基于符号有向图与定性趋势分析的化工过程故障诊断方法(英文)

In the past 30 years, signed directed graph (SDG), one of the qualitative simulation technologies, has been widely applied for chemical fault diagnosis. However, SDG based fault diagnosis, as any other qualitative method, has poor diagnostic resolution. In this paper, a new method that combines SDG with qualitative trend analysis (QTA) is presented to improve the resolution. In the method, a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model. Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consistent paths found in the previous step. New consistency rules based on qualitative trends are used to find the real causes from the candidate causes. The resolution can be improved. This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA. The implementation of SDG-QTA based fault diagnosis is done using the integrated SDG modeling, inference and post-processing software platform. Its application is illustrated on an atmospheric distillation tower unit of a simulation platform. The result shows its good applicability and efficiency.     

基于定性趋势与符号有向图的模型校核方法

模型校核的首要目标是建立一个完备的测试剧情集。针对现有模型校核方法存在的问题,提出了基于定性趋势与符号有向图的模型校核方法。首先,在总结前人多种SDG建模方法的基础上,提出了SDG校核模型的建模方法。其次,提出了基于定性趋势与符号有向图的模型校核方法,包括建立SDG校核模型、产生测试剧情、推理标准趋势序列、仿真模型数据趋势提取与识别和趋势对比分析5部分。最后,以TE模型为例进行分析,证明该方法的有效性。     

基于SDG模型的控制系统故障诊断方法

利用深层定性知识模型、符号有向图模型,对生产流程中常见的单回路和串级控制系统进行了建模与故障诊断研究。提出基于假设-验证的双向推理算法,解决了传统的故障诊断方法从未涉及复杂系统中的多个控制回路对系统故障存在的屏蔽作用的问题。通过对某厂常压蒸馏装置进行基于SDG模型的故障诊断,验证了基于SDG模型的故障诊断方法应用在包含多个控制回路的复杂系统故障诊断时的有效性与可行性。     

基于符号有向图分析的炼油厂中渣油催化裂化危险与可操作性

作为危险与可操作性(HAZOP)研究的一门辅助技术,符号有向图(SDG)分析技术迅速得到普及.仿真工厂数据是流程工业在线数据最理想的近似,能够体现过程变量之间的相互关系.本文以石油化工典型的渣油催化裂化装置为例,将SDG分析与基于机理模型的动态流程模拟仿真工厂结合起来,通过仿真工厂数据形成专家经验,进而在SDG辅助平台实施HAZOP分析,此外,分析结果也可以进一步作为HAZOP分析的知识库.同时,仿真工厂又可以验证事故传播路径,从而起到筛选SDG生成的事故序列的作用.相比于传统的专家组会议而言,将仿真工厂模拟数据运用于SDG分析中,能大幅缩短HAZOP分析时间,减少人员及投资,并且获得更为全面、准确的分析结果.     

基于SDG方法的环管反应器故障诊断

以某化工厂丙烯聚合关键设备—环管反应器为例,通过熟悉工艺流程,选取合适的关键变量,确定变量之间的影响关系,建立用于故障诊断的SDG模型.在与工厂工艺操作手册及仿真模型模拟分析校对该模型后,对该模型进行了故障诊断分析.实验结果表明,基于SDG模型的故障诊断能够准确地揭示故障传播路径.     

基于开源组件的SDG推理平台

符号有向图(SDG)是定性研究化工过程中变量间关系的有力工具,利用SDG的正向反向推理机制可以快速发掘出系统中变量之间影响的因果关系,不仅可以用于在线的故障诊断,还可以用于离线的危险和可操作性(HAZOP)分析。近年来,随着计算机和信息技术的发展,人们利用GensymG2或者C++开发了一些针对特定研究体系的SDG模型的计算机辅助推理系统,但是,目前还没有一个通用的SDG推理平台。为促进SDG在科研和教学中的广泛应用,本文介绍了通过公共组件来搭建的一套开放体系的SDG推理平台系统,这是服务器/浏览器结构的推理平台,使用方便,维护便捷。使用这套系统,可以方便地绘制特定研究体系的SDG模型的图形;可以快速建立针对特定研究体系的SDG系统并且进行相应的推理分析。本文通过一个例子演示了如何在SDG推理平台上建立特定SDG推理系统的方法,之后通过对两个研究体系建立SDG推理系统来展现该平台的有效性。     

Reliable modeling of discharge process for adsorbed natural gas storage tanks

Natural gas consumption has doubled in the last fifteen years. Among all storage techniques, adsorbed natural gas (ANG) provides a reliable vehicle for safe utilization of natural gas. Despite all favorable characteristics of the ANG process, thermal adverse effects during charge and discharge processes are the most challenging issues facing adsorbed natural gas applications, especially for automotive usage. Mathematical modeling of an ANG tank can provide a reliable method to analyze and solve such problems. A robust and lumped model is presented to mimic the discharge process of an ANG tank storing pure component. The proposed model is very convenient compared to other available conventional models that require extensive computational efforts. Two experimental measurements and two simulation data sets (borrowed from literature) are recruited to validate the model predictions. The simulation results indicate proper agreement between the proposed model predictions and the validation data.     

一类连续反应的SDG HAZOP与故障诊断

在分析苻号有向图（SDG）技术的理论基础上,探讨了SDG定性模型在计算机辅助HAZOP（危险与可操作性分析）和故障诊断中的实际应用,并针对该丙烯聚合反应（溶剂淤浆法）建立SDG模型,利用SDG技术进行HAZOP和故障诊断分析。实验结果表明,基于SDG的HAZOP和故障诊断技术具有完备性好、节省时间、人力、费用等众多优点。     

间歇过程动态SDG建模

目前用于间歇过程的SDG建模方式不能达到计算机辅助HAZOP的要求,本文在现有SDG-HAZOP理论基础上提出了面对间歇过程的动态SDG建模理论,并详细阐述了如何运用SDG对间歇过程进行建模的思路和方法,并运用该方法对一个煤制油流程的除灰工序进行建模和分析,同时解决了间歇过程SDG建模的模型接续性与故障和危险覆盖面最大化两方面问题。     

基于SDG图的化工过程初步设计方案的错误侦破方法

Digraph-based causal models have been widely used to model the cause and effect behavior of process systems. Signed digraphs （SDG） capture the direction of the effect. It should be mentioned that there are loops in SDG generated from chemical process. From the point of the inherent operability, the worst unsafe factor is the SDG having positive loops that means any disturbance occurring within the loop will propagate through the nodes one by one and are amplified gradually, so the system may lose control, which may lead to an accident. So finding the positive loops in a SDG and treating these unsafe factors in a proper manner can improve the inherent safety of a chemical process. This article proposed a method that can detect the above-mentioned unsafe factors in the proc- ess conceptual design stage automatically through the analysis of the SDG generated from the chemical process. A case study is illustrated to show the working of the algorithm, and then a complicated case from industry is studied to depict the effectiveness of the proposed algorithm.     

Experimental Validation of a Multidimensional Model for an Indirect Temperature Swing Adsorption Unit

Conventional temperature swing adsorption (TSA) is mainly applied for the removal of trace contaminants. Indirectly heated and cooled adsorbers were developed to make bulk separation economically feasible. A quasi-continuous TSA process to remove CO₂ from an N₂/CO₂ mixture with a pilot plant is established. The experimentally determined data are taken to validate and to adjust a 2D simulation model. For the validation, the CO₂ desorption, the N₂ recovery rate as well as the axial temperature profile are compared. The successful model validation can be seen in the good agreement between simulation and experimental results. Moreover, this process is able to separate high amounts of CO₂ and to produce a nearly CO₂-free product stream.     

A signed directed graph-based systematic framework for steady-state malfunction diagnosis inside control loops

Although signed directed graphs (SDG) have been widely used for modeling control loops, due to lack of adequate understanding of SDG-based steady-state process modeling, special and cumbersome methods are used to analyze control loops. In this paper, we discuss a unified SDG model for control loops, in which both disturbances (sensor bias, etc.) as well as structural faults (sensor failure, controller failure, etc.) can be easily modeled under steady-state conditions. Various fault scenarios such as external disturbances, sensor bias, controller failure, etc. have been thoroughly analyzed. A new algorithm for steady-state fault diagnosis using the SDG model for the steady-state system, that uses a combination of forward- and backward-reasoning, is proposed. Three case studies are presented to show the utility of the steady-state SDG model for fault diagnosis. A tank-level control system is used as the first case study. The second case study deals with fault diagnosis of a multi-stream-controlled CSTR. The third case study deals with fault/failure diagnosis in a process flowsheet containing a CSTR with one control loop and a flash vaporizer with three control loops.     

Numerical and experimental analysis of forced convection in rib-roughened channels with moisture-permeable walls

Ribbed features can promote mixing and improve convective heat and mass transfer in channels. This can be beneficial in certain exchangers, such as Energy Recovery Ventilators (ERVs), which employ moisture-permeable membranes to transfer both latent and sensible heat. In this work, a computational fluid dynamics model with experimental validation was used to study angled rib mixing features in compact channels. Results show that, relative to a smooth channel, the ribs increase the channel Sherwood and Nusselt numbers by a larger fraction than the corresponding increase in friction factor. For a typical commercial grade ERV, total effectiveness can be improved by over 10% for an equal pressure drop by adding ribs and slightly increasing the channel height. A custom test stand and rib-forming technique were developed to validate the simulation predictions. The experiments confirm the net benefit of ribbed channels and agree with the simulation results within experimental uncertainty.     

符号有向图在化工安全评价中的应用进展

符号有向图（Signed Directed Graph,SDG）是一种定性描述过程系统故障与故障源之间因果关系的模型方法。对SDG的研究进展进行了全面总结,通过实例介绍了SDG定性模型,重点介绍了SDG半定量模型以及SDG在安全评价中的研究成果,最后对未来发展趋势进行了展望。     

基于非线性主元分析和符号有向图的故障诊断方法

Nonlinear principal component analysis（NLPCA）fault detection method achieves good detection results especially in a nonlinear process.Signed directed graph（SDG）model is based on deep-going information,which excels in fault interpretation.In this work,an NLPCA-SDG fault diagnosis method was proposed.SDG model was used to interpret the residual contributions produced by NLPCA.This method could overcome the shortcomings of traditional principal component analysis（PCA）method in fault detection of a nonlinear process and the shortcomings of traditional SDG method in single variable statistics in discriminating node conditions and threshold values.The application to a distillation unit of a petrochemical plant illustrated its validity in nonlinear process fault diagnosis.     

Verfahrensentwicklung einer enzymkatalysierten Fettsäureveresterung mittels Prozeßsimulation

Process development of fatty acid esterification catalyzed enzymatically through process simulation. The batch esterification of fatty acids by means of fixed enzymes offers essential advantages in comparison with the conventional manufacturing process with metalkatalysts. The example of the synthesis of decyloleate from oleic acid and 1-decanol shows, that the reaction at low temperatures of < 80°C treats the product with care and selectivities of nearly 100% are reached. In addition to these environment-protecting improvements integrated into the process, there are also economic advantages as the batch time decreases and the output increases. By the use of the unsteady process-simulation it was possible to validate the results of the laboratory experiments within a short time and to minimize the risk of scale-up. Additionally, a deeper understanding of the process and important hints for process-optimization were gained. The optimal flow rate across the fixed bed as well as the most economic mass of enzymes were found by parameter variations by means of the simulation model. Simulation studies of different methods of operation showed, that the alternating operation achieves shorter reaction times than the batch operation. However, from an economic perspective, the time benefit did not compensate the additional devices required for this operation method. It could be shown, that a new, innovative process like the esterification catalyzed by enzymes can be described by mathematical models with sufficient accuracy and simulated unsteady on a PC The knowledge generated from the simulation model justifies the expenditure for the modelling and validation of the model, especially as the extension of the model on similar compounds of substances is possible without problem.     

Review of Spark Discharge Generators for Production of Nanoparticle Aerosols

In the growing field of nanotechnology there is an increasing need to develop production methods for nanoparticles, especially methods that provide control and reproducibility. The spark discharge generator (SDG) is a versatile device for the production of nanoparticle aerosols. It can produce aerosol nanoparticles in the entire nanometer range (1–100 nm), and beyond. Depending on requirements, and the system used, these nanoparticles can be completely contamination free and composed of one or more materials. This provides a unique opportunity to create new materials on the nanoscale. Already in use in semiconductor, materials, health and environmental research, the SDG shows promise for yet more applications. If needed, particle production by the SDG could be scaled up using parallel generators facilitating continuous high-volume production of aerosol nanoparticles. Still, there is a surprisingly low knowledge of fundamental processes in the SDG. In this article we present a thorough review of the most common and relevant SDGs and the theory of their operation. Some possible improvements are also discussed.

Copyright 2012 American Association for Aerosol Research     

一种间歇过程HAZOP危险性分析方法及其应用

首先描述了一种简化的间歇过程危险性与可操作性分析HAZOP（hazard and operability analysis）模型,即用Petri网和符号有向图（signed directed graph,SDG）结合的双层结构模型,模型综合了对离散事件有很好描述能力的Petri网和有较强深层推理能力的SDG二者的优点。其次应用此模型对精细化学品D3间歇生产过程操作复杂的萃取提纯工序进行了危险性分析,对生产过程中的一些误操作做了原因分析,并提出了相关的改进性措施。最后,对此方法的优缺点做了总结。     

基于复杂网络的化工过程层次符号有向图模型建立及关键节点识别

针对定性符号有向图（signed directed graph,SDG）在化工过程系统中建模复杂度高、故障分辨率低、容易忽略部分变量等问题,提出一种基于复杂网络理论构建层次SDG网络模型并识别关键节点的方法。首先利用层次分析法对化工过程系统划分递阶层次结构,建立基于子系统的系统SDG网络模型,选取度中心性、接近中心性等多个节点重要性评价指标,采用主成分分析法确定各指标权重并利用逼近理想排序法（technique for order preference by similarity to an ideal solution,TOPSIS）多属性决策方法得到节点重要性的综合评价值,初步识别关键节点所在的子系统;然后建立子系统的SDG模型并细化为有向网络,采用LeaderRank算法对节点重要性进行排序,进而在子系统网络模型中确定关键节点的位置。案例计算结果表明该方法可以有效地降低建模的复杂性,提高关键节点识别的全面性和准确性,从而改善化工过程系统的安全稳定性。     

Validation of a simulation model for water desalination in a greenhouse roof through laboratory experiments and conceptual parameter discussions

Water desalination in a greenhouse roof means that solar energy is absorbed for evaporation from a thin, flowing layer of water. Earlier a quite detailed simulation model was developed for analysis of the thermal and optical characteristics of this desalination system concept. This paper describes laboratory experiments with a small roof module and presents measurements compared to simulations obtained in order to validate the thermal part of the model. Equations, parameters and simplifications used in the model are briefly described. The laboratory work has been carried out with artificial light from a solar simulator operated in a well controlled thermal environment. The validation has an emphasis on the main parameters with impact on the water production capacity. These are the light absorptance and temperature of the absorber, the water flow rate and temperature, the inlet water temperature and the water storage volume. The main conclusion is that good agreement is obtained between simulated and measured variations of water production values for variations of these parameters. Concerning absolute values the simulated values are somewhat overestimated and possible factors behind this are discussed. Based on the simulation results, the presentation also includes some more conceptual discussions concerning system designs and operation methods. The most important indication is that geothermal water at elevated temperatures combined with this roof technology is the alternative with the highest water production capacity. A final, overall statement is that the model has a considerable potential for development into a more general system analysis tool.