Real Time Automation and Ratio Control Using PLC&SCADA in Industry 4.0

Industrial Control Systems(ICS)and SCADA(Supervisory Control and Data Acquisition)systems play a critical role in the management and regulation of critical infrastructure.SCADA systems brings us closer to the real-time application world.All process and equipment control capability is typically provided by a Distributed Control System(DCS)in industries such as power stations,agricultural systems,chemical and water treatment plants.Instead of control through DCS,this paper proposes a SCADA and PLC(Programmable Logic Controller)system to control the ratio control division and the assembly line division inside the chemical plant.A specific design and implementation method for development of SCADA/PLC based real time ratio control and automated assembly line system in a chemical plant is introduced.The assembly line division is further divided into sorting stage,filling stage and the auxiliary stage,which includes the capping unit,labelling unit and then the storage.In the ratio control division,we have defined the levels inside the mixer and ratio of the raw materials through human machine interface(HMI)panel.The ratio of raw materials is kept constant on the basis of flow rates of wild stream and manipulated stream.There is a flexibility in defining new levels and the ratios of the raw materials inside the mixer.But here we taken the predefined levels(low,medium,high)and ratios(3:4,2:1,2:5).Control valves are used for regulating the flow of the compositions.In the assembly line division,the containers are sorted on the basis of size and type of material used i.e.,big sized metallic containers and small sized non-metallic containers by inductive and capacitive proximity sensors.All the processes are facilitated with laser beam type or reflective type sensors on the conveyor system.Building a highly stable and dependable PLC/SCADA system instead of Distributed Control System is required to achieve automatic management and control of chemical industry processes to reduce waste manpower and physical resources,as well as to improve worker safety.

Automated federated learning‐based adversarial attack and defence in industrial control systems

With the development of deep learning and federated learning(FL),federated intrusion detection systems(IDSs)based on deep learning have played a significant role in securing industrial control systems(ICSs).However,adversarial attacks on ICSs may compromise the ability of deep learning-based IDSs to accurately detect cyberattacks,leading to serious consequences.Moreover,in the process of generating adversarial samples,the selection of replacement models lacks an effective method,which may not fully expose the vulnerabilities of the models.The authors first propose an automated FL-based method to generate adversarial samples in ICSs,called AFL-GAS,which uses the prin-ciple of transfer attack and fully considers the importance of replacement models during the process of adversarial sample generation.In the proposed AFL-GAS method,a lightweight neural architecture search method is developed to find the optimised replacement model composed of a combination of four lightweight basic blocks.Then,to enhance the adversarial robustness,the authors propose a multi-objective neural archi-tecture search-based IDS method against adversarial attacks in ICSs,called MoNAS-IDSAA,by considering both classification performance on regular samples and adver-sarial robustness simultaneously.The experimental results on three widely used intrusion detection datasets in ICSs,such as secure water treatment(SWaT),Water Distribution,and Power System Attack,demonstrate that the proposed AFL-GAS method has obvious advantages in evasion rate and lightweight compared with other four methods.Besides,the proposed MoNAS-IDSAA method not only has a better classification performance,but also has obvious advantages in model adversarial robustness compared with one manually designed federated adversarial learning-based IDS method.

e-Automation,an Architecture for Distributed Industrial Automation Systems

Due to the complexity of modern industrial systems, a conventional automation system is not capable of providing sufficient information management and high-level intelligent approaches, as achieving these functionalities requires the support of comprehensive data management and coordination between system devices and heterogenous information. This paper proposes the concept of e-Automation, in which computer networking and distributed intelligence agent technologies are applied to industrial automation systems, and presents a hardware and software architecture that implements this concept. An open infrastructure based on multi-agent systems is employed in the proposed architecture of e-Automation, which aims to allow the implementation of diverse tasks and to permit greater configurability than can be obtained from a traditional system. To evaluate our proposed e-Automation concept, this paper presents a case study of substation information management which adopts the proposed e-Automation architecture in power system domain.

Development and experience in the monitoring,assessment and control of environmentalpollutants in Hong Kong

The late start of environmental protection in Hong Kong was discussed in the light of problems encountered during the development of environmental protection legislation in Hong Kong for the past 20 years. The collaboration in monitoring and assessment of environmental pollutants between the University of Hong Kong and various governments were descrbed in parallel with the progress in environmental protection in Hong Kong. The developments of new analytical techniques for environmental monitoring and analysis is given and their application in environmental control described. The joint projects in assessment and control of environmental pollutants carried out in collaboration with local industries and other organizations within and without the university are given and discussed. The problems and possible solution facing Hong Kong in development control equipment for small scale industries are discussed and areas of development identified. The development and experience in the monitoring assessment and control of environmental pollutants in Hong Kong are summarized and areas of difficulties are illustrated.

Industry 4.0 Application in Manufacturing for Real-Time Monitoring and Control

Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing assets.This article builds upon the Industry 4.0 concept to improve the efficiency of manufacturing systems.The major contribution is a framework for continuous monitoring and feedback-based control in the friction stir welding(FSW)process.It consists of a CNC manufacturing machine,sensors,edge,cloud systems,and deep neural networks,all working cohesively in real time.The edge device,located near the FSW machine,consists of a neural network that receives sensory information and predicts weld quality in real time.It addresses time-critical manufacturing decisions.Cloud receives the sensory data if weld quality is poor,and a second neural network predicts the new set of welding parameters that are sent as feedback to the welding machine.Several experiments are conducted for training the neural networks.The framework successfully tracks process quality and improves the welding by controlling it in real time.The system enables faster monitoring and control achieved in less than 1 s.The framework is validated through several experiments.

产教融合理念下化工仪表及自动化课程教学改革探究

本文以产教融合理念为基础,针对化工仪表及自动化课程教学进行改革研究。以学生学习反应釜温度PID控制参数整定设置知识点为例,从理论教学和产业应用两个角度分析微分时间常数TD取值对温控系统过渡过程特性影响及调节阀流量特性和控制死区等因素对TD值的限制问题,提升学生深刻理解TD常数意义。在此基础上,提出教学改革措施,旨在提高学生的实践能力和创新意识。本研究表明,通过产教融合的教学模式和教学方法,可以显著提高学生的对化工自动化课程的学习效果,为其未来的职业发展打下坚实的基础。

基于运动模式划分的工业机器人健康监测方法

由于工业机器人存在多运动模式耦合的问题,传统的健康监测方案需要在每个关节处单独安装传感器,难以满足实际工业现场需求。本文以6关节工业机器人为研究对象,基于振动信号研究了多运动模式切换场景下工业机器人的健康监测方法。首先,通过跳变点算法实现机器人运动模式划分,获取不同运动模式对应的信号区间。其次,对不同运动模式的信号分别提取监测指标。最后,基于控制图法实现工业机器人不同关节的健康监测。在工业机器人退化实验数据中验证了本文所提方法,表明本文所提方法能够在仅使用两个振动传感器的条件下实现机器人6个关节的健康状态监测。本文所提运动模式划分算法在对大量历史退化数据进行分析时,所需运行时间更短、单次精度更高且重复性更好。本文提出的方法能够在使用少量传感器的条件下,有效避免运动模式耦合和采样信号的差异可能导致的监测结果误判,使得监测结果更加精准可靠,适用于实际工业现场的工业机器人健康状态监测。

基于Android平台的远程工业监控系统

针对生产管理人员需要运用移动终端对工业生产流程进行远程监控,设计并实现了基于Android平台的远程工业监控系统;该系统对现有工业控制平台进行了扩展,运用OPC技术与组态软件进行通讯,使用WCF Service技术封装了对数据的各类操作,以服务的形式提供了实时数据访问接口;基于Android平台工业控件库,开发了用于远程监控饲料生产系统的终端应用;实际应用表明移动终端能实时地显示生产数据,并对原有系统影响较小。

基于Android的工业控制监控软件设计

提出一种基于Android平台的工业控制移动监控软件设计方案。采用面向对象和层次化的方法,开发一个具有工业流程图显示、报警推送、安全认证等功能的监控软件。在原有工厂网络拓扑结构中架设移动终端服务器保证系统兼容性。运用Android NDK开发、多级页表映射和异步网络传输的方式提高位号点数据的传输速度,保证软件的实时性。测试结果表明,该方案能有效解决传统上位机软件只能运行于PC机端问题,具有良好的可用性。

隧道变形自动化监控数据校验与应用分析

以一新建双线盾构隧道近距离下穿既有暗挖隧道为工程依托,通过数值模拟分析既有隧道结构的变形规律,确定变形控制关键区域,布设自动化监测点。将自动化监测值与数值模拟值进行对比分析,及时对异常数据进行去噪处理,必要时调整数值计算模型,确保无人工复测数据验证时自动化监测数据的可靠性。确定监测数据可靠后,再对关键工序(如二次注浆等)既有隧道结构进行高频实时自动化监测,及时分析既有隧道变形情况,调整施工参数,从而实现对既有隧道结构变形的精准控制。

基于模糊测试技术的电力工控系统漏洞挖掘算法

针对工控系统运行环境封闭带来的传统漏洞检测无法导出系统组件进行分析的问题,根据工控网络协议特征,结合测试用例变异因子,针对Modbus_TCP公开协议提出一种改进的电力工控系统漏洞测试挖掘方法。所提方法利用变异因子与工控协议特征依赖关系,改造协议测试用例。通过将测试用例的特征值和数据域的长度值因子及其数值的选择进行合并,并做归一化处理,进而简化协议测试过程中变异因子的执行次数。针对Modbus_TCP工控协议的模糊测试结果表明,改进后的Fuzzing测试表现出了更高的测试用例接收率和测试效率,测试样例的平均接收率至少提高50%。

基于预测模糊FLC控制下农业生产过程监控与优化

该文以温室监控系统为案例,针对传统PLC控制在复杂环境下的局限性,提出了一种基于预测模糊FLC控制的优化技术,该技术利用模糊逻辑对环境变量进行模糊化处理,并结合预测算法对未来状态进行预测,从而实现对温室环境的精准控制和优化调节。通过试验验证,该优化技术能够提高温室生产效率、降低能耗成本,并保障农作物的生长质量和产量稳定性。研究结果可以为农业生产过程的智能化监控与优化提供新的思路和方法。

基于统计过程控制的硅转接板良率优化系统设计

针对2.5D封装用硅通孔(through silicon via,TSV)硅转接基板批量化生产过程中缺乏可靠性评价与优化技术的问题,提出基于统计过程控制(statistical process control,SPC)的评估控制系统,实现在线工艺状态监控及评价,设计硅转接板测试用工艺控制检测(process control monitor,PCM)结构,阐述自动光学检测(automated optical inspection,AOI)中常见的缺陷对系统可靠性的影响。提出的SPC系统对硅转接板批量化生产良率提升具有重要意义。

化工安全生产中DCS自动化控制的应用

DCS自动化控制作为自动化控制最为重要的技术,极大推动了化工行业的发展。DCS控制系统在化工产品中的应用已是必然趋势,能大大加速国内化工行业的发展步伐,有效保障化工生产运行的安全性,降低生产能耗。重点探讨了DCS自动化控制系统在组合聚醚生产中的应用问题以及发展趋势,为相关化工企业的自动化转型提供参考。

化工机械设备与电气自动化控制的有机融合

随着电气自动化控制技术的不断创新和快速发展,化工机械设备与电气自动化控制的有机融合成为化工企业发展和创新的必然趋势。简介电气自动化控制的类型,对化工机械设备与电气自动化控制有机融合的特点进行分析,展示化工机械设备与电气自动化控制融合在实时监测系统、紧急停车系统和安全仪表系统的应用。应用实践表明,化工机械设备与电气自动化控制的有机融合,能够提升化工产品质量、降低生产成本,减少化工机械设备的故障发生率,保障工作人员的人身安全,提高企业的经济效益,助力企业实现高质量、高效率、高标准发展。

电力系统自动化中的电能质量监测与控制

研究了电力系统自动化中的电能质量监测与控制方法,首先对电力系统的结构与功能、自动化技术的应用进行了概述,然后定义了电能质量的概念,并对电能质量的分类和监测方法进行了详细分析。其次,提出了电能质量的控制目标,分析了谐波控制、电压控制和电流控制等方法,并设计了相应的控制模型。最后,通过实验研究验证了所提方法的有效性,并对实验数据进行了分析。

自动化技术在汽车控制系统中的应用

阐述自动化技术在汽车控制系统中的特点,探讨自动化技术在信息监测与反馈处理、机械控制效率优化、电力分配中的应用,并提出一系列创新的自动化控制策略和优化方法。

化工机械设备与电气自动化控制的有机融合探讨

现阶段,化工企业内的机械设备不断增多,这些导致机械设备的自动化控制难度更大,将化工机械设备和电气自动化控制有机融合,能够建立一个庞大有序的自动化控制体系,将全部的化工机械设备涵盖在内,为机械设备的自动化监管和控制提供有效的技术支持。对此,就化工机械设备和电气自动化控制有机融合的意义、目标以及特点进行了分析,说明了化工机械设备和电气自动化控制融合的关键技术,并探究了具体的融合的应用。

海上平台仪表在油气生产自动化控制中的应用

油气资源需求市场不断增加,油气供应格局也在不断改变升级,从以陆为主到陆海统筹,再到现在的海陆并重,海洋油气开发已成为现代工业生产过程中不可或缺的一部分。海上油田的仪表自动化控制技术在生产过程中起着至关重要的作用,随着生产规模不断扩大、技术不断更新,仪表自动化控制技术的高水平应用在提高生产产量的同时,也保证平台生产的安全稳定运行。

可编程逻辑控制器在工业电气自动化的实践

在各类科技术持续发展下,工业领域与信息技术间的联系逐渐加深,可编程逻辑控制器(PLC)在工业领域得到广泛的应用,促进工业电气自动化控制水平的有效提升。基于此,文章从可编程逻辑控制器概述入手,分析工业电气自动化中(PLC)的应用,阐述可编程逻辑控制器(PLC)在工业电气自动化中的应用案例,最后,提出工业电气领域可编程逻辑控制器(PLC)未来发展方向,希望为相关人员提供参考,积极借助可编程逻辑控制器(PLC),促进工业电气自动化快速发展。