智能控制在现代包装工业中的发展和应用

叙述了反馈控制、自适应、鲁棒自适应，直到智能控制在包装工业中的进展，并阐述了智能控制在现代包装工业的发展中的应用前景。     

Robotics in the factory of the future: AI in manufacturing: The NBS AMRF as an intelligent machine

Within its Automated Manufacturing Research Facility (AMRF), the U.S. National Bureau of Standards (NBS) is addressing research issues in interface standards for the fully automated factory of the future for the production of small batches of discrete parts. Consisting of robots, machine tools and computers, the AMRF is being integrated using a real-time, sensory-feedback, data-driven hierarchical control architecture. As such, the AMRF is a research tool for investigating the manufacturing enterprise as a system of intelligent machines. This paper: (1) describes the AMRF in terms of its real-time control system architecture; (2) notes the role of symbolic languages, knowledge-representation, sensory-processing and other aspects of artificial intelligence in its development; and (3) speculates on further application of AI in future intelligent manufacturing systems similar in form to the AMRF.     

智能同步广播激励器及其标频

使用智能同步广播激励器,并采用CCTV传输的1MHz标频信号,就有可能实现自适应相位跟踪同步广播。这将大大节省中波段的频率资源。     

基于专家系统的机器人高层规划

本文介绍一个基于专家系统的机器人高层规划系统,阐述几个潜在应用子系统,并应用专家系统方法进行多机器人协调避碰运动规划。本系统具有良好的规划性能。     

矢量图形智能判断技术的研究与应用

研究矢量图形识别是建立工程制图自动阅卷与计算机辅助教学系统的基础。由于组成二维矢量图形图元类型的多样化及图形整体位置状态的不确定性，增加了矢量图形的识别与判断难度。结合开发的《三视图智能解答》系统，研究其智能识别与判断技术。系统中引入三视图导航技术，解决了图形整体定位与识别问题。实现了对矢量图形图元素信息的分类和提取，能够对所提取的的信息与标准答案进行智能判断与评定。该方法已在AutoCAD2000环境下使用AutoLISP语言编程实现。     

Driving intention recognition and behaviour prediction based on a double-layer hidden Markov model

We propose a model structure with a double-layer hidden Markov model (HMM) to recognise driving intention and predict driving behaviour. The upper-layer multi-dimensional discrete HMM (MDHMM) in the double-layer HMM represents driving intention in a combined working case, constructed according to the driving behaviours in certain single working cases in the lower-layer multi-dimensional Gaussian HMM (MGHMM). The driving behaviours are recognised by manoeuvring the signals of the driver and vehicle state information, and the recognised results are sent to the upper-layer HMM to recognise driving intentions. Also, driving behaviours in the near future are predicted using the likelihood-maximum method. A real-time driving simulator test on the combined working cases showed that the double-layer HMM can recognise driving intention and predict driving behaviour accurately and efficiently. As a result, the model provides the basis for pre-warning and intervention of danger and improving comfort performance.     

车辆TPMS轮速传感器误差消除方法研究

轮胎压力监测系统能够实时地自动监测行驶中汽车的轮胎气压,对于提高行车安全具有重要的意义。基于轮胎压力监测系统硬件平台,阐述了轮速信号的获取,研究了异点剔除方法,提出了基于弹性BP神经网络分析轮速传感器误差的方法,实现了对轮速信号的修正。仿真和实验结果表明,该轮速传感器误差消除方法的精度可达2×10-4rad,能够显著降低传感器误差,提高轮速信号的获取精度。     

物联网技术在高校校园中的应用

随着物联网技术的不断发展,物联网在高校的应用也越来越广泛。介绍物联网的概念,提出校园物联网的概念,对校园物联网的工作原理进行介绍,就物联网在高校校园中的应用做深入的探讨,在高校智能教学、教育管理和平安校园等方面做详细的分析。     

智能交通信号控制系统初探

城市交通拥挤是当今世界普遍关注的问题,它所带来的严重危害日益影响到人们的日常生活和社会经济的发展,而城市交通信号控制系统对解决这一问题发挥着不可替代的作用。从高性能智能交通信号控制系统的要求出发,针对目前我国城市交通问题的现状．对智能交通信号协调控制系统进行初步的研究和探讨。     

Conceptual digital twin modeling based on an integrated five-dimensional framework and TRIZ function model

Digital twin represents a fusion of the informational and physical domains, to bridge the material and virtual worlds. Existing methods of digital twin modeling are mainly based on modular representation, which limits guidance of the modeling process. Such methods do not consider the components or operational rules of the digital twin in detail, thereby preventing designers from applying these methods in their fields. With the increasing application of digital twin to various engineering fields, an effective method of modeling a multi-dimensional digital twin at the conceptual level is required. To such an end, this paper presents a method for the conceptual modeling of a digital twin based on a five-dimensional digital twin framework to represent the complex relationship between digital twin objects and their attributes. The proposed method was used to model the digital twin of an intelligent vehicle at the concept level.