遗传神经网络故障诊断自适应Petri网模型

研究故障诊断优化问题。针对传统Petri网难以精确地描述故障现象和故障原因之间的复杂关系,造成故障诊断难以精确,提出了将遗传算法、神经网络和传统Petri网模型结合,形成了一种改进的自适应的加权Petri网模型以及模型的构造算法,同时在此基础上,采用改进的遗传算法对神经网络模型的权值进行优化训练,并给出了采用构造的自适应模糊Petri网模型对故障进行诊断的具体步骤。仿真实例验证了算法的有效性,对柔性制造系统实例的故障进行诊断,验证了此自适应的加权模糊Petri网模型结合了Petri网和遗传算法的优点,具有很强的故障推理能力以及自适应能力,能有效地对故障进行诊断。     

FMS工作流故障诊断自适应加权模糊Petri网模型

研究了使用人工神经网络和加权模糊Petri网对故障进行诊断的方法。针对传统Petri网难以精确地描述故障现象和故障原因之间的复杂关系,将人工神经网络、模糊逻辑和传统Petri网模型结合,定义了一种自适应的加权模糊Petri网模型以及模型的构造方法,在此基础上,提出了一种使用改进的BP算法对模型的权值进行训练的方法,并给出了采用构造的自适应模糊Petri网模型对故障进行诊断的具体步骤。最后对柔性制造系统(FMS)实例的故障进行诊断,验证了此自适应的加权模糊Petri网模型结合了Petri网和人工神经网络的优点,具有很强的故障推理能力以及自适应能力,能有效地对故障进行诊断。     

基于BP算法和Petri网的柔性制造系统故障诊断

针对传统Petri网难以精确描述故障发生的不确定性以及缺乏学习能力的缺点,将BP神经网络和加权模糊Petri网相结合,定义了一种新的能对故障进行诊断的模型——BPFPN网(A net based on BP and FPN),并提出了对BPFPN网故障诊断模型进行构造的算法,以及一种将BP神经网络算法应用于BPFPN网故障诊断模型实现对各种参数进行训练的方法;最后通过对实验参数为=5000,算法学习速率η=0.05,学习误差Δe=0.0002的柔性制造系统加工中心故障诊断实例进行实验,在对各种参数进行学习后,能够有效地实现对故障的诊断,证明了BPFPN网是一种有效的故障诊断方法。     

基于ACO优化参数的模糊Petri网故障诊断技术研究

针对传统模糊Petri网在进行故障诊断推理时,需要依靠专家经验给出所有产生式规则的参数,使得故障诊断的精确度受限于专家知识水平的问题,提出了一种加权模糊神经Petri网模型以及相应的构造方法,此方法使用模糊Petri网进行故障诊断,网模型中各参数由BP神经网络训练而得,为了进一步提高诊断精确度,定义了使用ACO (Ant Colony Optimization)对网模型的各参数进行优化的算法;最后通过发电机故障诊断实例对比试验,验证了文中ACO优化的模糊神经Petri网,能够对各种故障进行正确的诊断,且在诊断精度和效率上较常规的模糊神经Petri网有了很大的提高,具有很强的实用性和可行性.     

基于模糊Petri网和状态监测的井下水泵故障诊断

为了快速找到井下水泵故障的原因,建立了一种基于模糊Petri网和状态监测的井下水泵故障诊断模型。首先通过井下排水设备状态监测系统测得水泵故障的振动信号,经过振动分析后,对获得的水泵故障样本进行学习训练;然后在水泵故障诊断的模糊Petri网模型结构上,引入神经网络中的BP算法对权值、阈值和置信度等参数进行网络优化训练。实例分析结果表明,该模型能较准确地找到水泵故障原因,具有较好的准确性、快速性和适应性。     

基于模糊Petri网的高炉故障诊断系统

采用模糊神经Petri网专家系统来对高炉进行故障诊断,结合神经网络自适应、自学习和模糊控制逻辑推理强、能够表达模糊语义的优点,建立了一种模糊神经Petri网故障诊断模型;针对高炉故障特点对先兆预测分析原理进行了分析研究,提出了自己的设计方法;在分析模糊Petri网及神经网络的优点的基础上,构建了基于模糊神经Petri网的专家诊断系统,通过测试风量,风压,喷吹量,炉顶温度,炉身温度,透气性指数得到诊断结果,使得诊断推理与网络学习更为完善,并运用VC++6.0中MFC功能设计了一套与前面诊断系统相对应的仿真程序,证明了该诊断模型的可行性。     

基于AFPN的舰船电子综合化系统总线故障诊断研究

针对舰船电子综合化系统总线故障诊断模糊性、不确定性的日益增强,且难以实现快速故障诊断的难题,提出一种基于自适应模糊Petri网(Adaptive Fuzzy Petri Net,AFPN)的舰船电子综合化系统总线故障诊断方法;在加权模糊Petri网(Weighted Fuzzy Petri Net,WFPN)的基础上,引入神经网络技术,给出了AFPN的形式化定义及学习算法;实例分析验证了所提方法的有效性,研究表明:AFPN模型具有很强的自适应能力和推理能力,克服了传统单纯依靠人工经验故障诊断的不确定性和偶然性,可以实现舰船电子综合化系统总线快速精确的故障诊断。     

一种自适应模糊Petri网及其应用*

模糊Petri网(fuzzy Petri nets, FPN)是基于模糊产生式规则的知识库系统的有力建模工具,但其缺乏较强的自学习能力。在FPN的基础上引入神经网络技术,给出了一种自适应模糊Petri网(adapt fuzzy Petri nets, AFPN)模型。该模型将神经网络中的BP网络算法引入到FPN模型中,对FPN中的权值进行反复的学习训练,避免了依靠人工经验设置带来的不确定性。AFPN具有很强的推理能力和自适应能力,对知识库系统的建立、更新和维护有着重要的意义。     

基于模糊神经Petri网的故障诊断模型

Petri网是对具有产生式规则的故障诊断系统的有力建模工具，但其缺乏较强的学习能力．本文以Petri网的基本定义为基础，结合模糊逻辑和Petri网模型，定义了模糊Petri网模型，在此基础上引入人工神经网络技术，给出了人工神经网络的模糊Petri网表示方法，并针对工程机械故障诊断异步、离散等特点，提出并建立了故障诊断的模糊神经Petri网模型及其改进模型．基于模糊神经Petri网的故障诊断系统结合了Petri网和人工神经网络的优点，经过自学习后同时具有很强的推理能力和自适应能力．     

改进BP网络在汽轮发电机组故障诊断中的应用

关于汽轮发电机系统一定要保证可靠安全.研究汽轮机发电机组的故障快速诊断问题上,针对汽轮发电机故障具有多样性和不确定性,传统BP神经网络不能很好的识别这种特性,存在训练时间长、误差收敛速度慢的缺陷,故障诊断正确率低.为了提高汽轮发电机组的故障诊断准确率,提出一种附加动量法和自适应速率相结合的BP神经网络故障诊断模型.采用附加动量调整了BP神经网络的权值,加快了网络的收敛速度,用自适应速率动态地调整了学习速度,减少了迭代次数,最后利用得到的BP神经网络对故障进行了诊断.在matlab上采用实测汽轮发电机故障数据对故障诊断模型进行测试,相对于传统的BP算法,该算法不仅迭代次数少、学习速度加快,而且故障诊断准确率高.结果表明,有效地克服了传统的梯度下降的BP算法的缺陷,诊断结果可为保证汽轮发电机安全运行提供保障.     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.