石化炼油企业原油库存的动态管理

石化炼油是一个流程工业，原油的流动是连续的。为支持动态生产排产与调度的需要，对原油库存信息进行动态管理是非常必要的。这就要求原油库存管理能提供任何时刻的库存状态，这是一个极大的挑战。基于离散事件动态系统理论提出了一个有效的方法。通过这个方法，只需要记录本文中定义的时间与事件点的库存信息。通过这些信息，再经过一些有效地计算就可获得任何时刻的库存状态。这一方法是基于Window环境下实现的。     

COMPOUND DYNAMIC EVENT METAMODELS FOR ELECTRONIC ASSEMBLY LINE SYSTEMS

In the assembly line systems of the electronics industry, production controls based on steady-state conditions have proved ineffectual in coping with dynamic events, such as machine breakdowns, part supply shortages, and high priority job order processing, which can occur individually or simultaneously.

There are few tools that give results quickly as to how many assemblies will be delayed by a dynamic event and how long it will take to recover from the impact. Computer simulation is available, but its lengthy execution time has hindered its application in real time.

Previous research discovered that the patterns of these dynamic events can be represented by metamodels in the solution form of first order systems. In this paper, these results are unified and it is further shown that compound dynamic event metamodels can be developed from the individual metamodels using linear additivity. These metamodels are fit to the output from the simulation; and the resulting equations can be used in real time to measure the number of assemblies that are delayed due to the dynamic events.

To demonstrate the potential application of compound dynamic event metamodels for decision making in real-time production control, a Decision Support System (DSS) is described that contains the dynamic metamodels in its model base. With this program, the impact of the dynamic events on production can be obtained virtually instantaneously. A case study is presented to support this conclusion.     

Condition-based dynamic maintenance operations planning & grouping. Application to commercial heavy vehicles

This paper aims at presenting a method to optimize the maintenance planning for a commercial heavy vehicle. Such a vehicle may be considered as a multi-components system. Grouping maintenance operations related to each component reduces the global maintenance cost of the system. Classically, the optimization problem is solved using a priori reliability characteristics of components. Two types of methods may be used, i.e. static or dynamic methods. Static methods provide a fixed maintenance planning, whereas dynamic methods redefine the groups of maintenance operations at each decision time. Dynamic procedures can incorporate component information such as component states or detected failures. For deteriorating systems, reliability characteristics of each component may be estimated thanks to deterioration models and may be updated when a degradation measure is available. This additional information on degradation features allows to better follow the real state of each component and to improve the maintenance planning.     

用分解—集结法研究复杂转子—轴承系统的稳定性

本文探讨应用大系统稳定性理论的分解—集结法研究复杂转子—轴承系统的运动稳定性问题。与目前常采用的传统分析方法，如特征根判稳法及派生的各种稳定性判据相比，这种方法的独到之处在于其不仅能提供整个系统的稳定性信息，还能反映子系统及其复合关系对整体系统稳定性的作用及影响等信息。这是传统的整体直接处理方式较难达到的。本文举出几个实例验证了这一系统工程方法的有效性和独特性，其直接应用背景是大型汽轮发电机组轴系的稳定性问题。     

结构物理参数时域识别的子结构方法研究

研究了输入、输出信息皆不完备情况下的结构参数识别以及荷载反演问题。阐述了一种通用的子结构动力方程及其参数识别方程建立的基本原理和方法,并针对实际工程检测中子结构参数识别方程的输入特性,分别采用一种与之相适应的分解反演算法或统计平均算法。子结构技术与分解算法或统计平均算法的有效结合,为有限测点条件下的结构参数识别及荷载反演问题提供了一个较好的解决方案。大量的数值计算结果表明,本文提出的方法具有很好的参数识别精度及荷载反演效果。     

Fault detection and identification in dynamic systems with noisy data and parameter/modeling uncertainties

A probabilistic approach is presented which can be used for the estimation of system parameters and unmonitored state variables towards model-based fault diagnosis in dynamic systems. The method can be used with any type of input–output model and can accommodate noisy data and/or parameter/modeling uncertainties. The methodology is based on Markovian representation of system dynamics in discretized state space. The example system used for the illustration of the methodology focuses on the intake, fueling, combustion and exhaust components of internal combustion engines. The results show that the methodology is capable of estimating the system parameters and tracking the unmonitored dynamic variables within user-specified magnitude intervals (which may reflect noise in the monitored data, random changes in the parameters or modeling uncertainties in general) within data collection time and hence has potential for on-line implementation.     

Analysis and optimization of weighted voting systems consisting of voting units with limited availability

The voting system studied consists of n voting units each either providing a binary decision (0 or 1) or abstaining from voting. The system output is 1 if the cumulative weight of all 1-opting units is at least a pre-specified fraction τ of the cumulative weight of all non-abstaining units. Otherwise, the system output is 0.In this paper, we study the effect of limited availability of the voting units on the entire voting system reliability. Two different types of systems are considered. In the system of type 1, the absence of unit output (unit unavailability) is interpreted by the system as abstention from voting. In the system of type 2, the unavailable state of the voting unit and its abstention from voting can be distinguished and the system parameters can be adjusted to optimize its performance for each combination of available units.There are two ways to improve reliability of weighted voting system consisting of units with the given output probability distribution: optimization of system parameters (weights of units and threshold factor value) and units availability enhancement (for example, by choosing proper maintenance policy). This paper shows a method of incorporating information about units' availability into a procedure for determining the optimal system parameters. It also presents a method for determining indices that measure importance of voting units availability for both types of systems. These indices indicate voting units for which efforts of availability enhancement are the most beneficial from the entire system reliability improvement point of view.The approach is based on using a universal generating function technique and optimization procedure presented in [5]. Examples are presented.     

Dynamic optimization of chemical engineering problems using a control vector parameterization method with an iterative genetic algorithm

An approach that combines genetic algorithm (GA) and control vector parameterization (CVP) is proposed to solve the dynamic optimization problems of chemical processes using numerical methods. In the new CVP method, control variables are approximated with polynomials based on state variables and time in the entire time interval. The iterative method, which reduces redundant expense and improves computing efficiency, is used with GA to reduce the width of the search region. Constrained dynamic optimization problems are even more difficult. A new method that embeds the information of infeasible chromosomes into the evaluation function is introduced in this study to solve dynamic optimization problems with or without constraint. The results demonstrated the feasibility and robustness of the proposed methods. The proposed algorithm can be regarded as a useful optimization tool, especially when gradient information is not available.     

Buffers and backup machines in automatic transfer lines

Buffer storage of the work-in-process inventory, decouples successive stages of automatic transfer production lines, assuring partial operability under machine failure. Certain special features such as secondary (standby) machines, special maintenance and diagnostic systems can lengtben the uptime or shorten the downtime of individual stages. When special features for K stages and spaces for M buffers are available, it is of great interest to system designers to know which stages should have the special features and where the buffer spaces should be inserted to maximize the line output rate. This paper addresses itself to such design problems. A bivariate dynamic programming procedure is developed which provides a layout for the buffers and an allocation of special features, maximizing the line output rate as defined by Buzacott (1967, 1968). The Buzacott formula is based on a heuristic argument which provides, in general, an upper bound on the true system output rate.     

Laser with a nonlinear mirror: application for improving the output power stability of a cw laser

We put forward a new method for improving the output power stability of a cw laser. The basic idea is to replace the output mirror of a laser with a nonlinear mirror that is formed by a dispersive nonlinear Fabry-Perot étalon. Based on the semiclassical dynamic model for this system, first we derive the static conditions for this laser operating with stabilized output power, then we study the dynamic responses of output power to gain fluctuations. Both static and dynamic results show that, compared with normal lasers, the output power stability of our laser can be improved significantly when the output power fluctuations are caused by the fluctuations of the gain. The improvement of the output power can be explained by the fact that there exists an optical servoloop in this laser that is produced by the nonlinear mirror.     

Ultrasonic dynamic focusing using an analog FIFO and asynchronoussampling

A dynamic focusing method which employs an analog FIFO (AFIFO) for signal sampling and storage is proposed. The delay control on the ultrasound pulse echo at each array element for focusing delay compensation is achieved by the nonuniform sampling process, as suggested previously in a full digital beamforming system called Pipelined Sampled-Delay Focusing (PSDF). In the new focusing method, an analog sampling device, AFIFO, is used to sample and store values of the pulse echo as it arrives from each imaging point at each array element. Due to the first-in first-out operation of each AFIFO, all the samples for each imaging point along the axis of the beam are arranged at the same output position required on each channel and will be output simultaneously by a uniform output clock. Except for the nonuniform sampling control, all processing in the new dynamic beamforming method is carried out exactly the same as in conventional analog imaging systems. The advantages of the new system are that the sampling rate and hardware complexity for dynamic focusing can be greatly reduced by employing nonuniform sampling and analog signal processing. The performance and validity of the new method are verified experimentally     

BP神经网络在测试系统动态补偿中的应用

测试系统的非线性动态补偿是仪器技术的一个重要方面．采用BP神经网络对测试系统进行动态补偿．BP神经网络的结果决定于网络输入、隐层和输出节点．由于其非线性映射特性,BP神经网络完全能够反映测试系统的动态响应特性．采用了收敛速度较快的递推预报误差算法训练神经网络．试验结果表明,BP神经网络的特性完全能够满足测试系统的动态补偿要求．表明本文的方法是有效的．     

Framework for flexibility in dynamic supply chain management

Effective Supply Chain Management (SCM) is a pivotal issue in the dynamically changing business environment. Dynamic SCM requires integrated decision-making amongst autonomous chain partners with effective decision information synchronization amongst them. By exploiting flexibility in supply chain structures, better performance can be achieved. Similarly, by judiciously employing decision flexibility and the associated dynamic control amongst autonomous supply chain nodes, many improvements are possible. The paper presents a study on the role of different flexibility options (i.e. no flexibility, partial flexibility and full flexibility) in a dynamic supply chain model based on some key parameters and performance measures. Supply chain flexibility has significant potential and needs a greater research attention. The paper attempts to advance the knowledge of dynamic control on effective flexibility exploitation in the context of dynamic supply chains. A simulation model of a dynamic supply chain is used for this purpose. The key results are highlighted along with industry implications. Here each supply chain node involves decision-making. Based on the order and sample information available from the immediate buyers or customers, the supplier selection decisions are dynamically made. A seemingly good decision at a stage based on local information often ends up as detrimental not only to the total chain cost, but also to the total costs of the node itself. These observations are important for the designers and managers of the flexible supply chain systems to arrive at appropriate types and a judicious level of flexibility to attain significant improvements in total cost reduction. The modelling of dynamic supply chains with a focus on flexibility can offer enormous potential to the industry. This paper addresses this interesting and challenging domain.     

The optimal frequency estimation of a noisy sinusoidal signal

A signal-processing method is proposed whereby the frequency of a noisy sinusoidal signal can be estimated optimally. The criterion for optimum performance is the minimum observation time for a given error or the minimum error for a given observation time when the same signal-to-noise condition prevails. Three methods of analyzing the instance of the transition of the signal through a selected level in a given direction can be used to determine the frequency. These methods have been simulated, and the results give a comparison of the measurement errors for the various methods for different signal-to-noise ratios and observation times. The first two methods utilize only part of the available data for frequency measurements. The third method uses all available information (e.g., all the positive zero crossings) in order to arrive at a better estimation of the required information in a given observation time or to use less measuring time for a given error. These results illustrate the superior performance of the third method. The amount of calculations that have to be done to extract the required information is a disadvantage, but the computing power and speed of modern systems make this problem irrelevant when measuring the precision frequency of a proton magnetometer. This point must be taken into consideration, though, when higher-frequency signals have to be processed using this method     

自动化立体仓库出入库决策系统的开发与仿真

在对作业方式、出入库作业方式分析的基础上,开发出了自动化立体仓库的出入库决策系统.系统管理层用Visual Basic 6.0编程语言开发,可实现对系统参数的初始设置,记录和查询出入库信息,货位优化管理和堆垛机的优化调度.监控仿真层的开发选用了组态软件组态王6.5,可实现对立体仓库的输入输出作业过程的动态模拟,并对系统运行结果进行曲线分析.系统数据库平台的构建选用的是Access 2000数据库软件,该数据库平台为管理层和监控层搭建了数据桥梁.进行货位优化管理时要综合考虑分布描述指标、库存量指标、出库分发效率指标这三个指标;按照堆垛机作业路线的优先级来安排堆垛机作业指令;综合考虑货位管理、堆垛机调度和输送机的运送管理这三个问题.通过仿真试验证明了可以得到系统进行优化决策方案.     

The Parametric Identification of a System with Unclear Input information

1 IntroductionIn many cases, it is needed to identify the palmeters of a system. A number of parametricidentification methods have been developed such as the Free--decay vibration method and theMode and vibration pattern analysis methodll&2]. In recent decaaes, for the resoluhon of nonlinear parameter idenhficahon Problems, some more adVanced techniques have been adopted. Forexample, using the adaptive system or expeft identifier system as a tool for non-linear systemidentification[3], and u…     

Principal components analysis in sensitivity studies of dynamic systems

Local sensitivity analysis is a modeling tool for determining the effects of single parameter variations on the output of a first order differential system. To determine the effects of multi-parameter variations, the local sensitivity matrix can be used in a first order Taylor series to approximately model the variance of the system output. For dynamic systems, a principal component analysis based on this time varying approximation reveals the evolution of the directions and magnitudes of greatest variation of the system output derived from input variability in the parameters. Such an analysis acts as a means of modeling the robustness of dynamic differential systems.     

A general identification technique for nonlinear differential equations of motion

This paper develops and demonstrates by computer simulations new nonlinear system stochastic techniques to determine the amplitude-domain and frequency-domain properties of nonlinear systems as described in nonlinear differential equations of motion. From measurements of input excitation data and output response data, this new method, based upon multiple-input/single-output (MI/SO) linear analysis of reverse dynamic systems, allows for the efficient identification of different nonlinear systems. Nonlinear systems simulated here include Duffing, Van der Pol, Mathieu, and Dead-Band systems. Features of this new method are: (1) it can be implemented using established MI/SO linear procedures and computer programs; (2) it determines nonlinear system amplitude properties separate from nonlinear system frequency properties; (3) it quantifies relative contributions from different nonlinear terms by using appropriate coherence functions; (4) it gives results that are independent of the input or output probability distributions, spectral properties, and input excitation levels.     

Performance evaluation of dynamic scheduling approaches in vehicle-based internal transport systems

This paper studies the performance of static and dynamic scheduling approaches in vehicle-based internal transport (VBIT) systems and is one of the first to systematically investigate under which circumstances, which scheduling method helps in improving performance. In practice, usually myopic dispatching heuristics are used, often using look-ahead information. We argue more advanced scheduling methods can help, depending on circumstances. We introduce three basic scheduling approaches (insertion, combined and column generation) for the static problem. We then extend these to a dynamic, real-time setting with rolling horizons. We propose two further real-time scheduling approaches: dynamic assignment with and without look-ahead. The performances of the above five scheduling approaches are compared with two of the best performing look-ahead dispatching rules known from the literature. The performance of the various approaches depends on the facility layout and work distribution. However, column generation, the combined heuristic, and the assignment approach with look-ahead consistently outperform dispatching rules. Column generation can require substantial calculation time but delivers very good performance if sufficient look-ahead information is available. For large scale systems, the combined heuristic and the dynamic assignment approach with look ahead are recommended and have acceptable calculation times.     

基于地球重力法的低频加速度计校准

ISO 16063-16描述的地球重力法只能用于低频加速度计灵敏度幅值静态校准, 无法用于灵敏度幅值与相位的动态校准。采用机器视觉方法测量激励加速度相位,并得到对应时刻的加速度计输出信号相位,该方法可同时实现基于地球重力法的灵敏度幅值与相位动态校准。该方法测量时由转台为被校加速度计提供峰值恒定为1g的正弦激励加速度,有效避免了低频时微小激励加速度引起的加速度计输出低信噪比信号对校准精度的影响。实验结果表明,地球重力法可实现从静态(DC)至10Hz范围内的灵敏度幅值与相位高精度校准。