科夫排队过程是马尔科夫决策规划的一个重要应用。本文研究将一般的排队系统转化为马尔科夫排队过程,因而可以利用马尔科夫决策规划的求值运算来求解。本文着重介绍了顾客逐一的接受服务和顾客成批的接受服务两种最主要类型并计算给出相应的结果。     

Stature and seat position as factors affecting fractionated response time in motor vehicle drivers

Motor vehicle accident fatalities are a cause for concern internationally; all drivers need to selectively attend to environmental changes, and to react swiftly and appropriately. The focus of the present paper was to investigate the effect of stature and seat positioning on fractionated response time. Eighty four young South African adults spanning a range of statures from 1.48 m to 2.00 m were tested in two extreme seat positions (near and far) using a European designed car-shell. Significant differences (p < 0.05) in knee flexion angle, but not in reaction or movement times were identified. Separation of tallest (X 1.93 m) and shortest (X 1.56 m) subjects (n = 20) revealed no significant stature-related differences in response times. However, the tall group showed significantly improved results when seated in the far position and the short group when seated in the near position. The results indicate that correct seat positioning will exert a significant effect on the overall response time of the driver, which in turn will affect the braking distance whilst driving.     

电力监控系统防越级跳闸方案的研究

针对单一防越级跳闸方案和地面供电系统防越级跳闸方案均不能有效解决煤矿井下越级跳闸故障的问题,提出了一种采用电力监控系统解决煤矿井下越级跳闸故障的方案;以河南平宝煤业有限公司供电网络为例,详细介绍了该方案的实现原理及具体实施情况。实际应用表明,该方案实现了上下级开关的配合,有效防止了越级跳闸故障。