选煤厂CPS及其生产调度研究

发布时间：2019-03-27 15:18

【摘要】：随着智慧矿山的发展,选煤厂对智能化的要求不断提高。当前选煤厂控制系统中各子系统的控制和信息采集相互独立,因此无法将整个生产过程作为整体进行建模,并通过子系统之间的实时交互完成整个系统的优化控制。因此,研究智能化选煤厂及其生产调度十分必要。本文以兖州兴隆庄选煤厂为例,将CPS引入选煤厂中,对选煤厂CPS模型及生产调度方法进行了研究。针对当前选煤厂PLC系统中各控制子系统相互独立的问题,结合MAS特征以及PLC网络结构,建立基于语义agent的选煤厂CPS模型。分析了选煤厂CPS中各主要车间代理结构和相互之间的关系以及车间管理agent相互交互过程。为了解决选煤厂CPS的智能调度问题,提出基于订单窗口期的、以经济效益最大化为目标的静态生产调度模型,并利用TS-PSO对调度模型进行了求解。将PSO算法与TS算法结合,克服了粒子群过早陷入最优及TS算法过分依赖初始解的缺点。通过理论分析证明了该静态调度模型符合选煤厂生产线的实际情况,并通过实验仿真表明了利用禁忌粒子群算法求解静态调度模型的有效性。考虑到选煤厂实际的动态生产环境,分析了引起物理环境动态变化的几种因素,提出了设备异常及紧急订单到达两种动态因素情况下的选煤厂CPS动态调度策略。在环境发生动态变化时,通过选煤厂CPS中订单agent、调度agent、车间管理agent及车间内其他agent之间的协作与合作完成动态调度。实验仿真了在静态调度结果的基础上有紧急订单到达时的动态调度,结果证明了调度策略的可行性。本文的研究成果表明了CPS应用在选煤厂中可以解决当前PLC集控系统存在的问题,满足选煤厂对系统智能化的需求,并可以通过优化调度提高选煤厂生产效率。
[Abstract]:With the development of intelligent mine, the requirement of intelligence of coal preparation plant is increasing. At present, the control and information collection of each subsystem in the coal preparation plant control system is independent of each other, so the whole production process can not be modeled as a whole, and the optimization control of the whole system can be completed through the real-time interaction between subsystems. Therefore, it is necessary to study the intelligent coal preparation plant and its production scheduling. Taking Xinglongzhuang Coal preparation Plant in Yanzhou as an example, this paper introduces CPS into the coal preparation plant, and studies the CPS model and production scheduling method of the coal preparation plant. In view of the problem that each control subsystem is independent of each other in the PLC system of coal preparation plant at present, combined with the characteristics of MAS and the network structure of PLC, the CPS model of coal preparation plant based on semantic agent is established. The agent structure and the relationship among the main workshops in CPS of coal preparation plant are analyzed, and the interaction process of agent in workshop management is also analyzed. In order to solve the intelligent scheduling problem of CPS in coal preparation plant, a static production scheduling model based on order window period and aiming at maximization of economic benefit is put forward, and the scheduling model is solved by using TS-PSO. The PSO algorithm and the TS algorithm are combined to overcome the shortcomings of premature particle swarm optimization and over-dependence on the initial solution of the TS algorithm. Through theoretical analysis, it is proved that the static scheduling model accords with the actual situation of coal preparation plant production line, and the effectiveness of using Tabu particle swarm optimization algorithm to solve the static scheduling model is proved by experimental simulation. Considering the actual dynamic production environment of the coal preparation plant, several factors causing the dynamic change of the physical environment are analyzed, and the dynamic dispatching strategy of CPS for the coal preparation plant under the circumstances of abnormal equipment and the arrival of emergency orders are put forward. When the environment changes dynamically, the dynamic scheduling is accomplished through the order agent, scheduling in CPS of the coal preparation plant, and the cooperation and cooperation between the agent and other agent in the workshop, which are managed by the agent, workshop. The dynamic scheduling of emergency order arrival is simulated on the basis of static scheduling results. The results show that the scheduling strategy is feasible. The research results of this paper show that the application of CPS in the coal preparation plant can solve the problems existing in the current PLC centralized control system, meet the demand of intelligentization of the system in the coal preparation plant, and improve the production efficiency of the coal preparation plant by optimizing the dispatching.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TD94;TP301.6

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