废水污染物排放总量监测方法及系统设计

针对目前我国工业点源水污染在线自动监测系统存在的废水取样和分析(测量)间隔时间过长导致废水污染物排放总量监测、计算不准确以及排污企业容易掌握其废水采样规律并经常偷排、突排高浓度废水而不能被有效监测的问题,提出一种按废水排放流量比例随机采样、统一存储综合水样进行污染物排放总量监测和计算的技术方案以及相应的智能化污水污染物总量监测系统结构,并阐述其工作原理.该智能化监测系统可有效克服现有水污染在线自动监测系统在运行中存在的计算时间长、监测误差大和取样规律易泄漏的缺陷.     

A software platform for process monitoring: Applications to water treatment

Effective online monitoring of the performance of water treatment is critical. Industrial wastewater treatment, for example, has to confront important challenges concerning both cost management of treatment plants and fulfillment of regulations. Moreover, when drinking water is produced, water safety is an important consideration, and possible changes in water quality should be detected as soon as possible. On the other hand, the large amount of measurement data available creates its own challenges for water treatment processes, which means that advanced tools for monitoring, analysis, and control are often required. Therefore, it would be useful to have a monitoring system which is able to handle all available measurements and present the available information in a simple, user-friendly and flexible manner. In this paper, we introduce a piece of software which can be utilized in the monitoring of water treatment processes. The structure of the software is designed so that it can be easily modified according to the user’s needs. The system is demonstrated using process measurements from an activated sludge treatment plant, which is part of a pulp and paper plant, and from a pilot treatment plant for producing drinking water.     

基于OPC技术的LabVIEW与S7-300 PLC的污水处理监控系统

随着社会经济的迅速发展,污水处理成为环境保护的重要环节,迫切需要对污水处理过程进行先进控制和优化。目前,LabVIEW在工业自动化领域已经有了一些成功应用,但在污水处理系统中却少见报道。本文详细描述了基于LabVIEW的污水处理监控系统的体系结构和软件设计方案,利用SIMATIC.NET建立OPC服务器,为监控提供信息采集接口,并提出了避免通讯阻塞,减少实时数据采集延迟的优化策略。该系统应用于上海达能污水处理厂,可靠、稳定,很好的实现了对污水处理各工艺单元中控制对象的实时监控。     

乙烯氧氯化反应过程微机辅助监测优化的实现

工业氯乙烯生产装置是一类大规模存在的化工工业装置，本文针对其中乙烯氧氯化法反应过程特点设计的微机辅助监测优化系统，对该过程的运行特征进行在线监测，并进行数据处理和工艺分析，为该过程的优化提供了依据，此外，对这一类的化工工业装置微机辅助监测优化系统设计进行探讨，为如何在工业装置优化领域利用计算机这一先进工具提供了一个范例，并就此提出了具有普遍意义的功能模型和运行逻辑，以供类似的系统开发借鉴。     

组合机理知识的污水生化处理过程在线监视策略研究

本文把呼吸量估计知识组合到多变量主模型中，提出了一种新的污水生化处理过程（WWTP）在线监视策略.呼吸量是活性污泥(微生物)呼吸能力的一种表示,与微生物消耗的氧直接有关，其估计仅需要测量活性污泥反应器中溶解氧浓度和有关物料流量信号.由于溶解氧和流量计在工业污水处理现场安装普遍，响应快速，运行稳定且易维护，因此构造基于微生物呼吸量估计的过程监视方法，在故障检测与诊断速率、经济性等方面有显著的优势.把新方法应用到国际水协会发布的Benchmark问题，在监视暴风雨事件和毒素脉冲等典型的WWTP异常状态时，统计指标变化灵敏，诊断及时.     

Statistical and computational intelligence techniques for inferential model development: a comparative evaluation and a novel proposition for fusion

In industry today many products are sold for their efficacy rather than their chemical composition. Many variables (dependent variables), which characterize the quality of the final product in a manufacturing process, can be difficult to measure in real-time. Measurement difficulties can be due to a variety of reasons, including: (1) Reliability of on-line sensors, (2) Lack of appropriate on-line instrumentation. It is often the case that off-line laboratory tests are the only means of determining product quality measurements. However such laboratory analyses introduce delays in the measurement of key performance indicators. This can result in a significant economic loss if the analysed product fails the quality control test. In such situations an improved monitoring system is therefore required to determine product quality online and minimise commercial wastage. To facilitate this, advanced monitoring and control or optimisation techniques require inferred measurements, generated with correlations from readily available process variables (independent variables). Although inferential models are widely used in industry, only a few techniques for inferential model development are discussed in the open literature. This paper therefore will present a comparative evaluation study of the current inferential measurement techniques. An improved systematic approach for the development of inferential models using intelligent and soft computing systems is also highlighted. The proposed approach is designed to address some of the problems that currently exist in the area of inferential modelling through the fusion of statistical and computational intelligence models. A novel method of fusion is also proposed and an industrial case study is then presented to demonstrate the methodology by inferring the ‘Anchorage’ of polymeric-coated substrates (i.e. Tyvek or paper) in the coating industry. The application on which this methodology is demonstrated is unique. No such work in the literature to date has presented any inferential modelling strategies in the area of the coating industry. This strategy developed through the fusion of statistical and artificial modelling to generate a hybrid inferential measurement system has the potential to significantly improve the quality control monitoring system and reduce the economic loss encountered through the production of off-spec material.     

Design automation in MEDEA: present and future

The semiconductor industry has been growing at an unprecedented level since its start in the early 1960s. Capitalizing on the outstanding properties of silicon and its stable oxide permitted the introduction of the CMOS industry, the leading semiconductor industry process. However, the average 15% to 16% annual growth in semiconductor sales has also presented tremendous problems of huge investments in manufacturing. Mandatory now is a rapid return of investment through advanced products (in the latest available processes) that have high added value at the system level. Sometimes the system is the product itself, which raises thoughts of new ways to design these complex systems on a single chip that mixes several functionalities. This article explores a future European evolution of design automation, discussing the present status of Europe's lack of local industrial developments as well as its tremendous knowledge reservoir. Earlier MEDEA activities paved the road to new design solutions and gave European companies the chance to influence US developments, as is evidenced by frequent technology partnerships with US software vendors. Recently, we have seen a significant increase in European start-ups in advanced design automation domains (hardware-software codesign, intellectual property reuse, deep-submicron effects)     

小型计算机控制系统的设计及应用

针对因经济、技术等因素的制约,当前众多中小型工矿企业自动化水平较低、采用大型计算机系统易造成资源浪费的现状,介绍了自行研制的适合中小型生产过程特点的小型计算机控制系统,包括组态和运行两大部分。使用可视化组态平台,可快速方便地开发出经济实用的监控系统。运行平台是交互式的图形用户界面,具有数据实时采集处理、历史数据存储和浏览、报警显示和对复杂工业对象的远程控制等功能,并内嵌OPC服务器,便于对系统进行远程访问和控制。应用结果表明,该系统具有良好的开放性和可靠性,各项功能正常,能满足实际工业生产的需要。     

污水处理厂远程运营管理系统解决方案

污水处理厂远程运营管理系统解决方案,主要满足水务集团、排水集团等用户对多个污水处理厂进行集中管理的需求,以工业数据库软件-KingHistorian为核心,实现多个污水处理厂远程数据采集、可视化管理、水质集中监管、生产成本管理、设备管理等主要功能。     

废水资源化处理过程在线监测方法

针对废水资源化处理过程,基于偏最小二乘法提出了基于准三维荧光谱的在线解析方法,实现了废水资源化处理过程中荧光谱的在线解析。研究结果表明,该方法能够在少量数据的情况下对色氨酸、核黄素、辅酶进行有效区分,预测浓度的准确率达到85%以上。基于算法研究的基础上提出了一种废水资源化处理过程在线监测方案,设计并实现了在线监测系统。根据采集数据进行分析,实验表明,该方法具有体积小、精度高、采集速度快、数据可在线分析等优点,实用性强,易于推广和应用。     

Robust optimization-based multi-loop PID controller tuning: A new tool and its industrial application

Modern process plants are highly integrated and as a result, decentralized PID control loops are often strongly interactive. The iterative SISO tuning approach currently used in industry is not only time consuming, but does also not achieve optimal performance of the inherently multivariable control system. This paper describes a method and a software tool that allows control engineers/technicians to calculate optimal PID controller settings for multi-loop process systems. It requires the identification of a full dynamic model of the multivariable system, and uses constrained nonlinear optimization techniques to find the controller parameters. The solution is tailored to the specific control system and PID algorithm to be used. The methodology has been successfully applied in many industrial advanced control projects. The tuning results that have been achieved for interacting PID control loops in the stabilizing section of an industrial Gasoline Treatment Unit as well as a Diesel Desulfurization plant are presented.     

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.     

A petri nets‐based process planning system for wastewater treatment

It is always challenging to simulate, debug or diagnose automated systems. The aim of this paper is to present the development of a convenient tool for reengineering the control system in a complicated industrial wastewater treatment plant. In this project, a PC‐based Human‐Machine Interface (HMI) in conjunction with Petri nets (PN) theory is adopted to develop and simulate the operational process for wastewater treatment. The resultant tool offers many advantages to the reality of the automated control world. It not only reduces the process reengineering time and the cost of error recovery, but also builds a panel of human interface for the process. The discrete event control sequence of wastewater treatment can be easily modeled and evaluated before its build‐up. Furthermore, this PN‐based system can be used as an online diagnostic tool when the wastewater treatment process is malfunctioning. That is, the presented PN tool provides an adequate means for offline process development, simulation, performance evaluation, and quick online process diagnosis. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

DCS系统在热源厂中的应用

DCS系统是完全无缝集成的自动化解决方案。可以应用于所有工业领域,包括过程工业、制造工业、混合工业以及工业所涉及的所有制造和过程自动化产品。作为先进的过程控制系统,DCS形成了一个带有典型过程组态特征的全集成系统。该文着重介绍了DCS在热源厂自动化控制系统中的应用,论述了该系统的组成及其特点,并通过实际应用验证了其系统的高效性、实用性和稳定性。     

CAS理论视角下产业集群演化模型构建

针对产业集群的复杂自适应系统（Complex Adaptive System,CAS）特性,以CAS理论的个体行为模型和整体演化的ECHO模型为基础,并结合产业集群的概念特征建立产业集群系统构架。并在此基础上,提出产业集群系统动态演化模型。该模型把产业集群演化的生命周期特性和复杂系统的演化识别过程结合起来,以复杂系统的演化机制为依据,认为产业集群诞生于混沌经济环境,经过系统对环境的自适应学习,自身的分岔与突变,系统功能的整体涌现,达到系统暂态稳定,是一个螺旋上升的循环过程。产业集群系统演化的核心机制是以产业分工为主的自适应机制和以系统创新为主的分岔与突变机制。     

Developing and evolving a DSL-based approach for runtime monitoring of systems of systems

Complex software-intensive systems are often described as systems of systems (SoS) due to their heterogeneous architectural elements. As SoS behavior is often only understandable during operation, runtime monitoring is needed to detect deviations from requirements. Today, while diverse monitoring approaches exist, most do not provide what is needed to monitor SoS, e.g., support for dynamically defining and deploying diverse checks across multiple systems. In this paper we report on our experiences of developing, applying, and evolving an approach for monitoring an SoS in the domain of industrial automation software, that is based on a domain-specific language (DSL). We first describe our initial approach to dynamically define and check constraints in SoS at runtime and then motivate and describe its evolution based on requirements elicited in an industry collaboration project. We furthermore describe solutions we have developed to support the evolution of our approach, i.e., a code generation approach and a framework to automate testing the DSL after changes. We evaluate the expressiveness and scalability of our new DSL-based approach using an industrial SoS. We also discuss lessons we learned. Our results show that while developing a DSL-based approach is a good solution to support industrial users, one must prepare the approach for evolution, by making it extensible and adaptable to future scenarios. Particularly, support for automated (re-)generation of tools and code after changes and automated testing are essential.     

基于随机取样的污水污染物总量监测系统设计

针对目前水污染在线自动监测系统普遍存在的废水污染物排放总量测算不精确、废水采样周期固定而具有规律性的问题,提出一种基于比例取样结合随机取样方法的智能化污水污染物总量监测系统,并详细阐述了系统的软、硬件设计方案.该系统采用悬浮的模数转换器(A/D)模拟输入口的随机电压值作为随机采样周期并按废水流量比例采样、统一存储综合水样.系统实测证明,该系统可有效实现对废水排放企业的排污总量的精确测量,降低运行成本并使排污企业无法掌握监测系统采样规律,从而避免其偷排、突排高浓度废水.     

基于USB2831数据采集卡的污水处理在线检测仪设计

采用USB2831数据采集卡与外部其它器件构成污水处理过程监控系统,控制污水处理过程参数和采集过程关健产物的荧光光谱数据,实现污水处理过程在线检测.该仪器不仅应用于污水处理,在啤酒酿造以及发酵领域有很好的应用前景.     

AAO 生物池自控系统设计

在目前城镇污水处理厂的污水处理工艺中,AAO 生物池占有举足轻重的地位,而在AAO 生物池设置适当的 在线检测仪表,采用先进的PLC 自动控制系统,通过调节曝气量、污泥回流量等参数则可达到设计预期的脱氮除磷效果。为 了根据进水水质、温度等调节AAO 生物池的各设计参数,将变频器与先进的自动控制技术、通讯技术相结合,对鼓风机、回流 污泥泵等进行变频调速控制,不但可以满足工艺设计要求,而且也是一种比较节能的技术手段。     

基于OSR—MAS的产业集群演化建模与仿真

针对产业集群的复杂自适应系统（ComplexAdaptiveSystem,CAS）特性,以CAS理论的个体行为模型和整体演化的ECHO模型为基础,并结合产业集群的概念特征建立产业集群系统构架。在此基础上,提出产业集群系统演化机制模型。该模型把产业集群演化的生命周期特性和复杂系统的演化识别过程结合起来,以复杂系统的演化机制为依据,提出产业集群诞生于混沌经济环境,经过系统对环境的自适应学习、自身的分岔与突变、系统功能的整体涌现,达到系统暂态稳定的循环过程。