PLC在造纸机负荷分配控制中的应用

介绍了纸机变频传动中负荷分配问题产生的原因及影响,同时介绍了PLC控制负荷分配的原理、方法及应用。     

多目标差分进化在热连轧负荷分配中的应用

提出一种基于差分进化算法的多目标进化算法, 该算法个体的选择是通过非支配排序和拥挤度距离进行综合考虑. 保证了算法收敛到Pareto最优解集的同时, 提高了最优解个体分布的多样性. 通过与非支配排序遗传算法Ⅱ(NSGA Ⅱ)算法进行仿真对比, 结果显示基于拥挤度排序的多目标差分进化算法在收敛性和Pareto最优解集分布的多样性上均优于NSGA Ⅱ算法. 最后将其引入到热连轧负荷分配优化计算中, 给出了目标函数的表达方式, 对多目标进化算法在热连轧负荷分配计算中的应用进行了研究.     

火电厂具有高次特性曲线机组的经济负荷分配

本文根据微增率与机组负荷存在一定的关系，提出在λ－Ｐ坐标图上用比例求根法寻找最优的λ。然后求出各机组的最优分配负荷Ｐ１，此法用于电厂经济负荷分配的计算，对于五次以下的机组特性曲线不但收敛速度快，而且所占微机内存少，不但适用于离线计算，也适用于在线控制与分配。     

改进型复杂过程全局进化算法在热连轧负荷分配中的应用

为实现热连轧精轧机组负荷分配的优化设定,提出一种具有柔性框架结构的改进型复杂过程全局进化算法.该算法部分地借用了分散搜索原则,在通用框架中嵌入具有搜索机制的子方法;利用无限折叠映射混沌模型和局部搜索法,分别对初始种群的生成和"超越"深度搜索进行改进以提高最优解的求解效率.实验结果表明,该算法能够使用较少的参数完成负荷分配优化问题的可行解搜索,具有较好的时效性,是局部和全局搜索的有机体.     

先进控制技术在VCM合成负荷分配中的应用探讨

为实现VCM合成装置负荷自动分配功能,实现装置提质增效的目标,该文以VCM合成工序为应用背景,探讨采用多变量模型预测控制、智能专家控制以及软测量策略相结合的先进控制技术建立VCM合成先进控制系统,实现了VCM合成负荷自动分配的目标,提高了装置的效益及效率。实践证明,先进控制技术在VCM合成装置的应用能取得显著的效果。     

PLC与变频器在纸机负荷分配中的应用

举例说明了造纸机变频传动中负荷分配产生的原因、造成的影响以及用程序实现负荷分配的设计原理.结合工程实例,重点介绍了造纸机在交流变频传动控制的情况下,用PLC的通讯控制功能和用高性能变频器的直接转矩控制功能实现负荷分配的原理及方法.     

修正指数曲线在电力负荷预测中的应用

在现有文献研究的基础上，对修正指数曲线预测法作了进一步研究，给出了修正指数曲线参数估计的一种新方法。该方法将最优化方法与回归方法结合在一起，利用最优化理论中的区间搜索和一维搜索得到一系列 值，利用回归方法可求得与其相对应的一系列a和b的值，当 取最优 时，a和b 便得到最优值 和 。经示例计算表明，这种改进的预测方法具有较高的精度。     

轧机辊缝自动控制

莱钢目前主要产品为型钢、棒材、螺纹钢、带钢、宽厚板等,其中需要在线轧机调整辊缝的有带钢和宽厚板,在轧制过程中需要根据影响轧件质量的外部条件的变化来自动调整轧机辊缝,以此补偿轧制偏差,达到目标产品辊缝的恒定。辊缝自动控制系统是轧机控制的核心内容,其控制精度的高低直接影响产品质量。本文将对其轧机自动辊缝控制系统的原理及实际应用进行详细说明。     

基于新型免疫粒子群优化的热连轧负荷分配策略*

针对带钢热连轧精轧中的负荷分配问题,提出了一种新型的优化策略。首先提出了一种新型的免疫粒子群混合优化算法,通过克隆选择算子来调节群体的浓度,实现混合算法的个体高亲和力和群体的多样性; 然后通过提出的混合算法对负荷分配进行优化,得到优化的压下量数据,通过这些数据建立了计算负荷分配输出的人工神经网络。实验表明,提出的混合算法和负荷分配优化策略给出了很好的优化效果,能有效地指导实际生产应用。     

热连轧精轧负荷分配优化的多目标反向迭代法

在求解热精轧负荷分配优化的过程中,针对目标函数中加权系数难以确定的问题,提出多目标反向迭代法(multi-objective inversion iteration algorithm,MOII),该法通过数值迭代的方式实现了热精轧机组负荷分配的多目标优化.首先,在综合考虑板形、板厚精度和质量的基础上,设计负荷分配优化的多目标函数;然后,基于轧制力能参数与轧机入口和出口板带厚度的单调性关系,设计MOII算法,并对MOII算法的合理性及异常情况进行分析,给出其计算流程;最后,基于实际生产数据进行仿真,结果表明,MOII算法不仅能够实现负荷分配的多目标优化,而且求解速度快、精度高,体现出良好的在线应用前景;与其他方法得到的解相比,MOII算法求得的解有更好的性能.     

基于负荷曲线的配网支线负荷电流计算研究与应用

本文提出了一种基于负荷曲线的配网支线负荷电流计算方法,计算出配网线路的支线负荷电流,为运行人员、调度人员提供分析和处理事故的依据,也为配网规划等业务提供了理论基础。本文采用的方法为：通过一条10kV配电网线路上所有配变节点的电量计算出各配变节点平均电流,然后按照叠加法推导出各条支线的负荷电流。作者根据理论依据,以兴义城区配电网线路为实例进行验证,证明该计算方法是有效的并能实际应用。最后对计算方法进行实际应用,通过python编程编写了一套应用程序,用在兴义城区配电网调度运行中,取得了很好的效果,解决了调度人员、运行人员对配变及支路不能监视的问题,减少事故处理的困难程度和风险,为配网运行管理提供了一种新的思路     

Minimizing energy consumption in reverse osmosis membrane desalination using optimization-based control

This work focuses on the design and implementation of an optimization-based control system on an experimental reverse osmosis (RO) membrane water desalination process in order to facilitate system operation at energy optimal conditions. A nonlinear model for the RO process is derived using first principles and the model parameters are computed from experimental data. This model is combined with appropriate equations for reverse osmosis system energy analysis to form the basis for the design of a nonlinear optimization-based control system. The proposed control system is implemented on UCLA’s experimental RO desalination system and its energy optimization capabilities are evaluated.     

The effect of load distribution within military load carriage systems on the kinetics of human gait

Military personnel carry their equipment in load carriage systems (LCS) which consists of webbing and a Bergen (aka backpack). In scientific terms it is most efficient to carry load as close to the body's centre of mass (CoM) as possible, this has been shown extensively with physiological studies. However, less is known regarding the kinetic effects of load distribution. Twelve experienced load carriers carried four different loads (8, 16, 24 and 32 kg) in three LCS (backpack, standard and AirMesh). The three LCS represented a gradual shift to a more even load distribution around the CoM. Results from the study suggest that shifting the CoM posteriorly by carrying load solely in a backpack significantly reduced the force produced at toe-off, whilst also decreasing stance time at the heavier loads. Conversely, distributing load evenly on the trunk significantly decreased the maximum braking force by 10%. No other interactions between LCS and kinetic parameters were observed. Despite this important findings were established, in particular the effect of heavy load carriage on maximum braking force. Although the total load carried is the major cause of changes to gait patterns, the scientific testing of, and development of, future LCS can modify these risks.     

Design, implementation and testing of an intelligent knowledge-based system for the supervisory control of a hot rolling mill

This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems.     

BIM-based investigation of total energy consumption in delivering building products

Considerable efforts have been made to reduce buildings’ operational energy use over the last decades, but little attention has been paid to reduce the material transportation and construction energy. Focusing only on the operation phase forgoes the opportunity to reduce other building-related energy consumption, and even if the environmental impacts arising from construction and transportation are small as compared to the operation phases, its cumulative impact at the national level is of concern.The energy consumed by a building is divided into two parts embodied energy and operation energy. Further, the embodied energy is constituted of energy intensity of materials, energy consumed during transportation and energy consumed for construction. This paper proposes a methodology to integrate embodied energy consumption into a BIM platform and provides a seamless analysis based on available information. Plug-ins are developed to fulfill a convenient linkage between the BIM model and external databases. Simulation models are created, which can be used as templates for energy optimization during transportation and construction. By analyzing different resource combination scenarios, lower energy consumption can be achieved.     

Evaluating the energy consumption and the silicon area of on-chip interconnect architectures

Sophisticated on-chip interconnects using packet and circuit switching techniques were recently proposed as a solution to non-scalable shared-bus schemes currently used in Systems-on-Chip (SoCs) implementation. Different interconnect architectures have been studied and adapted for SoCs to achieve high throughput, low latency and energy consumption, and efficient silicon area. Recently, a new on-chip interconnect architecture by adapting the WK-recursive network topology structure has been introduced for SoCs. This paper analyses and compares the energy consumption and the area requirements of Wk-recursive network with five common on-chip interconnects, 2D Mesh, Ring, Spidergon, Fat-Tree and Butterfly Fat-Tree. We investigated the effects of load and traffic models and the obtained results show that the traffic models and load that ends processing elements has a direct effect on the energy consumption and area requirements. In these results, WK-recursive interconnect generally has a higher energy consumption and silicon area requirements in heavy traffic load.     

具有负载和流量控制的软件分发系统设计与实现

通过分析软件分发过程中负载控制和流量控制的关键点,在原型系统的基础上设计并实现了一个基于可激活RMI框架的应用软件分发系统,系统可以实现B/S模式下的主动软件分发。实验结果表明,系统可以在较低负载下执行流量可控的大规模应用软件分发。     

EMS系统在钢铁厂能源中心的应用

介绍了钢铁厂能源中心采用计算机网络构成的集中管理和远程遥控遥测的能源管理系统(简称EMS系统),分析了系统的软硬件结构、数据的采集和监控理念,并对该系统主要功能的实现进行了描述。     

Physics-based machine learning method and the application to energy consumption prediction in tunneling construction

Representing causality in machine learning to predict control parameters is state-of-the-art research in intelligent control. This study presents a physics-based machine learning method providing a prediction model that guarantees enhanced interpretability conforming to physical laws. The proposed approach encodes physical knowledge as mapping relationships between variables in engineering dataset into the learning procedure through dimensional analysis. This derives causal relationships between the control parameter and its influencing factors. The proposed machine learning method's objective function is further improved by the penalty term in the regularization strategy. Verifications on the energy consumption prediction of tunnel boring machine prove that, the established model accords with basic principles in this field. Moreover, the proposed approach traces the impact of three major factors (structure, operation, and geology) along the construction section, offering each component's contribution rates to energy consumption. Compared with several commonly used machine learning algorithms, the proposed method reduces the need for large amounts of training data and demonstrates higher accuracy. The results indicate that the revealed causality and enhanced prediction performance of the proposed method advance the applicability of machine learning methods to intelligent control during construction.