基于VPLS的TE过程统计产品质量与费用控制

Product quality and operation cost control obtain increasing emphases in modern chemical system engineering. To improve the fault detection power of the partial least square (PLS) method for quality control, a new QRPV statistic is proposed in terms of the VP (variable importance in projection) indices of monitored process variables, which is significantly advanced over and different from the conventional Q statistic. QRPV is calculated only by the residuals of the remarkable process variables (RPVs). Therefore, it is the dominant relation between quality and RPV not all process variables (as in the case of the conventional PLS) that is monitored by this new VP-PLS (VPLS) method. The combination of QRPV and T2 statistics is applied to the quality and cost control of the Tennessee Eastman (TE) process, and weak faults can be detected as quickly as possible. Consequently, the product quality of TE process is guaranteed and operation costs are reduced.     

用数值模拟方法分析混合和导流筒对搅拌槽中沉淀硫酸钡的影响

1 INTRODUCTION Precipitation of sparingly soluble salts is an im- portant operation widely adopted in the production of functional materials, catalyst, protein, pharmaceutical product and pigment. By precipitation, two aqueous streams containing respective reactants are mixed in a precipitator, and the sparingly soluble salt forms as result of chemical reaction if the concentration of produced salt exceeds its solubility. The quality of the final product obtained by precipitation is strong…     

Physical Properties in Drying of Food Products with Combined Sublimation and Evaporation

Drying is an important unit operation in processing of biological resources. The drying process may influence the product properties and quality, which may shrink, break or undergo rheological, physical and biochemical changes. The important parameters responsible for such changes are drying conditions, type of drying technology and residence drying time. Thermal conductivity, thermal-mass diffusivity, enthalpy, porosity and density are the main material property and heat-mass transfer parameters, which are essential for understanding the changes in product quality and for designing and dimensioning the drying processes. In this paper physical properties of food products undergoing a combined sublimation and evaporation were studied. Pieces of vegetables and potatoes were dried in a heat pump fluidized bed dryer at combined modes with temperatures below the freezing point in the beginning and a final drying step at temperatures above the freezing point. Samples of products were tested at different moistu     

Simultaneous optimization of heat-integrated crude oil distillation systems☆

Crude oil distil ation is important in refining industry. Operating variables of distil ation process have a critical ef-fect on product output value and energy consumption. However, the objectives of minimum energy consumption and maximum product output value do not coordinate with each other and do not lead to the maximum eco-nomic benefit of a refinery. In this paper, a systematic optimization approach is proposed for the maximum an-nual economic benefit of an existing crude oil distil ation system, considering product output value and energy consumption simultaneously. A shortcut model in Aspen Plus is used to describe the crude oil distillation and the pinch analysis is adopted to identify the target of energy recovery. The optimization is a nonlinear program-ming problem and solved by stochastic algorithm of particle warm optimization.     

Chemical Reaction Route Selection Based on Green Chemical Engineering

In the preliminary stage of chemical process design, the choice of chemical reaction route is the key design decision, and the concepts of atom utilization and environmental quotient have become extremely useful tools. However, the waste quality such as chemical toxicity and other engineering factors have not been taken into account. Therefore, a synthetic route selection index, IRoute is proposed to determine the suitability of a chemical route in this paper. IRoute considers the effects of "extended atom economy", material renewability, chemical characteristics and some engineering factors. The extended atom economy concept regards not only the value of the desired product but also the value of byproducts. The methodology by using IRoute to compare different routes is illustrated in case study of cyclohexanone oxime and acrylonitrile manufacture.     

用升华与蒸发联合法干燥食品的物理性质

Drying is an important unit operation in processing of biological resources. The drying process may influence the product properties and quality, which may shrink, break or undergo rheological, physical and biochemical changes. The important parameters responsible for such changes are drying conditions, type of drying technology and residence drying time. Thermal conductivity, thermal-mass diffusivity, enthalpy, porosity and density are the main material property and heat-mass transfer parameters, which are essential for understanding the changes in product quality and for designing and dimensioning the drying processes. In this paper physical properties of food products undergoing a combined sublimation and evaporation were studied. Pieces of vegetables and potatoes were dried in a heat pump fluidized bed dryer at combined modes with temperatures below the freezing point in the beginning and a final drying step at temperatures above the freezing point. Samples of products were tested at different moisture contents with respect to physical properties. Physical properties of leek and potato samples were measured and mass diffusivities were determined from drying kinetic data. Based on bulk density and rehydration measurements it was clearly observed that drying temperature and modes influenced the final product physical properties. The potato cuberun dried with initial atmospheric freeze-drying step had rehydration ability 430% above a run dried only above the freezing point. The average effective mass diffusivity for 5 mm slabs of leek was 0.5×10^-11m^2·s^-1 for the sublimation stage and 2.2×10^-11m^2·s^-1 for the evaooration stage.     

Economic analysis in product design——A case study of a TCM dietary supplement

An approach for the economic analysis of chemical product design is proposed. It takes into account of customers' preference on product quality and economic considerations such as pricing, profit, market share, capital investment, and operating cost. The activities needed to support business decision making – identifying product quality, estimating product cost, calculating financial metrics, and performing make–buy analysis – are discussed.The design of a Ganoderma lucidum dietary supplement, a traditional Chinese medicinal(TCM) product, is used to illustrate all the activities in this approach.     

基于绿色化工的化学反应路径选择

In the preliminary stage of chemical process design, the choice of chemical reaction route is the key design decision, and the concepts of atom utilization and environmental quotient have become extremely useful tools. However, the waste quality such as chemical toxicity and other engineering factors have not been taken into account. Therefore, a synthetic route selection index, /Route, is proposed to determine the suitability of a chemical route in this paper. /Route considers the effects of “extended atom economy”, material renewability, chemical characteristics and some engineering factors. The extended atom economy concept regards not only the value of the desired product but also the value of byproducts. The methodology by using IRoute to compare different routes is illustrated in case study of cyclohexanone oxime and acrylonitrile manufacture.     

可持续制造业中汽车表面涂层自动化生产的多尺度表征

Automotive surface coating manufacturing is one of the most sophisticated and expensive steps in automotive assembly. This step involves generating multiple thin layers of polymeric coatings on the vehicle surface through paint spray and curing in a multistage, dynamically changing environment. Traditionally, the quality control is solely post-process inspection based, and process operational adjustment is only experience based, thus the manufacturing may not be （highly） sustainable. In this article, a multiscale system modeling and analysis methodology is introduced for achieving a sustainable application of polymeric materials through paint spray and film curing in automotive surface coating manufacturing. By this methodology, the correlations among paint material, application processes and coating performance can be identified. The model-based analysis allows a comprehensive and deep study of the dynamic behaviors of the material, process, and product in a wide spectrum of length and time. Case studies illustrate the efficacy of the methodology for sustainable manufacturing.     

基于软测量技术的先进控制在精馏塔上的应用

In this paper, the control of a butadiene distillation column is discussed and improved. At first, a neural network soft-sensor instrument of product quality was built based on abundant on-the-spot data collected by DCS and simulated data obtained by a theoretical model. Then, an inferential control scheme based on the soft-sensor was designed. By increasing logic and expert controllers in the inferential control arithmetic, the robustness of the system was enhanced. The practical application showed that the scheme could run smoothly over a long period and realized close-loop control of product quality.     

Nonlinear Real‐time Process Monitoring and Fault Diagnosis Based on Principal Component Analysis and Kernel Fisher Discriminant Analysis

The aim of this paper is to propose a novel real‐time process monitoring and fault diagnosis method based on the principal component analysis (PCA) and kernel Fisher discriminant analysis (KFDA). There is a need to develop this method in order to overcome the inherent limitations of the current kernel FDA method. The idea of the method is to initially reduce dimensionality using PCA and then to map the score data in the reduced original space to the high‐dimensional feature space via a nonlinear kernel function. Following this, the optimal Fisher feature vector and discriminant vector are extracted to perform process monitoring. If faults occur, the method uses the degree of similarity between the optimal discriminant vector presented and the optimal discriminant vector of the faults in the historical dataset to perform a diagnosis. The proposed method can effectively capture nonlinear relationships in process variables. In comparison with kernel FDA, the PCA plus kernel FDA method is more efficient and has a more rapid response when used to undertake online monitoring and fault diagnosis. In this study, the method is evaluated by applying it to the fluid catalytic cracking unit (FCCU) process. As a consequence, its effectiveness is demonstrated.     

MPCA在间歇反应过程故障诊断中的应用

将多方向主元分析(MPCA)理论应用到一个实际的PVC间歇反应过程的性能监测与故障诊断中。由于间歇反应的特点,数据具有多维性,应用传统的主元分析将使过程的统计建模与故障诊断难以实现。MPCA可将间歇过程的多维数据沿时间轨迹分割,使得多批次的数据可以在各时间序列轨迹上建立相应的PCA模型,从而完成对间歇过程的实时监视及故障诊断。     

自适应MPCA方法在链霉素过程监控中的应用

Multi-way principal component analysis (MPCA) had been successfully applied to monitoring the batch and semi-batch process in most chemical industry. An improved MPCA approach, step-by-step adaptive MPCA (SAMPCA), using the process variable trajectories to monitoring the batch process is presented in this paper. It does not need to estimate or fill in the unknown part of the process variable trajectory deviation from the current time until the end. The approach is based on a MPCA method that processes the data in a sequential and adaptive manner. The adaptive rate is easily controlled through a forgetting factor that controls the weight of past data in a summation. This algorithm is used to evaluate the industrial streptomycin fermentation process data and is compared with the traditional MPCA. The results show that the method is more advantageous than MPCA, especially when monitoring multi-stage batch process where the latent vector structure can change at several points during the batch.     

步进MPCA及其在间歇过程监控中的应用

针对多向主元分析法(MPCA)在间歇过程监控过程中需要预测过程未来输出的困难,提出了一种新的步进多向主元分析方法。该方法通过建立一系列的PCA模型,避免了对预估过程变量未来输出的需要,通过引入遗忘因子能够自然地处理多阶段间歇过程的情况。对于多阶段链霉素发酵过程的监控表明,相对于普通MPCA,步进MPCA能够更精确地对过程故障行为进行描述。     

一种基于改进MPCA的间歇过程监控与故障诊断方法

针对基于不同展开方式的多向主元分析(MPCA)方法在线应用时各自存在的缺陷,提出一种改进的基于变量展开的MPCA方法,实现间歇过程的在线监控与故障诊断。该方法采用随时间更新的主元协方差代替固定的主元协方差进行T²统计量的计算,充分考虑了主元得分向量的动态特性;同时引入主元显著相关变量残差统计量,避免SPE统计量的保守性,且该统计量能提供更详细的过程变化信息,对正常工况改变或过程故障引起的T²监控图变化有一定的识别能力;最后提出一种随时间变化的贡献图计算方法用于在线故障诊断。该方法和MPCA方法的监控性能在一个青霉素发酵仿真系统上进行了比较。仿真结果表明：该方法具有较好的监控性能,能及时检测出过程存在的故障,且具有一定的故障识别和诊断能力。     

基于核Fisher判别分析方法的非线性统计过程监控与故障诊断

化工过程中大量的生产数据反应了生产过程的内在变化和系统的运行状况，基于数据驱动的统计方法可以有效地对生产过程进行监控。对于复杂的化工和生化过程，其过程变量之间的相关关系往往具有很强的非线性特性，传统的线性统计过程监控方法显得无能为力。本文提出了基于核Fisher判别分析的非线性统计过程监控方法，首先利用非线性核函数将数据从原始空间映射到高维空间，在高维空间中利用线性的Fisher判别分析方法提取数据最优的Fisher特征矢量和判别矢量来实现过程监控与故障诊断，能有效地捕获过程变量之间的非线性关系，通过对流化催化裂化（FCCU）过程的仿真表明该方法的有效性。     

基于核主角的故障检测方法

基于主元分析（PCA）的统计检测方法已经被广泛应用于各种化工过程的故障检测和识别.移动主元分析（moving principal component analysis,简称MPCA）算法基于PCA,根据主元子空间的变化来判断故障是否发生.然而,基于主元分析的统计检测方法是线性方法,无法有效应用于非线性系统.因此,提出一种适合于非线性系统的故障检测方法——基于核主角(kernel principal angle,简称KPA)的故障检测方法,其基本思想与MPCA相似,主要内容包括构建特征子空间和核主角测量两部分.TE过程故障检测仿真实验证明,基于核主角的故障检测方法优于传统的多元统计检测方法（cMSPC）和MPCA.     

基于核Fisher包络分析的间歇过程故障诊断

随着间歇过程越来越受重视,其过程监控和故障诊断技术也成为研究热点。以核Fisher判别分析为基础,提出了基于核Fisher的正常工况与故障包络面模型,给出了基于该模型的在线故障诊断流程。此方法利用了Fisher判别分析对类别的划分特点,分别针对正常工况数据和各故障类型数据建立包络曲面模型。与多向Fisher判别分析相比,该方法按批次方向将数据展开,能够解决生产周期不一致问题,在线故障诊断时也不需要预报完整的生产轨迹,并且加入核函数来处理复杂的非线性。最后在青霉素发酵过程的仿真平台上对该方法进行测试,与改进多向Fisher判别分析方法进行对比,该方法获得了满意的诊断效果：能够及早诊断出故障的发生,并在有效识别已有故障的同时还具有对新故障的自学习能力。     

基于Fisher判别分析和核回归的质量监控和估计

A novel systematic quality monitoring and prediction method based on Fisher discriminant analysis (FDA) and kernel regression is proposed. The FDA method is first used for quality monitoring. If the process is under normal condition, then kernel regression is further used for quality prediction and estimation. If faults have occurred, the contribution plot in the fault feature direction is used for fault diagnosis. The proposed method can effectively detect the fault and has better ability to predict the response variables than principle component regression (PCR) and partial least squares (PLS). Application results to the industrial fluid catalytic cracking unit (FCCU) show the effectiveness of the proposed method.     

在线自适应批次过程监视的双滑动窗口MPCA方法

Online monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database. In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA （multiway principal component analysis） model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA. The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride （PVC） process in the Jinxi Chemical Company of China since 1999.