Expert system based controller for the high-accuracy automatic assembly of vehicle headlamps

A vehicle headlamp is a high-sophisticated device basically composed of three elements: housing, lighting system and lens. Nowadays, they are assembled with no dimensional control, obtaining a final product with high physical deviations. Since the car manufacturer is requiring more and more precision, the number of faulty headlamps is increasing, and thus the cost to the headlamp producer. To solve this problem, a new automatic assembly machine was built. It integrated different technologies such as sensor systems, linear actuators and computational capacities.This work presents the conception, design and development of a fuzzy control algorithm for an automatic machine capable of correcting the dimensional tolerances of vehicle headlamps during its assembly process. Particularly, this paper describes the problem of modeling and control an industrial system, with a high complex dynamics and unknown model, by a rule-based model constructed from measured data.To validate the proposed control system, different experimental tests were carried out in both the lab and the assembly line in the factory. The obtained results show how the prototype, together with the proposed fuzzy software, solve the problem of assembling vehicle headlamps obtaining a final product with minimum dimensional errors.     

基于Web的手套机工业物联网平台设计与开发

针对手套机生产过程的远程监控管理、大数据处理和数据可视化问题,设计与开发了一款基于Web的手套机工业物联网平台。平台与物联网体系相结合,实现人员基础信息管理、手套机设备运行监控、报警推送、程序远程更新升级和生产数据统计分析等功能。采用Socket完成端口模型和线程池技术设计通信服务程序,解决了大量手套机通过WIFI无线通信方式传输的高并发数据处理问题。经测试,该平台界面美观,操作方便,实时性强,实现了在高并发网络连接情况下的稳定运行,CPU使用率低于6.03%,内网环境每秒能处理80.9个HTTP请求,外网环境每秒能处理24.9个HTTP请求,达到车间生产要求。该平台为智能手套机远程监控管理的开发与应用提供较好的参考价值。     

Cyber physical process monitoring systems

Manufacturing process monitoring systems is evolving from centralised bespoke applications to decentralised reconfigurable collectives. The resulting cyber-physical systems are made possible through the integration of high power computation, collaborative communication, and advanced analytics. This digital age of manufacturing is aimed at yielding the next generation of innovative intelligent machines. The focus of this research is to present the design and development of a cyber-physical process monitoring system; the components of which consist of an advanced signal processing chain for the semi-autonomous process characterisation of a CNC turning machine tool. The novelty of this decentralised system is its modularity, reconfigurability, openness, scalability, and unique functionality. The function of the decentralised system is to produce performance criteria via spindle vibration monitoring, which is correlated to the occurrence of sequential process events via motor current monitoring. Performance criteria enables the establishment of normal operating response of machining operations, and more importantly the identification of abnormalities or trends in the sensor data that can provide insight into the quality of the process ongoing. The function of each component in the signal processing chain is reviewed and investigated in an industrial case study.     

海洋工程水池造波机远程测控系统造波数据处理

本文介绍了海洋工程水池造波机远程测控系统的造波数据处理方法。为实现造波机的远程测控要求,造波数据必须通过远程计算机下载到就地PLC,快速输出控制造波机造波。测控系统通过嵌入VB编程辅助控制,解决了Wincc组态监控与PLC控制的高速数据传输瓶颈问题,实施后运行验证,研制的系统既满足高可靠性,又达到了造波的快速响应性。     

ZigBee 技术在城市照明监控系统中的应用

为了方便有效地对城市照明设施进行监测和控制,采用CC2530芯片构成网络节点,将ZigBee技术应用到照明监控系统中。主要阐述了所设计的照明监控系统的ZigBee网络的拓扑结构设计,路由设计,网络实现等方面内容。实践表明采用了该ZigBee网络的照明监控系统具有覆盖范围广、成本低、体积小、效率高等诸多优点。     

基于彩色图像处理的西红柿品质特征的提取研究

用机器视觉系统判别西红柿品质是否有效 ,关键在于能否真实地提取特征参数 .由于西红柿果实存在新陈代谢且表面非常光滑 ,使机器视觉系统采集图像时受环境温度和光线的影响很大 .同时 ,很难直接从采集到的RGB彩色图像中提取有效的品质特征参数 .为此 ,本论文基于彩色图像处理技术把 RGB彩色图像转换为 L* a* b*模式的彩色图像 ,然后提取西红柿品质特征参数 ,试验结果验证采用这种特征提取法提取的西红柿品质特征参数基本上不受照明强度的影响     

助航灯光单灯监控系统的数据传输设计与实现

针对助航灯光单灯监控系统数据传输存在的问题,提出了基于无线传感网络技术和GPRS/GSM技术的综合通讯方案。对系统组成中的微处理器、射频模块、GPRS/GSM模块硬件进行了介绍,重点阐述了通讯模块软件的设计以及监控系统平台的搭建.该系统实现了助航灯巡检自动化,可以实时监控灯光设备运行状况。对通讯中关键技术一点对多点通信进行了讨论。测试结果表明,系统能够稳定可靠进行数据传输,满足了机场对助航灯自动巡检要求。 基于无线通信技术的助航灯光单灯监控系统能够增强机场地面保障能力。     

基于Modbus协议的定量装车控制系统设计

根据定量装车过程中复杂的工艺参数监视和设备控制问题,提出了一种基于Modbus协议的自动监控系统。实现上位机服务端与上位机客户端之间的数据通讯,以及上位机客户端与下位机之间的监控。主要介绍了该系统的软件部分的设计和实现,并完整阐述了Modbus协议命令的实现。     

CS5460A在路灯单灯监控系统中的应用

为了更精确地对城市的路灯进行智能监控,采用CS5460A及MC13213组成单灯测控节点,将ZigBee技术应用到照明监控系统中去。详细论述了单灯测控系统的设计过程及CS5460A的编程配置。系统具有电路简单、体积小、功耗低、精度高、成本低等特点,具有较高的实用价值。     

HISYCOL a hybrid computational intelligence system for combined machine learning: the case of air pollution modeling in Athens

The analysis of air quality and the continuous monitoring of air pollution levels are important subjects of the environmental science and research. This problem actually has real impact in the human health and quality of life. The determination of the conditions which favor high concentration of pollutants and most of all the timely forecast of such cases is really crucial, as it facilitates the imposition of specific protection and prevention actions by civil protection. This research paper discusses an innovative threefold intelligent hybrid system of combined machine learning algorithms HISYCOL (henceforth). First, it deals with the correlation of the conditions under which high pollutants concentrations emerge. On the other hand, it proposes and presents an ensemble system using combination of machine learning algorithms capable of forecasting the values of air pollutants. What is really important and gives this modeling effort a hybrid nature is the fact that it uses clustered datasets. Moreover, this approach improves the accuracy of existing forecasting models by using unsupervised machine learning to cluster the data vectors and trace hidden knowledge. Finally, it employs a Mamdani fuzzy inference system for each air pollutant in order to forecast even more effectively its concentrations.     

注塑生产中残留物监测系统的研究

将设计一种将摄像头应用于注塑机残留物的监测中.该系统能够通过摄像头去采集注塑现场的信息,利用单片机微处理系统对采集的图像数据进行实时地处理,最后达到自动地去控制注塑机的运转功能,提高注塑机的自动化程度.主要结合了图像处理算法和单片机的优点,并进行不断地优化系统.试验结果表明该系统能够实时高效地进行自动监测.     

Scheduling unrelated parallel batch processing machines with non-identical job sizes

Scheduling unrelated parallel batch processing machines to minimize makespan is studied in this paper. Jobs with non-identical sizes are scheduled on batch processing machines that can process several jobs as a batch as long as the machine capacity is not violated. Several heuristics based on best fit longest processing time (BFLPT) in two groups are proposed to solve the problem. A lower bound is also proved to evaluate the quality of the heuristics. Computational experiments were undertaken. These showed that J_SC-BFLPT, considering both load balance of machines and job processing times, was robust and outperformed other heuristics for most of the problem categories.     

自确认金属氧化物半导体气体传感器阵列及其应用研究

金属氧化物半导体(MOS)气体传感器阵列是机器嗅觉系统中获取目标气体信息的重要装置.由于气敏元件的材料特性,MOS气体传感器阵列在工作过程中不可避免地会发生突发故障及外界干扰,导致机器嗅觉系统的检测与分析性能下降.为了提升机器嗅觉系统的可靠性,在总结以往研究成果的基础上,提出了自确认MOS气体传感器阵列.该气体传感器阵列结合自确认传感器技术,能够实现自身的多故障检测与隔离、故障识别、故障恢复及测量质量评估等自确认功能.本文分别探讨了自确认MOS传感器阵列的硬件架构、功能模型及其关键技术.最后,介绍了一种面向大气环境污染气体监测的自确认MOS传感器阵列,实现了其异常状态监测与测量质量评估并对其有效性进行了验证.     

基于监控大数据平台上的人工智能应用总体设计

针对电网监控业务管理中存在系统运行复杂、日常工作繁杂、管理难度高和人员培训难度大等难题,本文设计了一套基于大数据平台的人工智能电网监控管家管理系统,系统中引入了监控人工智能,通过智能交互中心、智能监视中心和智慧处理中心三大技术实现了系统的全过程设备维护、智能巡检、行为监管、智能提醒服务、记录信息错误提醒、监控信号异常缺陷处置、智能交互、设备信息调试全过程管控、遥控防误操作和人员培训评价,全方位掌握监控人员工作的规范性,对履职能力进行分析评价,提出提升和改进建议,同时系统融入了智能语音处理相互技术、智能图像识别技术、专家库技术,实现技术突破,提高了工作效率,建立了监控信息分析,优化了工作模式、增强了专业管理,为监控工作的顺利、高效完成奠定坚实基础。     

基于机器视觉的工业巡检过程监控分析系统

工业巡检中人员的行为与生产安全息息相关,有关巡检监测方法的设计成为了研究热点.针对目前巡检监控分析依赖于人工判断且精度低的问题,本文提出了一种基于机器视觉的工业现场巡检过程监控分析系统.首先利用YOLOv3网络对将视频流中的人员进行检测,根据检测结果,使用人员行为分析方法,剔除场景内干扰并获取巡检人员真实的行为信息,最后根据人员行为信息对巡检过程进行评估,将评估结果存储至数据库同时发布至网页.本文使用多个监控视角的视频进行实验,实验结果表明,本文所提系统在复杂环境下,能够准确检测巡检人员并分析其行为,同时满足实时处理的需求.本文可以为工业巡检的智能化监测提供参考.     

恶劣光照下驾驶人疲劳及注意力视觉监测算法

驾驶人驾驶行为监测及预警系统对于提高行车安全性及降低交通事故等问题具有重要作用,而利用机器视觉对驾驶人疲劳状态及注意力状态进行监测和分析是安全辅助驾驶领域内的研究热点之一。机器视觉受光照条件影响非常严重,甚至直接影响到图像处理算法的可靠性。在弱光和强光两种特殊照明条件下,介绍了驾驶人疲劳状态的检测思路,提出利用普尔钦斑点及投影曲线极点位置分割面部器官独立区域,最终获得眼睛的轮廓状态,利用PERCLOS判断驾驶人的疲劳状态。在驾驶人面部及面部器官定位的基础上,对驾驶人的头部旋转运动进行分析,提出了计算驾驶人头部旋转角度的计算方法,以驾驶人头部旋转角度为依据判断驾驶人的注意力是否分散。实践证明,在弱光和强光两种特殊照明条件之下,算法实时性好,准确率较高,效果非常理想,能够为驾驶人疲劳状态及注意力状态分析提供较为准确的依据。     

Data-Enabled Modeling and Analysis of Multistage Manufacturing Systems with Quality Rework Loops

In a multistage serial production line, multiple inspection stations and repair processes are typically involved to ensure high product quality. Quality rework is the activity to repair or repeat the work on the defect parts during manufacturing processes. The rework process after each inspection can add cost and cycle time to the normal process and impose negative impact on the throughput. This paper studies real-time performance of multistage serial manufacturing systems with quality rework loops and machine random failures. A production line with multiple quality rework loops is first unify by segmenting it into a set of serially connected quality rework loops. An event-based data-enabled mathematical model is developed to evaluate real-time production rate of each machine for such a system. In addition, the system properties are analyzed and permanent production loss due to quality rework loops and random machine failures are identified respectively. The permanent production loss attribution to each disruption event and machine can be used as real-time performance indicators to diagnose production system inefficiency. The mathematical model and system performance identification methodology are studied analytically and validated through numerical case studies.     

种子自动数粒仪

本文介绍一种利用机器视觉技术研究开发的种子自动数粒仪 ,该系统基于美国NI公司的软件开发平台LabView 7.1和图像处理软件包IMAQVISION及IMAQPCI -14 11图像采集卡进行软硬件的开发。系统在硬件结构上主要包括电磁震动工作台、摄像机及灯光、图像采集卡、PC机 ;在软件上主要包括图像采集模块、图象处理模块、图像分析模块。试验结果表明 ,该系统操作简单 ,效率高 ,并解决了其他数种仪器对种子大小有要求的弊端。     

An improved heuristic for parallel machine weighted flowtime scheduling with family set-up times

This paper studies the identical parallel machine scheduling problem with family set-up times and an objective of minimizing total weighted completion time (weighted flowtime). The family set-up time is incurred whenever there is a switch of processing from a job in one family to a job in another family. A heuristic is proposed in this paper for the problem. Computational results show that the proposed heuristic outperforms an existing heuristic, especially for large-sized problems, in terms of both solution quality and computation times. The improvement of solution quality is as high as 4.753% for six-machine problem and 7.822% for nine-machine problem, while the proposed heuristic runs three times faster than the existing one.     

Force-torque based on-line tool wear estimation system for CNC milling of Inconel 718 using neural networks

In a modern machining system, tool condition monitoring systems are needed to get higher quality production and to prevent the downtime of machine tools due to catastrophic tool failures. Also, in precision machining processes surface quality of the manufactured part can be related to the conditions of the cutting tools. This increases industrial interest for in-process tool condition monitoring (TCM) systems. TCM supported modern unmanned manufacturing process is an integrated system composed of sensors, signal processing interface and intelligent decision making strategies. This study includes key considerations for development of an online TCM system for milling of Inconel 718 superalloy. An effective and efficient strategy based on artificial neural networks (ANN) is presented to estimate tool flank wear. ANN based decision making model was trained by using real time acquired three axis (F_x, F_y, F_z) cutting force and torque (M_z) signals and also with cutting conditions and time. The presented ANN model demonstrated a very good statistical performance with a high correlation and extremely low error ratio between the actual and predicted values of flank wear.