用数据流思想开发故障诊断知识库

本文分析了目前在故障诊断专家系统知识库构造方面存在的问题，研究了大型旋转机械故障诊断领域知识的构成特点和表达形式。为了保证故障诊断知识库的通用性、管理与维护的方便性和可靠性，引入了面向数据流的软件设计思想，并利用这种思想构造了一个汽轮发电机组故障诊断专家系统的知识库管理系统。     

模具曲面机器人智能抛光系统的研究

介绍了一个初步实现的模具曲面机器人智能抛光系统的构成,分析了模具机器人抛光的特性,重点对实现机器人具智能抛光系统的若干问题诸如工艺过程建模、工艺知识的获取与表达、工艺知识库与数据库建立、智能工艺规划系统的构造以及抛光刀具轨迹自动生成等进行了研究。     

CAPP系统开发工具的研究

本文论述了构造CAPP系统开发工具的重要意义及其宗旨,给出了CAPP系统开发工具的逻辑结构和总体结构,并对CAPP系统开发工具的零件信息描述与输入、知识的表示与创成、知识库的建立、柔性推理机的设计、学习模型以及智纯接口的设计等问题作了分析和探讨,给出其设计策略和采取的相应措施。     

地球卫星遥感影像解译中国台湾地区的构造系统

运用区域地质调查资料和地球卫星遥感资料进行综合分析,发现并确定和划分了环形构造系统、北北东向构造系统、南北向构造系统、北东向构造系统和弧形构造系统等5套构造系统。采用结构面组合及配套的方法恢复重建构造演化序次和形成时期并讨论了地质发展过程等问题,为研究东亚构造域和板块运动以及大陆板内构造活动提供新信息。     

汽车发动机综合检测诊断系统

该系统以便携式工控机与卡式仪器相结合,利用各种传感器实时采集数据,配以专用测试诊断模块、自动测试诊断软件、故障专家知识库以及维修资源知识库等,结合人工神经网络和专家系统,从不同的角度、不同层次进行诊断推理并完成自学习功能.     

工程设计的专家系统

本文对人工智能和专家系统的发展概况、工程设计专家系统的基本组成、框图以及知识的描述和知识库的构造作了简要介绍,并讨论了一个简单的应用问题。     

基于I-deas的工装CAD系统中知识库系统的研究

论述了基于三维建模软件I-deas的工装CAD系统中工装知识库系统的结构、功能及其子库实现方法，分析了子库之间的相互关系。以开发的工装设计管理系统中工装知识库系统开发为例，描述了知识库系统与工装设计管理系统的集成。     

热障涂层知识库系统的设计和构建

设计并建立了热障涂层知识库系统,采用多用户的管理模式由知识库管理系统统管整个知识库系统.系统采用问答方式进行询问回答,并给出相应建议和具体的实例说明.建立了临时库,方便用户自行添加规则进行推理.     

一类基于认知心理特征的知识发现新模型

为克服数据挖掘过程中的"数据海量,算法复杂"的困扰,建立了两个用于在知识发现系统与过程中模拟认知心理特征的协调器--启发型协调器和维护型协调器,从而实现了系统自主地发现知识短缺和进行知识库的实时维护;创建了双库协同机制,它揭示了数据库与知识库在特定构造下,两个范畴间的等价关系(即结构对应定理);并将这两个协调器和双库协同机制融入经典的数据库中的知识发现(KDD)过程模型,诱导出新的知识发现过程模型--KDD和基于数据库和知识库双库数据挖掘(KD (D&K))过程模型,实现了"定向搜索"与"定向挖掘".最后通过实例验证了其有效性与先进性.     

CAPP专家系统中知识库设计方式初探

本文从BH—SIPP系统的设计为基础,就CAPP领域知识库的设计方法提出了一些看法,并对知识库的更新、恢复和共享等方面作了一些讨论。     

"岩石模型"虚拟仪器库中的自动拼搭系统

在分析“岩石模型”大型虚拟仪器库库中资源的基础上提出了一种可在该仪器库中实现虚拟仪器自动化拼搭的系统结构并给出了系统的工作流程。对此自动拼搭系统进行了方案设计,并对其决策控制环节、现有资源的分类管理模式和方法以及关系数据库和规则集的建立进行了研究。虚拟仪器的自动拼搭能极大程度地降低虚拟仪器的开发要求,并能对虚拟仪器的推广起到一定的促进作用。     

Test case of the long term preliminary performance assessment for the L&IL radioactive waste repository Baita Bihor, Romania

The paper presents the assessment methodology developed in the framework of the long-term preliminary performance assessment of Baita Bihor Romanian national low-level and intermediate-level radioactive waste repository. Conservative assumptions, input parameters and tools used in this approach reflect limitations imposed by the current assessment capability, as well as limited knowledge and understanding of the disposal system. The resultant dose rates are presented and analysed. Conclusions are drawn relating to the safety of the repository.     

Expert Diagnosing system for a Rotation Mechanism Based on a Neural Network

By combining the artificial neural network with the rule reasoning expert system,an expert diagnosing system for a rotation mechanism was established.This expert system takes advantage of both a neural network and a rule reasoning expert system;it can also make use of all kinds of knowledge in the repository to diagnose the fault with the positive and negative mixing reasoning mode.The binary system was adopted to denote all kinds of fault in a rotation mechanism.The neural networks were trained with a random parallel algorithm (Alopex).The expert system overcomes the self-learning difficulty of the rule reasoning expert system and the shortcoming of poor system control of the neural network.The expert system developed in this paper has power ful diagnosing ability.     

Review and perspectives on spallings release models in the 1996 performance assessment for the Waste Isolation Pilot Plant

The Waste Isolation Pilot Plant was licensed for disposal of transuranic wastes generated by the US Department of Energy. The facility consists of a repository mined in a bedded salt formation, approximately 650 m below the surface. Regulations promulgated by the US Environmental Protection Agency require that performance assessment calculations for the repository include the possibility that an exploratory drilling operation could penetrate the waste disposal areas at some time in the future. Release of contaminated solids could reach the surface during a drilling intrusion. One of the mechanisms for release, known as spallings, can occur if gas pressures in the repository exceed the hydrostatic pressure of a column of drilling mud. Calculation of solids releases for spallings depends critically on the conceptual models for the waste, for the spallings process, and assumptions regarding driller parameters and practices. This paper presents a review of the evolution of these models during the regulatory review of the Compliance Certification Application for the repository. A summary and perspectives on the implementation of conservative assumptions in model development are also provided.     

Probabilistic dose calculations and sensitivity analyses using analytic models

Newly developed analytic models mimic numerical models for radionuclide transport and dose calculations for a deep repository for spent nuclear fuel, reducing computation times more than three orders of magnitude. In this paper, the analytic models are used to extend preliminary probabilistic dose calculations reported in a recent performance assessment for a deep repository in Sweden. It is demonstrated that the analytic models are useful for gaining insights into the probabilistic properties of the system concerning, e.g. the importance of input variable correlations and various properties of input distributions. Regarding sensitivity analyses, the analytic model is used for screening out nuclides which do not influence the calculation end-point, for demonstrating monotonicity and for developing tailored regression models with non-linear expressions.     

Importance measures for nuclear waste repositories

Several importance measures are identified for possible use in the performance assessment of a high-level nuclear waste repository. These importance measures are based on concepts of importance used in system reliability analysis, but the concepts are modified and adapted to the special characteristics of the repository and similar passive systems. In particular, the importance measures proposed here are based on risk (in comparison to traditional importance measures which are based on frequency of failure) and are intended to be more suitable to systems comprised of components whose behavior is most easily and naturally represented as continuous, rather than binary. These importance measures appear to be able to evaluate systems comprised of both continuous-behavior and binary-behavior components. Three separate examples are provided to illustrate the concepts and behavior of these importance measures. The first example demonstrates various formulations for the importance measures and their implementation for a simple radiation safety system comprised of a radiation source and three shields. The second example demonstrates use of these importance measures for a system comprised of components modeled with binary behavior and components modeled with continuous behavior. The third example investigates the use of these importance measures for a proposed repository system, using a total system model and code currently under development. Currently, these concepts and formulations of importance are undergoing further evaluation for a repository system to determine to what degree they provide useful insights and to determine which formulations are most useful.     

MEMS版图自动生成与工艺匹配系统研究

根据MEMS工艺设计的特点提出了反馈式专家系统运作方式,并据此给出了MEMS版图自动生成与工艺匹配系统的体系结构.同虚拟MEMS加工工艺相比,该系统可实现工艺流水的逆向推理流程,由此,进一步给出了系统逆向推理所需的专家规则描述方式和推理机实现方法,并实现了一个原型系统,该系统可实现由两种标准MEMS工艺制作器件的版图自动生成与工艺匹配工作,初步验证了系统的可行性.     

一种基于生物免疫原理的入侵检测新模型

入侵检测系统可以从生物免疫系统的很多特点中得到启发，文中利用生物免疫原理设计了一个新的入侵检测框架模型，该框架在传统信息传输网基础上构建了免疫淋巴网，用来监控和管理传统传输网的行为。模型中还应用了阴性选择、克隆选择等免疫算法，使得该模型对于入侵检测问题有较好的敌我识别功能。     

专家系统在精馏塔故障诊断中的应用

精馏是空气分离过程中非常重要的一步。简单介绍了精馏塔故障诊断的必要性,主要阐述了专家系统的具体实现,包括知识库、推理机、人机界面等。将故障诊断技术和专家系统结合起来,能够有效的预防和避免事故,这将是故障诊断的发展趋势。     

SMINER: Detecting Unrestricted and Misimplemented Behaviors of Software Systems Based on Unit Test Cases

Despite the advances in automated vulnerability detection approaches, security vulnerabilities caused by design flaws in software systems are continuously appearing in real-world systems. Such security design flaws can bring unrestricted and misimplemented behaviors of a system and can lead to fatal vulnerabilities such as remote code execution or sensitive data leakage. Therefore, it is an essential task to discover unrestricted and misimplemented behaviors of a system. However, it is a daunting task for security experts to discover such vulnerabilities in advance because it is time-consuming and error-prone to analyze the whole code in detail. Also, most of the existing vulnerability detection approaches still focus on detecting memory corruption bugs because these bugs are the dominant root cause of software vulnerabilities. This paper proposes SMINER, a novel approach that discovers vulnerabilities caused by unrestricted and misimplemented behaviors. SMINER first collects unit test cases for the target system from the official repository. Next, preprocess the collected code fragments. SMINER uses pre-processed data to show the security policies that can occur on the target system and creates a test case for security policy testing. To demonstrate the effectiveness of SMINER, this paper evaluates SMINER against Robot Operating System (ROS), a real-world system used for intelligent robots in Amazon and controlling satellites in National Aeronautics and Space Administration (NASA). From the evaluation, we discovered two real-world vulnerabilities in ROS.