Optimal control of parallel queues with impatient customers

We consider a queueing system with a number of identical exponential servers. Each server has its own queue with unlimited capacity. The service discipline in each queue is first-come-first-served (FCFS). Customers arrive according to a state-dependent Poisson process with an arrival rate which is a non-increasing function of the number of customers in the system. Upon arrival, a customer must join a server’s queue according to a stationary state-dependent policy, where the state is taken to be the number of customers in servers’ queues. No jockeying among queues is allowed. Each arriving customer is limited to a generally distributed patience time after which it must depart the system and is considered lost. Two models of customer behavior are considered: deadlines until the beginning of service and deadlines until the end of service. We seek an optimal policy to assign an arriving customer to a server’s queue. We show that, when the distribution of customer impatience satisfies certain property, the policy of joining shortest queue (SQ) stochastically minimizes the number of lost customers during any finite interval in the long run. This property is shown to always hold for the case of deterministic customer impatience.     

液力变速箱测控系统的研制与应用

为维修后的液力变速箱提供检测们维修质量评定依据,研制了适用于美国艾里逊5000／6000／750系列和贵州凯星BY系列的非公蹄液力变速衔测控系统。该测控系统采用RS485总线技术构建测控系统硬件线路,采用VB6．0进行测控系统的软件开发,实现了对液力变速箱压力、温度、转速及流量等参数的采集、显示、存储、处理和报表打印等功能。现场试验和应用情况表明,该测控系统符合设计要求,测试数据满足液力变速箱性能试验方法规范的要求。     

论工业设计与设计管理

设计管理是当今工业设计的一个新兴学科,其发展关系着工业设计自身的进步。本文通过对设计与管理关系的探讨,阐述了设计管理的概念,以及设计管理中关于设计师管理与企业设计管理的研究。     

基于自注意力机制的无边界应用动作识别方法

近年来,工业互联网获得了飞速的发展.但是和传统互联网一样,工业互联网也面临着大量的网络攻击威胁和敏感信息泄露风险.而流量识别技术,特别是细粒度的应用动作识别技术,可以辅助网络管理者对异常行为进行检测和及早发现隐私泄露风险,保障工业互联网的安全.然而,现有动作识别技术依赖对流量数据中动作边界的预先分割,无法识别无边界的动作,难以应用于实际场景.为解决这一问题,提出一种无边界动作识别算法：首先构建基于自注意力机制的包级识别模型,对数据包进行动作分类;然后提出动作聚合算法,从数据包的分类结果中聚合出动作序列;最后,建立2种新指标来衡量识别结果的好坏.为验证算法的可行性,以微信为实例进行实验,结果表明该模型能够取得最高超过90%的序列识别精度.这一研究成果将有望极大推动应用动作识别技术的实用化.     

E+H组合式过程测控装置及实时监控系统设计

Endress+Hauser(E+H)工业现场仪表广泛应用于石油、冶金、电力、生命科学等多个核心行业,具有可靠集成、精准测量、交互式数据管理等特点。为提高实验装置工业适用性,培养学生熟练运用工业级传感器和过程监控的操作技能,将这类传感器引入实验室,设计了一套E+H组合式过程测控装置与实时监控系统。系统以过程控制涉及的典型对象为基础,以PLC为控制主体,组合装配多类工业级E+H传感器完成检测与控制,并具备实时组态控制显示和远程可视化监控功能。可实现自主设计并完成工业过程中常见的液位、流量、温度、溶液PH等控制量的测控实验,为自动化、测控技术、传感器等相关专业课程提供综合实验平台。     

20t／h工业过热锅炉多媒体智能化控制系统

介绍一个新颖的２０ｔ／ｈ工业过热锅炉多媒体智能化控制系统,具体性能可靠、功能强大、调试方便、界面友好、便于操作维护等特点。经济效益显著。     

基于网络结构搜索的工业过程自动故障诊断方法

针对现有基于深度神经网络的工业过程故障诊断方法存在网络结构设计烦琐及参数寻优耗时等问题,提出了一种基于网络结构搜索的工业过程自动故障诊断方法(automatic fault diagnosis, AutoFD),该方法采用AutoFD网络结构搜索算法,来自动完成卷积神经网络的网络结构设计和网络参数寻优。在此基础上,首先通过在原始数据上施加操作生成新通道;接着利用表现预测加速获取通道适应性排序的过程;然后依据通道适应性排序,通过表现预测来快速选取最优卷积通道数;最终根据最优卷积通道来搜索表现最优的多通道卷积神经网络模型用于工业过程自动故障诊断。采用田纳西—伊斯曼(Tennessee Eastman, TE)工业过程和数值系统对提出方法进行验证,结果表明该方法可以实现网络结构自动设计及网络参数的自动寻优,并且具有优良的故障诊断性能。     

Impatient customers in an M/M/1 queue with single and multiple working vacations

We consider an M/M/1 queue with impatient customers and two different types of working vacations. The working vacation policy is the one in which the server serves at a lower rate during a vacation period rather than completely stop serving. The customer’s impatience is due to its arrival during a working vacation period, in which the customer service rate is lower than the normal busy period. We analyze the queue for two different working vacation termination policies, a multiple working vacation policy and a single working vacation policy. Closed-form solutions and various performance measures like, the mean queue lengths and the mean waiting times are derived. The stochastic decomposition properties are verified for both multiple and single working vacation cases. A comparison of both the models is carried out to capture their performances with the change in system parameters.     

Security measure allocation for industrial control systems: Exploiting systematic search techniques and submodularity

To protect industrial control systems from cyberattacks, multiple layers of security measures need to be allocated to prevent critical security vulnerabilities. However, both finding the critical vulnerabilities and then allocating security measures in a cost‐efficient way become challenging when the number of vulnerabilities and measures is large. This paper proposes a framework that can be used once this is the case. In our framework, the attacker exploits security vulnerabilities to gain control over some of the sensors and actuators. The critical vulnerabilities are those that are not complex to exploit and can lead to a large impact on the physical world through the compromised sensors and actuators. To find these vulnerabilities efficiently, we propose an algorithm that uses the nondecreasing properties of the impact and complexity functions and properties of the security measure allocation problem to speed up the search. Once the critical vulnerabilities are located, the security measure allocation problem reduces to an integer linear program. Since integer linear programs are NP‐hard in general, we reformulate this problem as a problem of minimizing a linear set function subject to a submodular constraint. A polynomial time greedy algorithm can then be applied to obtain a solution with guaranteed approximation bound. The applicability of our framework is demonstrated on a control system used for regulation of temperature within a building.     

基于AI智能调节器的小型装置控制系统

采用AI智能调节器，流量控制器，压力变送器等，对小型装置的温度，流量、压力等参数实行测量与控制，效果良好，增加工控机，与AI智能调解器构成小型集散控制系统，进行分散控制和集中管理，使控制系统的功能更加完善，可靠性更高。