Discriminant Analysis of Time Series in the Presence of Within‐Group Spectral Variability

Many studies record replicated time series epochs from different groups with the goal of using frequency domain properties to discriminate between the groups. In many applications, there exists variation in cyclical patterns from time series in the same group. Although a number of frequency domain methods for the discriminant analysis of time series have been explored, there is a dearth of models and methods that account for within‐group spectral variability. This article proposes a model for groups of time series in which transfer functions are modelled as stochastic variables that can account for both between‐group and within‐group differences in spectra that are identified from individual replicates. An ensuing discriminant analysis of stochastic cepstra under this model is developed to obtain parsimonious measures of relative power that optimally separate groups in the presence of within‐group spectral variability. The approach possesses favourable properties in classifying new observations and can be consistently estimated through a simple discriminant analysis of a finite number of estimated cepstral coefficients. Benefits in accounting for within‐group spectral variability are empirically illustrated in a simulation study and through an analysis of gait variability.     

Multi-zone TAP-reactors theory and application. III Multi-response theory and criteria of instantaneousness

A general theory of multi-response state-defining experiments for a multi-zone temporal analysis of products reactor, is developed using the Laplace transform and a generalization of the transfer matrix formalism previously introduced for single-response experiments. The theory provides a unified approach to multi-response modelling and an efficient means to compute the actual profiles of gases and surface species concentration in the reactor, as well as the values of the outlet fluxes numerically, using e.g. fast fourier transform. We investigate the kinetic/mathematical conditions under which explicit expressions for the moments of the outlet fluxes and series expansions for their transient values can be obtained. Several important examples are analyzed in detail, leading to simple criteria of instantaneousness for different reactants within a catalytic mechanism. In the case of thin-zone reactors, the criteria are significantly simplified, with equality (within experimental error) of “shifted residence times” of reactants being proposed as the criterion of instantaneousness. This is illustrated for the oxidation of propene on a vanadium oxide catalyst.     

涂料剖析

简要分析了不同涂料体系分析程序,说明了每种涂料剖析体系中应该注意的事项。     

On The Peña–Box Model

Abstract.  Peña and Box [Journal of Americal Statistical Association (1987) Vol. 82, PP. 836–843] proposed a factor model which aimed to explore the possibility of using lower-dimensional series to represent or explain an observed higher-dimensional multiple time series. However, there were no statistics with distribution results with which to build the model. In this paper, we derive a statistical procedure to build the model for stationary and first-order non-stationary series. The main idea, conducted by the canonical correlation analysis between present series and non-present series, is an extension of the concept of the scalar component model proposed by Tiao and Tsay [Journal of the Royal Statistical Society B (1989) Vol. 51, pp. 157–213]. Finally, simulation studies and reanalysis of two real data sets are illustrated.     

MULTILEVEL PCA AND INDUCTIVE LEARNING FOR KNOWLEDGE EXTRACTION FROM OPERATIONAL DATA OF BATCH PROCESSES

A new methodology for monitoring batch processes is presented which is based on analysis of historical operational data using both principal component analysis (PCA) and inductive learning. Historical data of batch operations are analysed according to stages. For each stage, PCA is employed to analyse the trajectories of each variable over all batch runs and groups the trajectories into clusters. The first one or two PCs for all variables at a stage are then used in further PCA analysis to project the operation of the stage onto operational spaces. Production rules are generated to summarise the operational routes to produce product recipes, and to describe variables' contributions to stage-wise state spaces. A method for automatic identification of stages using wavelet multi-scale analysis is also described. The methodology is illustrated by reference to a case study of a semi-batch polymerisation reactor.     

Systematic design of an extractive distillation for maximum‐boiling azeotropes with heavy entrainers

Extractive distillation is one of the most attractive approaches for separating azeotropic mixtures. Few contributions have been reported to design an extractive distillation for separating maximum‐boiling azeotropes and no systematic approaches for entrainer screening have been presented. A systematic approach to design of two‐column extractive distillation for separating azeotropes with heavy entrainers has been proposed. A thermodynamic feasibility analysis for azeotropes with potential heavy entrainers was first conducted. Then, five important properties are selected for entrainer evaluation. Fuzzy logic and develop membership functions to calculate attribute values of selected properties have been used. An overall indicator for entrainer evaluation is proposed and a ranking list is generated. Finally, the top five entrainers from the ranking list have been selected and use process optimization techniques to further evaluate selected entrainers and generate an optimal design. The capability of the proposed method is illustrated using the separation of acetone–chloroform azeotropes with five potential entrainers. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3898–3910, 2015     

结构安全性的模糊评价

结构安全性评价中的模糊性是目前可靠性工程学中的主要难点之一.本文使用失效可能性的概念来描述系统中各事件的状态,用模糊逻辑替代经典的二值逻辑,建立了以模糊语言为参量的失效树分析方法.文中还提出了以模糊失效树分析和模糊综合评判为基础的安全性评价方法.作为初步应用,本文研究了影响焦碳塔结构安全性的诸因素的重要性,评价结果对石油化工设备安全管理有一定参考价值.     

Online Flooding Supervision in Packed Towers: An Integrated Data‐Driven Statistical Monitoring Method

The development of simple and efficient monitoring methods for flooding supervision is an important but difficult task for the safe operation of packed towers. A data‐driven online flooding monitoring method named Bayesian integrated dynamic principal component analysis (IDPCA) is assessed. In the first step of IDPCA, using the fuzzy c‐means clustering method, the multivariate samples collected during plant operation are first classified into several groups. Then, in each subset a dynamic principal component analysis (DPCA) model is constructed to extract the process characteristics. To improve the monitoring performance, Bayesian inference is utilized to combine these DPCA models in a suitable manner. Consequently, the control limits are formulated using the probabilistic analysis. The superiority of IDPCA is illustrated using a lab‐scale packed tower by comparison with the conventional principal component analysis (PCA) and DPCA methods.     

模糊系统的模型化和优化

过程工业中的生产过程变量关系比较复杂，难于获得精确的模型，常使得过程系统的模拟和优化有较大误差。本文提出基于模糊逻辑表述和处理系统变量间的不精确近似关系，使模型方程间的冲突和不协调性趋于最小，模糊目标函数趋于最大。从而实现对模糊系统的模拟和优化。     

ESD在安全联锁应用的优势

就安全联锁系统的逻辑单元而言,ESD和DCS(或PLC)都有逻辑运算功能,都能实现安全联锁功能。文章从设计规定要求、ESD本身优势和现场操作维护方面比较分析,并通过一个应用实例,比较合理的解释了什么情况需要采用ESD并比较全面的分析了ESD比DCS(或PLC)在安全联锁方面应用的优势。     

Automated affinity separation processes

This paper describes the automation of fixed-bed affinity separation techniques for the purification of proteins. The basic requirements of an automated system suitable for carrying out such a separation are detailed together with an introduction to the concept of process optimisation by interactive control. Such systems can continue to optimise separations when operating conditions are variable but require that methods for the on-line analysis of separation performance are available. Such methods require that the levels of particular proteins in the presence of other proteins can be determined and include continuous measurement of enzyme activity and the use of the new technique of rapid chromatographic analysis. The latter technique, which can also be used more generally in the process control of protein purification, is described and its use illustrated.     

A method for robustness analysis of controlled nonlinear systems

This paper presents an approach to analyzing robustness properties of nonlinear systems under feedback control. The core idea is to apply numerical bifurcation analysis to the closed-loop process, using the controller/observer tuning parameters, the set points, and parameters describing model uncertainty (parametric as well as unmodeled dynamics) as bifurcation parameters. By analyzing the Hopf bifurcation and saddle-node bifurcation loci with respect to these parameters, bounds on the controller tuning are identified which can serve as a measure for the robustness of the controlled system. These bounds depend upon the type as well as the degree of mismatch that exists between the plant and the model used for controller design.The method is illustrated by analyzing three control systems which are applied to a continuously operated stirred tank reactor: a state feedback linearizing controller and two output feedback linearizing controllers. While model uncertainty has only a minor effect on the tuning of the state feedback linearizing controller, this does not represent a very realistic scenario. However, when an observer is implemented in addition to the controller and an output feedback linearizing scheme is investigated, it is found that the plant-model mismatch has a much more profound impact on the tuning of the observer than it has on the controller tuning. In addition, two observer designs with different level of complexity are investigated and it is found that a scheme which makes use of additional knowledge about the system will not necessarily result in better stability properties as the level of uncertainty in the model increases. These investigations are carried out using the robustness analysis scheme introduced in this paper.     

A combined heuristic and indicator-based methodology for design of sustainable chemical process plants

The current emphasis on sustainable production has prompted chemical plants to minimize raw material and energy usage without compromising on economics. While computer tools are available to assist in sustainability assessment, their applications are constrained to a specific domain of the design synthesis problem. This paper outlines a design synthesis strategy that integrates two computer methodologies - ENVOPExpert and SustainPro - for simultaneous generation, analysis, evaluation, and optimization of sustainable process alternatives. ENVOPExpert diagnoses waste sources, identifies alternatives, and highlights trade-offs between environmental and economic objectives. This is complemented by SustainPro which evaluates the alternatives and screens them in-depth through indicators for profit and energy, water, and raw material usage. This results in accurate identification of the root causes, comprehensive generation of design alternatives, and effective reduction of the optimization search space. The framework is illustrated using an acetone process and a methanol and dimethyl ether production case study.     

Statistical Modeling of Logic Gates and Flip-Flops for High Speed CMOS Circuits Applications

Process parameter variations of MOSFET and environment parameter variations of the high speed VLSI circuits have become a critical issue in timing analysis. This paper proposes the statistical modeling of basic logic gates and flip-flops used for combinational logic and sequential logic circuits. The basic logic gates and flip-flops model are developed for 32 nm technology. To analyze the accurate performance of the models, we propose for the first time the model which considers both the process and environment parameter variations. The performance parameters of logic gates, such as propagation delay of logic gates and clock to Q delay time, setup time, and hold time for latches and flip-flops are verified with Monte Carlo analysis. The performance of the circuit depends on the propagation delay of logic gates and flip-flops so we propose our models to calculate the accurate performance of the high speed digital circuits. The model shows better accuracy and takes less time than Monte Carlo analysis to produce results. Finally, it is shown that the models can accurately predict all the timing parameters of logic gates and flip-flops.     

复合材料构件宏细观跨尺度分析

本文探讨一种适用于复合材料宏细观间跨尺度分析的细观元方法。细观元法在结构的常规有限元内部设置密集细观单元以反映材料细观构造,又通过协调条件将各细观元结点自由度转换为同一常规有限元自由度,再上机计算。此方法可实现材料细观结构到构件宏观响应的直接过渡分析,而计算单元与自由度又等同一般常规有限元,为解决具有细观结构新材料与构件跨尺度分析提供一种新的有力工具。本文给出用于宏细观跨尺度分析细观元法的基本原理与算式,并以纤维增强复合材料和功能梯度复合材料为例介绍其工程应用。     

Automatic safety analysis of computer-controlled plants

The paper describes an approach to apply the formal technique of model checking to the verification of logic controllers within the safety analysis of processing plants. In order to investigate plant safety in an early design phase in which only basic information is available, we set up plant and controller models in a qualitative and modular fashion. In a first step, the computer-controlled plant is partitioned into functional units, named modules, and the communication between different modules is represented graphically in a so-called process control event diagram (PCED). The PCED can be transformed into a formal model in which the behaviour of each module is described in terms of logical expressions for the modules’ input, state and output variables. Based on the formal model, the method of model checking can be applied to determine algorithmically whether the system fulfils a set of given safety requirements. Specifically, we use the tool symbolic model verifier (SMV) to determine whether the plant can reach states that are, in some sense, critical for the plant operation. The whole approach is illustrated by application to an industrial computer-controlled tube reactor.     

Structural solvability analysis of dynamic process models

The variable structure of dynamic process models is represented by a directed graph termed as the representation graph for the purpose of solvability analysis in this paper. Structural solvability analysis, the determination of the structural differential index and the structural decomposition of the differential–algebraic equations (DAE) model set can be performed using the representation graph. The characteristic features of the representation graph for both index 1 and high index semi-explicit DAE models are presented. Based on the above a novel index reduction procedure for high index models is proposed. The notions and methods are illustrated on simple process examples.     

Performance Analysis of Perturbation‐Based Methods for Real‐Time Optimization

This paper provides a comprehensive performance analysis approach for Real‐Time Optimization (RTO) technologies, which incorporates systematic approaches to estimating bounds on the convergence behaviour and performance effects of on‐line experiments used by a given RTO approach. The performance analysis method is illustrated by an investigation of the conventional two‐phase approach and representative techniques drawn from the three main classes of perturbation‐based RTO methods which attempt to directly compensate for plant/model mismatch through adaptation. The proposed approach is applied to two simulation‐based case studies: a heat exchanger system and a continuous bioreactor.     

基于主成分分析的输出集成反馈网络及其在化工动态过程建模中的应用

针对主成分分析和反馈神经网络的优点，提出基于主成分分析的输出集成反馈网络建模方法，并对训练算法作了推导，在动态化工过程建模中取得满意的效果。     

天然气组分含量分析的不确定度评定

构建天然气含量分析数学模型,研究提出影响天然气分析结果的不确定度来源。结合分析数据实例,说明了不确定度的具体评定过程,对考察分析结果准确度具有指导意义。