工艺管道调节阀组安装形式探讨

从工艺管道调节阀组安装的角度出发,介绍了在石化装置中应用的调节阀的分类和常见形式；并对调节阀组安装管道设计的一般规定进行了详细的论述；结合石油化工生产装置中设备调节阀组安装的实例,对装置中调节阀组常用安装形式的优缺点进行了分析.进而了解如何合理安装调节阀组,确保生产过程安全运行.     

数字式调节阀原理及应用

1.从模拟式调节阀到数字式调节阀众所周知,调节阀又称为调节机构,它和执行机构一起构成执行器,是过程控制系统中一个重要的组成部分。它依据来自调节器的控制信号而改变执行机构输出的角位移或直线位移,并通过调节机构改变被调介质的流量,使生产过程保持满足预定的要求。     

调节阀应用技术

随着自动化装置的更新换代和企业生产自动化水平的提高,不论是“八五”计划新上化工装置,还是化工企业节能改造工程项目,对自动调节阀的应用、选择和品种,尤其是特殊产品的解决都提出了新的要求,各地读者对此反应强烈。为此,我们特邀谈者熟悉的调节阀行家明赐东同志撰写了“调节阀应用技术讲座”,从本期起连续刊登。本讲座共分六讲。第一讲、调节阀的选择,分析了调节阀计算与选择中应着重和加强对调节阀选择的应用技术问题。第二讲,调节阀选型应注意的问题,介绍了对调节阀的全面选择,划分、各类阀的特点及应用中注意的问题。第三讲、特殊产品的选择和应用。第四讲、典型介质、典型场合调节阀的应用。三、四两讲对正在实施中的“八五”项目、企业技术改造项目和引进装置中急待调节阀国产化的设计人员,管理人员和技术工人大有帮助。第五讲、调节阀选择中其它若干问题。第六讲、调节阀安装、维护中的若干问题。本讲座工业应用性强,突出解决调节阀使用中的有关问题,具有新颖性、实用性,拟为提高我国调节阀的应用技术水平起点作用。读者有什么意见或疑难问题可以来信共同讨论。     

化工自动控制过程中气动调节阀的选择与应用

阐述了在化工自动控制过程中气支调节阀的地位以及对一定的控制过程，为了实现高品质的调节，怎样从优造反调节阀的流量特性和各项技术参数。     

化工企业调节阀防火安全故障原因及对策

阐述分析了调节阀阀门漏泄、阀体结合面渗漏、冲量调节阀动作后主调节阀不动作、冲量调节阀回座后主调节阀延迟回座时间过长以及调节阀的回座压力低、频跳和颤振等常见的防火安全故障原因,并针对故障原因提出了对策。     

调节阀技术研究综述

介绍了有关调节阀的发展史,对国内外调节阀技术的发展现状进行了综合评述,并展示了调节阀的最新研究成果。在此基础上,对调节阀的发展趋势进行了展望。     

自动控制设计中调节阀的选型

阐述了在自动控制工程设计中 ,调节阀的选择原则 ,认为调节阀的选择内容 ,应包括结构形式 ,流量特性、流向、执行机构、调节阀的材质和口径等。介绍了各方面选择的要求及各种调节阀的应用场合     

调节阀的现场检验与日常维修

简要叙述了现场检测、调节阀主要性能、调节阀安装时注意要点及调节阀常见故障处理。     

一种新型的调节阀

详细介绍调节阀流量特性种类,调节阀内件结构型式对流量特性的影响,从流路和结构上对直行程和角行程调节阀进行了比较。介绍一种适用于石油、化工等行业的新型(角行程)调节阀——AST防气蚀低噪声调节球阀的主要技术参数、结构特点。     

影响调节阀安全运行的因素及对策

分析了影响调节阀安全运行的因素，如卡堵、泄漏、振荡、阀门定位器故障等，并针对问题分别提出了解决方法，从而大大提高调节阀的可靠性。     

广义运输问题的状态算法

经典运输问题在实际应用中有很大的局限性,推广后可以得到具有运输能力限制、供求量可以变化的广义运输问题。广义运输问题不能用运输问题的表上作业法进行求解。利用网络流算法对广义运输问题进行求解。我们首先将广义运输问题等价化为最小费用循环流模型,然后根据求最小费用循环流的状态算法,构造了求解用于广义运输问题的有效方法。     

基于遗传算法的高职化工院校排课系统的设计与实现

排课问题是一个有约束的、多目标的组合优化问题,并且已经被证明是一个NP完全问题。遗传算法是一种随机搜索算法,非常适合于解决NP问题。本文将遗传算法应用于求解课表问题,采用优化编码结构组合的方法减少排课冲突,降低算法的复杂度;对排课问题的关键参数进行量化分析,针对染色体编码完成各个遗传算子的设计和开发任务,最后集成排课的整体优化算法。     

Integrated Scheduling and Dynamic Optimization of Sequential Batch Processes with Online Implementation

An efficient decomposition method to solve the integrated problem of scheduling and dynamic optimization for sequential batch processes is proposed. The integrated problem is formulated as a mixed‐integer dynamic optimization problem or a large‐scale mixed‐integer nonlinear programming (MINLP) problem by discretizing the dynamic models. To reduce the computational complexity, we first decompose all dynamic models from the integrated problem, which is then approximated by a scheduling problem based on the flexible recipe. The recipe candidates are expressed by Pareto frontiers, which are determined offline by using multiobjective dynamic optimization to minimize the processing cost and processing time. The operational recipe is then optimized simultaneously with the scheduling decisions online. Because the dynamic models are encapsulated by the Pareto frontiers, the online problem is a mixed‐integer programming problem which is much more computationally efficient than the original MINLP problem, and allows the online implementation to deal with uncertainties. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2379–2406, 2013     

Pareto Optimality in a Bicriterion Optimal Stopping Problem

Abstract

This article concerns a characterization of a vector-valued optimal stopping problem with only two reward functions. Under certain conditions, we give an explicit characterization of the Pareto stopping times for the present problem via a scalar-valued double optimal stopping problem. The latter problem is a natural extension of the classical McDonald-Siegel optimal stopping problem with one stopping rule.     

A dual temperature simulated annealing approach for solving bilevel programming problems

This paper presents a dual temperature simulated annealing approach to bilevel programming problems. Bilevel programming problems arise when one optimization problem, the inner problem, is a constraint of a second optimization problem, the outer problem. In this paper, the inner problem is stochastically relaxed with a parameter that can be used as a temperature scale in simulated annealing. Solving the outer problem with simulated annealing as well leads to the dual temperature approach. The technique is demonstrated with several linear, nonlinear, and mixed integer nonlinear bilevel programming problems, including a safe plant layout problem that simultaneously minimizes cost and the damage caused during a worst case scenario accident.     

ON THE MINLP APPROACH FOR OPTIMAL DESIGN OF CHEMICAL ENGINEERING SYSTEMS (I) A GLOBAL OPTIMIZATION METHOD FOR NONCONVEX MINLP PROBLEMS

An algorithm for global optimization of a class of nonconvex MINLP problems is devel-oped and presented in this paper.By partitioning the variables,dual representation of the primal ofsubproblems and outer-approximation strategy are used to develop a representative relaxed iterativeproblem.Then the original MINLP problem is replaced by a series of subproblems and relaxediterative problems.By exploiting the particular form of the nonconvex MINLP problem,the feasibleregion of this problem is explicitly included in the representative problem,thus the inconvenienceencountered with the GBD method can be avoided.The proposed method is illustrated andinterpreted geometrically with an example problem.     

Integration of scheduling and control with online closed-loop implementation: Fast computational strategy and large-scale global optimization algorithm

In this paper, we propose a novel integration method to solve the scheduling problem and the control problem simultaneously. The integrated problem is formulated as a mixed-integer dynamic optimization (MIDO) problem which contains discrete variables in the scheduling problem and constraints of differential equations from the control problem. Because online implementation is crucial to deal with uncertainties and disturbances in operation and control of the production system, we develop a fast computational strategy to solve the integration problem efficiently and allow its online applications. In the proposed integration framework, we first generate a set of controller candidates offline for each possible transition, and then reformulate the integration problem as a simultaneous scheduling and controller selection problem. This is a mixed-integer nonlinear fractional programming problem with a non-convex nonlinear objective function and linear constraints. To solve the resulting large-scale problem within sufficiently short computational time for online implementation, we propose a global optimization method based on the model properties and the Dinkelbach's algorithm. The advantage of the proposed method is demonstrated through four case studies on an MMA polymer manufacturing process. The results show that the proposed integration framework achieves a lower cost rate than the conventional sequential method, because the proposed framework provides a better tradeoff between the conflicting factors in scheduling and control problems. Compared with the simultaneous approach based on the full discretization and reformulation of the MIDO problem, the proposed integration framework is computationally much more efficient, especially for large-scale cases. The proposed method addresses the challenges in the online implementation of the integrated scheduling and control decisions by globally optimizing the integrated problem in an efficient way. The results also show that the online solution is crucial to deal with the various uncertainties and disturbances in the production system.     

Optimal synthesis of a system of simple distillation columns

The problem of optimal superstructure-based synthesis of a system of distillation columns is formulated as a mixed integer nonlinear programming problem, and a branch-and-bound method is suggested for solving this problem. A two-stage approach to the problem is described, and the corresponding computational algorithm is presented.     

浅谈ABS塑料件涂装质量的提升

通过对公司目前ABS件涂装时存在的涂膜缺陷,从毛坯注塑问题、毛坯材质问题及施工产生的涂膜问题3方面进行分析,采取有效措施,从而提高ABS件涂装质量。     

MINLP formulations for solving strip packing problems in LCD mother glass production

Mother glass production for liquid crystal displays involves the cutting of small rectangles from a large rectangle (strip) to minimize the length of the strip used. This is called the strip packing problem. The main concept for formulating this problem is to generate cutting patterns that can be used to produce items from the strip. This problem is a non-convex mixed integer nonlinear programming (MINLP) problem due to the bilinear terms in the demand and objective function. To obtain global optimal solutions, this problem should be transformed into several linear forms. Numerical examples based on the strip packing problem in LCD mother glass production are provided. Different objective functions for two problems are presented and compared.