柔性制造单元的智能调度系统

本文基于递阶控制原理提出了柔性制造单元的一种新的计划与调度方法,并综合采用了理论分析、专家系统技术和仿真技术,建立了一个智能调度系统原型.另外,在制造单元调度问题的描述上采用了状态方程形式,从系统的观点来研究调度问题.并在此基础上建立了仿真模块,对单元的加工过程进行了仿真实验.

监控式遥控机器人初探

本文初步探讨了遥控机器人监控的基本概念,得出这样一种认识:监控方式是机器人向智能化发展的一个恰当模式,监控系统是由人的高级智能与机器人的低级智能构成的系统.监控是系统中这两种智能相互作用的过程,人的智能应当能够在机器智能的不同级别上输入,我们研制了一个遥控机器人监控操作器的实验系统,通过实例和实验作了说明.

数控自动编程专家系统

本文简要地介绍了数控自动编程专家系统.其中包括:专家系统知识表示的形式;分层次的黑板结构;前向推理求解策略和相应的解释功能;系统针对不同类型的曲线组合,采用不同的独立的知识源(KS)进行处理.由于在知识的处理上采用编码技术,在前向推理求解策略中使用启发信息和“剪技”技术,提高了系统的时空效率.系统中的规划程序能自动规划切削路径.输出供数控车床使用的 NC 代码,并可在显示屏上进行图形显示和切削仿真.目前原型系统已经在 IBM-PC 和 Sun3/60计算机上利用FORTRAN 语言实现.

知识表达语言(NFA)及其在石油测井解释专家系统中的应用

石油测井解释是一项逻辑推理和数值计算交错进行的复杂过程。为了描述测井解释专家的这种知识、经验并模拟其思维方式,在扩充纯产生式规则的基础上,我们开发了知识表达语言——NFA,它把逻辑推理和数值计算综合成统一的形式。石油测井解释专家系统 LIX 先后在 INTERDATA-85机和 PE-3230机上实现,现场(胜利油田)运行近两年,解释了130余口井,符合率94%以上。LIX 实质上是 NFA 语言的解释系统,它的研制成功,说明了 NFA 语言的有效性和实用性。

基于CDMA技术的无线监控系统的研究与应用

利用CDMA技术,可以完成控制中心对移动终端设备的无线监控,从而实现监控系统的高质量性,高效率性以及高抗干扰性。本文给出了一种基于CDMA技术的无线监控系统方案,主要介绍了这种无线监控系统在警犬机器人中的应用,其中重点讨论了该应用系统的硬件组成以及软件的设计与功能实现。

基于以太网技术的ARCNET数据采集系统设计

为了解决ARCNET网络与以太网不兼容的问题,针对目前ARCNET网络设备监控管理系统存在的缺陷,提出了一种基于嵌入式TCP/IP协议的ARCNET数据采集与传输系统。分析了该数据采集系统的原理与结构,给出了系统的硬件设计方案,完成了数据采集与传输的软件结构设计和嵌入式TCP/IP协议栈的建立。对系统的实时性、可靠性和应用效果等进行了测试,结果证明,系统使用方便,性能稳定,具有良好的实时性和可靠性,综合性能优于现有的ARCNET数据采集系统。

基于数字化生产模型的在线故障诊断技术研究

提出了一种基于数字化的生产模型,使用控制图、故障树分析和专家知识,能够进行制造过程实时监控的诊断,该模型提高了故障诊断系统的可靠性,并提供了可实际操作的可视化建模工具。所开发的在线统计过程控制系统能够根据生产事件的监测,动态响应制造过程变化。该系统运用可视化建模工具,根据专家经验进行故障树建模,通过故障树自动生成专家系统诊断规则库,实现诊断知识的自动获取。将该系统应用于汽车变速箱装配过程的检测与故障诊断,验证了方法的有效性。

模糊控制在现场总线控制系统中的应用

介绍了如何把模糊控制算法与现场总线中的CAN总线结合起来应用于控制系统 ,并设计了一种智能型模糊控制算法 ,给出了系统的整体结构和现场模糊控制单元的硬件实现电路及其软件设计思路 ;系统的仿真结果表明 ,该系统实时性好 ,控制精度较高 ,鲁棒性强 ,在现场控制中有效可行

基于MRF模型的油气储层属性随机建模方法研究

Stochastic reservoir modeling is a technique used in reservoir describing. Through this technique, multiple data sources with different scales can be integrated into the reservoir model and its uncertainty can be conveyed to researchers and supervisors. Stochastic reservoir modeling, for its digital models, its changeable scales, its honoring known information and data and its conveying uncertainty in models, provides a mathematical framework or platform for researchers to integrate multiple data sources and information with different scales into their prediction models. As a fresher method, stochastic reservoir modeling is on the upswing. Based on related works, this paper, starting with Markov property in reservoir, illustrates how to constitute spatial models for catalogued variables and continuum variables by use of Markov random fields. In order to explore reservoir properties, researchers should study the properties of rocks embedded in reservoirs. Apart from methods used in laboratories, geophysical means and subsequent interpretations may be the main sources for information and data used in petroleum exploration and exploitation. How to build a model for flow simulations based on incomplete information is to predict the spatial distributions of different reservoir variables. Considering data source, digital extent and methods, reservoir modeling can be catalogued into four sorts: reservoir sedimentology based method, reservoir seismic prediction, kriging and stochastic reservoir modeling. The application of Markov chain models in the analogue of sedimentary strata is introduced in the third of the paper. The concept of Markov chain model, N-step transition probability matrix, stationary distribution, the estimation of transition probability matrix, the testing of Markov property, 2 means for organizing sections-method based on equal intervals and based on rock facies, embedded Markov matrix, semi-Markov chain model, hidden Markov chain model, etc, are presented in this part. Based on 1-D Markov chain model, conditional 1-D Markov chain model is discussed in the fourth part. By extending 1-D Markov chain model to 2-D, 3-D situations, conditional 2-D, 3-D Markov chain models are presented. This part also discusses the estimation of vertical transition probability, lateral transition probability and the initialization of the top boundary. Corresponding digital models are used to specify, or testify related discussions. The fifth part, based on the fourth part and the application of MRF in image analysis, discusses MRF based method to simulate the spatial distribution of catalogued reservoir variables. In the part, the probability of a special catalogued variable mass, the definition of energy function for catalogued variable mass as a Markov random field, Strauss model, estimation of components in energy function are presented. Corresponding digital models are used to specify, or testify, related discussions. As for the simulation of the spatial distribution of continuum reservoir variables, the sixth part mainly explores 2 methods. The first is pure GMRF based method. Related contents include GMRF model and its neighborhood, parameters estimation, and MCMC iteration method. A digital example illustrates the corresponding method. The second is two-stage models method. Based on the results of catalogued variables distribution simulation, this method, taking GMRF as the prior distribution for continuum variables, taking the relationship between catalogued variables such as rock facies, continuum variables such as porosity, permeability, fluid saturation, can bring a series of stochastic images for the spatial distribution of continuum variables. Integrating multiple data sources into the reservoir model is one of the merits of stochastic reservoir modeling. After discussing how to model spatial distributions of catalogued reservoir variables, continuum reservoir variables, the paper explores how to combine conceptual depositional models, well logs, cores, seismic attributes production history.

管理心理学专家系统开发工具（ESBT－MP）研制原理与方法的探索

The principle and methods to develop the expert system building tool for managerial psychology are explored and the prototype of "ESBT-MP" (The Expert System Building Tool for Managerial Psychology) in this research is made.

Computer-Based Diagnostic Systems: Computer-Based Troubleshooting

ISBN: 3-540-76198-5 (out of print)

As neurotoxinas de clostridium sp.

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

Linking Visual Cortex to Visual Perception: An Alternative to the Gestalt Bubble

Lehar's lively discussion builds on a critique of neural models of vision that is incorrect in its general and specific claims. He espouses a Gestalt perceptual approach, rather than one consistent with the "objective neurophysiological state of the visual system" (p. 1). Contemporary vision models realize his perceptual goals and also quantitatively explain neurophysiological and anatomical data.

The use of fault detection and diagnostics to reduce air handling unit energy consumption

The contribution of buildings towards total worldwide energy consumption in developed countries is between 20% and 40%. Heating Ventilation and Air Conditioning (HVAC), and more specifically Air Handling Units (AHUs) energy consumption accounts on average for 40% of a typical medical device manufacturing or pharmaceutical facility’s energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning HVAC systems, and more specifically AHU operations, to rectify faulty operation. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with potentially partially or fully automating the commissioning process through the detection of faults. An expert system is a knowledge-based system, which employs Artificial Intelligence (AI) methods to replicate the knowledge of a human subject matter expert, in a particular field, such as engineering, medicine, finance and marketing, to name a few. This thesis details the research and development work undertaken in the development and testing of a new AFDD expert system for AHUs which can be installed in minimal set up time on a large cross section of AHU types in a building management system vendor neutral manner. Both simulated and extensive field testing was undertaken against a widely available and industry known expert set of rules known as the Air Handling Unit Performance Assessment Rules (APAR) (and a later more developed version known as APAR_extended) in order to prove its effectiveness. Specifically, in tests against a dataset of 52 simulated faults, this new AFDD expert system identified all 52 derived issues whereas the APAR ruleset identified just 10. In tests using actual field data from 5 operating AHUs in 4 manufacturing facilities, the newly developed AFDD expert system for AHUs was shown to identify four individual fault case categories that the APAR method did not, as well as showing improvements made in the area of fault diagnosis.

Improving supply chain performance: Real-time demand information and flexible deliveries

In some supply chains, materials are ordered periodically according to local information. This paper investigates how to improve the performance of such a supply chain. Specifically, we consider a serial inventory system in which each stage implements a local reorder interval policy; i.e., each stage orders up to a local basestock level according to a fixed-interval schedule. A fixed cost is incurred for placing an order. Two improvement strategies are considered: (1) expanding the information flow by acquiring real-time demand information and (2) accelerating the material flow via flexible deliveries. The first strategy leads to a reorder interval policy with full information; the second strategy leads to a reorder point policy with local information. Both policies have been studied in the literature. Thus, to assess the benefit of these strategies, we analyze the local reorder interval policy. We develop a bottom-up recursion to evaluate the system cost and provide a method to obtain the optimal policy. A numerical study shows the following: Increasing the flexibility of deliveries lowers costs more than does expanding information flow; the fixed order costs and the system lead times are key drivers that determine the effectiveness of these improvement strategies. In addition, we find that using optimal batch sizes in the reorder point policy and demand rate to infer reorder intervals may lead to significant cost inefficiency. © 2010 INFORMS.