[数据驱动的智能服务]数据驱动的复杂产品智能服务技术与应用

随着传感器、数据采集装置和其他具备感知能力的模块在复杂产品服务运行阶段的应用，复杂产品运维系统的数字化和智能化程度越来越高，具有实时、多源、异构、海量等特性的数据成为提高复杂产品系统可靠和低成本运行的决策依据，数字孪生技术提供了一种有效途径。介绍了数据驱动的复杂产品智能服务研究进展；分析了数据驱动的智能服务基本特征与框架模型；提出了数据驱动的复杂产品智能服务方法，主要包括面向服务的复杂产品建模与仿真方法、数据驱动的服务需求获取与精准分析预测方法、基于数字孪生的设备故障识别与动态性能预测方法、数据驱动的装备视情维修与备件库存联合多目标决策优化方法、基于数字孪生的复杂产品辅助维修技术、多要素协同的复杂装备能效精准分析预测方法、基于数据挖掘的复杂产品运行优化控制方法等；给出了智能服务系统的应用案例。所提出的框架和方法可为现代制造服务的智能化转型升级提供参考。     

带检测环节的制造单元布局优化

针对带检测环节的智能制造单元，考虑其具有随机性因素的特点，本文对其机器布局问题进行研究。首先对该智能制造单元的生产过程及特点进行分析，建立其机器布局优化问题的随机非线性整数规划的数学模型；然后建立该智能制造单元对应的仿真模型，对该优化问题进行求解；最后分析抽检率的变化对最优解造成的影响，并对该智能制造单元的性能指标进行方差分析，研究不同的布局方案和抽检率对系统性能的影响程度。研究成果为企业进行智能制造单元的机器布局提供决策依据。     

基于Android的智能家居控制系统的设计研究

随着科学技术的发展，各种电器和家具控制的智能化是目前市场流行起来。人们生活水平的不断提高使人们对生活的质量有了一定的要求。在人们的日常生活中，家用电器是不可缺少的生活用品，如何快捷方便的对这些电器进行管理，使我们需要进行研究的任务。智能家居控制系统的出现为人们的生活带来了便利，也逐渐的改变和影响着人们的生活方式。本文就基于Android的智能家居控制系统的设计进行分析和研究。     

Traffic video‐based intelligent traffic control system for smart cities using modified ant colony optimizer

Road traffic congestion is a serious problem in today's world and it happens because of urbanization and population growth. The traffic reduces the transport efficiency in the city, increases the waiting time and travel time, and also increases the usage of fuel and air pollution. To overcome these issues this papers propose an intelligent traffic control system using the Internet of Vehicles (IoV). The vehicles or nodes present in the IoV can communicate between themselves. This technique helps in determining the traffic intensity and the best route to reach the destination. The area of study used in this paper is Vellore city in Tamilnadu, India. The city map is separated into many segments of equal size and Ant Colony Algorithm (AOC) is applied to the separated maps to find the optimal route to reach the destination. Further, Support Vector Machine (SVM) is used to calculate the traffic density and to model the heavy traffic. The proposed algorithm performs better in finding the optimal route when compared to that of the existing path selection algorithms. From the results, it is evident that the proposed IoV‐based route selection method provides better performance.     

Intelligent Information‐Centric Networking routing scheme under imprecise information

Information‐Centric Networking (ICN) has been accepted to overcome some weaknesses of the current Internet architecture, showing that “what is being exchanged” is more important than “who are exchanging information.” Given the inadequate considerations on Quality of Service (QoS) and energy saving in ICN routing, we propose in this paper a routing algorithm to enhance the two aspects. At first, on one hand, Cauchy distribution is used as a fuzzy model to evaluate users' QoS requirements, such as bandwidth, delay, and error rate; on the other hand, we formulate energy saving problem to evaluate the green quality of routing algorithm. Then, we design a link selection approach by considering QoS and energy saving, which belongs to a multi‐objective decision problem resolved by intelligent drops algorithm. Finally, we implement the proposed algorithm and compare it with the famous adaptive forwarding mechanism in terms of some significant metrics, and the experimental results reveal that the proposed algorithm is more efficient.     

基于蛛状网拓扑智能变电站“三层一网”通信系统研究

在110kV及以下电压等级变电站中，“三层一网”架构虽然简化了二次系统接线，但实时性和可靠性难以保证。针对传统拓扑结构下的实时性和可靠性无法同时达到最优效果的问题，本文采用“三层一网”架构下蛛状网拓扑结构，仿真结果表明该结构下的通信系统实时性最佳，解决了传统拓扑结构实时性差的问题，并结合算例验证了其可行性；运用故障树分析法定量分析不同结构的可靠性，结果表明蛛状网结构的可靠性更好。为解决研究复杂的通信系统可靠性时传统故障树方法有一定的局限性的问题，本文引入T-S模糊故障理论，建立T-S故障树模型，计算结果表明蛛状网结构下通信系统可靠性最好。根据本文研究可以得到蛛状网拓扑结构能同时提高通信系统实时性和可靠性的结论。     

Homogeneous and Universal Detection of Various Targets with a Dual-Step Transduced Toehold Switch Sensor

Toehold switch sensors represent a class of new advances that allow specific targets to trigger in situ expression of a protein reporter. Although they offer unique advantages of a label-free nature and high portability, they generally require repeated sequence design, high expenditure, and laborious optimization of toehold switch sequences according to different targets. To simplify the sensing process further and to improve its practicability, we innovatively introduce a dual-step pre-transduction upon traditional toehold switch sensor. Through two successive toehold-mediated strand-displacement reactions that are initiated, respectively, by a linear and an associative trigger, different DNAs, RNAs, or ligands of functional nucleic acids can be generally transduced into the input of one high-performance toehold switch sensor. This advance greatly increases the target range. Furthermore, the whole process is signal-on, homogeneous, and free of any requirements for complicated operations such as probe labeling, separation, and reconstruction of the toehold switch, being promising and practical even in portable or point-of-care assays.     

Disturbance observer-based adaptive boundary iterative learning control for a rigid-flexible manipulator with input backlash and endpoint constraint

In this article, an observer-based adaptive boundary iterative learning control law is developed for a class of two-link rigid-flexible manipulator with input backlash, the unknown external disturbance, and the endpoint constraint. To tackle the backlash nonlinearities and ensure the vibration suppression, the disturbance observers based upon the iterative learning conception are considered in the adaptive boundary control design. A barrier Lyapunov function is incorporated with boundary control law to restrict the endpoint state. Based on the defined barrier composite energy function, the tracking angle error convergence of the rigid part is guaranteed, and the vibrations of the flexible part are suppressed through the rigorous analysis. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed control.     

商用车输入轴生产线智能化建设

根据用户要求,从空间布局和网络拓扑方面介绍了输入轴智能化生产线的建设过程,详述各环节的工作任务和动作机能,给出了主要零/部件的结构图样。生产线投用后,成效显著。对智能化制造商具有指导意义,对商用车用户具有借鉴意义。     

基于目标跟踪的变电站隔离开关状态图像识别方法

为解决变电站中隔离开关状态的自动识别问题，提出了基于目标跟踪的开关分合状态图像识别方法。首先，基于隔离开关开合过程的动态视频，通过 Ｌａｓｓｏ正则化稀疏表示的目标跟踪模型对隔离开关运动轨迹进行识别；其次，利用隔离开关２个闸刀之间的距离自动识别算法获得开关的分合状态。实测结果表明，该方法可快速跟踪开关运行轨迹，实时对变电站中隔离开关状态进行准确识别。