A genetic algorithm approach to the multiple machine tool selection problem

A number of earlier researches have emphasized the on-the-job scheduling problems that occur with a single flexible machine. Two solutions to the problem have generally been considered; namely minimization of tool switches and minimization of tool switching instances. Methods used to solve the problems have included KTNS heuristic, dual-based relaxation heuristic, and non-LP-based branch-and-bound methods. However, scant literature has considered the case of job scheduling on multiple parallel machines which invokes another problem involving machine assignment. This paper addresses the problem of job scheduling and machine assignment on a flexible machining workstation (FMW) equipped with multiple parallel machines in a tool-sharing environment. Under these circumstances, the authors have attempted to model the problem with the objective of simultaneously minimizing both the number of tool switches and the number of tool switching instances. Furthermore, a set of realistic constraints has been included in the investigation. A novel genetic algorithm (GA) heuristic has been developed to solve the problem, and performance results show that GA is an appropriate solution.     

基于有限元的电容临近传感器研究

建立了电容临近传感器的三维仿真数学模型,用FEA对不同参数的传感器进行了仿真,比较分析了被测物距离、电极宽度、电极长度间隙比等对传感器灵敏度的影响,并与理论计算进行比较,结果表明:测量系统的灵敏度与电极宽度和电极长度间隙比近似成正比,与被测物距离近似成反比.该研究对电容临近传感器的结构设计有指导意义.     

A hybrid fuzzy MCDM approach to machine tool selection

The selection of the appropriate machine tools for a manufacturing company is one of the important points to achieving high competitiveness in the market. Besides, an appropriate choice of machine tools is very important as it helps to realize full production quickly. Today’s market offers many more choices for machine tool alternatives. There are also many factors one should consider as part of the appropriate machine tool selection process, including productivity, flexibility, compatibility, safety, cost, etc. Consequently evaluation procedures involve several objectives and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision making (MCDM) has been found to be a useful approach to solve this kind of problem. Most of the MCDM models are basically mathematical and ignore qualitative and often subjective considerations. The use of fuzzy set theory allows incorporating qualitative and partially known information into the decision model. This paper describes a fuzzy technique for order preference by similarity to ideal solution (TOPSIS) based methodology for evaluation and selection of vertical CNC machining centers for a manufacturing company in Istanbul, Turkey. The criteria weights are calculated by using the fuzzy AHP (analytical hierarchy process).     

A monitor tool for a network based on the cambridge ring

An evolving network is subject to technological advances and increasing user demands through out its lifetime. Continuous monitoring is therefore required to understand its behaviour in the operational environment and to provide an aid to planning. A monitor tool has been developed to meet such requirements in a heavily used service network. A decentralized but integrated approach has been adopted. An active collection allows accumulated measurements to be retrieved. The measurements required are determined and the constraints imposed by existing mechanisms and the methods chosen are discussed. Flexible user facilities are available to allow selected measurements to be collected and displayed, and these are described. Daily sessions of network-wide monitoring have been undertaken. The overhead incurred is quantified. The sessions revealed communications software errors and anomalous behaviour of a network node. Further analysis shows the symptoms of the latter, the result of a hardware fault. Enhancements which would increase the flexibility of the tool are also suggested.     

基于MEMS的微型手术器中的传感器

基于MEMS的微型手术器是一种可用于微创手术的新型医疗器械。这种手术器实际上是一种微型智能机器人 ,其中的传感器采用MEMS技术制造 ,具有微型、机电一体化集成、智能等特点。介绍了国际上具有代表性的微型手术器及其所采用的新传感技术 ,并探讨了这些传感器的发展和应用前景。     

Computers and the Internet as a job assisted tool: based on the three-tier use model approach

Personal attitudes are a major factor to affect individual information technology usage. The purpose of this study is to explore the role of individual attitudes toward computers and the Internet usage for assisting job performance. This research applies the 3-TUM approach to understand individual attitudes toward computers and the Internet usage. After statistical analysis, the results provide a support that the 3-TUM is appropriate model for investigating faculty and staff perceptions toward computers and Internet. In addition, the results also support that using computers and the Internet may assist individual job performance. Furthermore; this study offer evidence that when individuals have more self-efficacy and feel computers and the Internet are more useful, then they have more behavioral intention to use and learn computers and the Internet for assisting their job performance.     

A program design language based software maintenance tool

Program design languages are an increasingly important method of expressing the detailed design of a software system. Such languages can be modelled using a data structure known as a semantic net. This paper describes a maintenance tool for program design languages based on such a data structure. The tool allows the user to interrogate a semantic net using an interactive procedural language in order to derive information necessary for software maintenance. The technique upon which this tool is based is applicable to the maintenance of activities throughout the software lifecycle.     

基于检修标准化的输电线路工器具配置系统

通过介绍输电线路安全运行的重要性,分析目前输电线路配置检修工器具的局限性。依据检修作用标准化分析了在复杂环境温度、风速、覆冰情况下检修/更换直线塔和耐张塔绝缘子串及金具类设备的工器具标准化配置的方法。运用Microsoft Visual Studio 2010开发环境下的C#和SQL Server 2008数据库设计开发了输电线路工器具智能配置系统,系统主要由用户管理、系统配置管理、工器具全生命周期管理和系统设置与维护组成,系统将弱化检修工器具配置对工作负责人的依赖,实现工器具配置的标准化、模块化、智能化作业,提高巡检作业的质量和科学管理技术水平。     

一种基于累积误差控制的RTC补偿算法及电路

介绍了晶体振荡器的温漂特性,提出了基于累积误差控制的RTC温度补偿算法,累积频率误差控制在15.3 ppm以内。设计了应用于微控制器中的RTC补偿电路,开发了自动调教电路,能很好地满足智能电表高精度、低功耗的计时要求。     

An agent-based approach to tool integration

Tool integration is a very difficult challenge. Problems may arise at different abstraction levels and from several sources such as heterogeneity of manipulated data, incompatible interfaces, or uncoordinated services, to name just a few examples. On the other hand, applications based on the coherent composition of activities, components, services, and data from heterogeneous sources are increasingly present in our everyday lives. Consequently, tool integration takes on increasing significance.In this paper we analyze the tool-integration problem at different abstraction levels and discuss different views on a layered software architecture that we have designed specifically for a middleware that supports the execution of distributed applications for the orchestration of human/system activities. We noticed that the agent paradigm provided a suitable technology for abstraction in tool integration. Throughout the paper, the discussion refers to a case study in the bioinformatics domain.     

一种基于温补时钟芯片的授时系统

针对传统天文测量授时系统结构复杂、操作繁琐、便携性差等缺点,研究开发了一种基于DS12C887温补时钟芯片的功耗低、体积小且携带方便的天文授时系统。简要介绍了系统的基本构成和主要部件的功能特性及各种参数。介绍了授时系统的计时原理和工作流程,介绍了授时系统比时平台的构成以及比时的基本原理。做了大量的实验测试,分析了授时系统的稳定性和精度,收集了22d的时间比对实验数据。经实验验证,授时系统计时精度高,运行稳定,自动化程度高,可方便运用于野外天文测量与其他时间服务。     

基于特征补偿的单目标跟踪算法

为适应长期跟踪的需求,提出一种基于特征补偿的单目标跟踪方法。通过分析现有算法的优缺点,使用低层特征的相关滤波模型完成简单场景的任务,以保证速度;使用高层语义特征的卷积神经网络模型完成复杂场景的任务,以提升精度和鲁棒性;引入一个简单的分类器,作为切换特征的标志,有选择的对模型的模版进行更新,降低累计误差。结合实例验证了算法的有效性,在保证较快速度的同时,精度和鲁棒性均有较高的提升。     

Off-line compensation of the tool path deviations on robotic machining: Application to incremental sheet forming

In this paper, a coupling methodology is involved and improved to correct the tool path deviations induced by the compliance of industrial robots during an incremental sheet forming task. For that purpose, a robust and systematic method is first proposed to derive the elastic model of their structure and an efficient FE simulation of the process is then used to predict accurately the forming forces. Their values are then defined as the inputs of the proposed elastic model to calculate the robot TCP pose errors induced by the elastic deformations. This avoids thus a first step of measurement of the forces required to form a test part with a stiff machine. An intensive experimental investigation is performed by forming a classical frustum cone and a non-symmetrical twisted pyramid. It validates the robustness of both the FE analysis and the proposed elastic modeling allowing the final geometry of the formed parts to converge towards their nominal specifications in a context of prototyping applications.     

A method of illumination compensation for human face image based on quotient image

Illumination variation is one of the critical factors affecting face recognition rate. A novel approach for human face illumination compensation is presented in this paper. It constructs the nine-dimension face illumination subspace based on quotient image. In addition, with the aim to improve algorithm efficiency, a half-face illumination image is proposed and the low-dimension training set of the face image under different illumination conditions are obtained by means of PCA and wavelet transform. After processing, two different illumination compensation strategies are given: one is adding light, and the other is removing light. Based on the illumination compensation strategy, we implement the typical illumination sample image synthesis and the standard illumination sample image synthesis on a PCA feature subspace and a wavelet transform subspace, respectively, and the illumination compensation of the gray images and the color images are further realized. Experimental results based on the Yale Face Database B, the Extended Yale Face Database B and the CAS-PEAL Face Database indicate that execution time after compensation is approximately half the time and face recognition rate is improved by 20% compared with that of the original images.     

基于FLNN的加速度传感器动态特性补偿方法

对加速度传感器动态性能进行分析,提出其动态性能补偿的神经网络方法,介绍了补偿原理以及神经网络算法,给出用函数连接型神经网络建立的加速度传感器动态补偿网络的数学模型。结果表明:这种补偿模型精度高、能实现在线修正,有良好的鲁棒性及动态补偿器实现简单等优点。     

基于小波商图像的人脸光照补偿

复杂光照条件下的人脸识别是一个困难但需迫切解决的问题,为此提出了一种有效的光照补偿算法.该方法根据人脸光照线性变换子空间理论--商图像理论,构造了小波低维训练集,实现了对待识别图像的光照条件估计,并且通过加光和去光策略增强了光照补偿效果.与传统商图像理论相比,该方法利用小波分解,提高的算法执行效率,实验结果表明,该算法以较小的代价取得了较高的识别性能.     

基于视觉的刀具参数高精度测量

为满足现代制造业对刀具几何参数快速、高精度的测量要求,用高速CCD摄像机、远心镜头及可调的LED光源搭建刀具图像的采集系统,且在VS2010平台上用简单高效的C#语言开发基于机器视觉的具有可视化快速调焦功能的刀具几何测量系统。采用亚像素边缘提取法精准定位刀具边缘,设计一个快速调焦提示法。实验结果表明,该测量系统重复测量精度不超过2μm,速度快,鲁棒性好,极大提高了需要预知刀具参数来控制刀具运动轨迹的数控机床和加工中心的工作效率和加工质量。     

Error compensation in machine tools: a neural network approach

For a non-idealized machine tool, each point in the workspace is associated with a tool point positioning error vector. If this error map can be determined, then it is possible to substantially improve the positioning performance of the machine by introducing suitable compensation into the control loop. This paper explores the possibility of using an artifical neural network (ANN) to compute this mapping. The training set for the ANN is obtained by mounting a physical artifact whose dimensions are precisely known in the machine's workspace. The machine, equipped with a touch trigger probe, measures the positions of features on the artifact. The difference between the machine reading and the known dimension is the machine error at that point in the workspace. Using standard modeling techniques, the kinematic error model for a CNC turning center was developed. This model was parameterized by measurement of the parametric error functions using a laser interferometer, electronic levels and a precision square. The kinematic model was then used to simulate the artifact-measuring process and develop the ANN training set. The effect of changing artifact geometry was explored and a machining operation was simulated using the ANN output to provide compensation. The results show that the ANN is capable of learning the error map of a real machine, and that ANN-based compensation can significantly reduce part-dimensional errors.     

NTC热敏电阻器分段多项式拟合非线性补偿

NTC热敏电阻器的非线性影响到它的测温准确度和测温范围,介绍了利用分段多项式拟合法对其非线性进行补偿来减小非线性误差,提高测量准确度和量程,并通过实例对该方法进行分析和对比。实验表明:在-30~110℃温度范围内,应用该方法补偿后的测量误差小于±0.4℃。     

A process-control and diagnostic tool based on continuous fuzzy Petri nets

The use of Petri nets and fuzzy logic in intelligent process control has caught the attention of many researchers. In this paper, a Continuous Fuzzy Petri Net (CFPN) tool which integrates the three technologies of fuzzy control, Petri nets and real-time expert systems is presented. The CFPN approach can deal with real-time continuous inferencing, for the purpose of process monitoring and diagnostics, at a high level in the presence of uncertainty. This tool has been implemented in the G2 real-time expert-system environment and is currently being used by ESSO Canada.