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大型混凝土搅拌站管控系统的研究与开发
Research and Development of Management and Control System of Large Concrete Mixing Plant
【作者】 周俊；
【导师】 王立新；
【作者基本信息】 郑州大学 ， 机械设计及理论， 2012， 硕士
【摘要】 随着预拌混凝土生产规模的扩大,人们对大型混凝土搅拌站管控系统提出了更高的要求,而目前大型混凝土搅拌站管控系统信息化、智能化滞后,对生产效率和产品质量构成了较大的影响。为改善此种现状,本文提出了一套基于"Server+IPC+PLC"配置方式的大型混凝土搅拌站管控系统。本文所设计的系统构架分为总站和分站两层,采用B/S和C/S的混合模式进行外部和内部的访问。总站对分站采用分布式集中控制的方式来实现集中管理,主要用来向分站传递订单内容、配方详情等信息；各个分站对总站采用C/S方式来进行数据访问,主要向总站传递各个分站的原料库存,订单完成情况等信息；分站管控系统与底层的PLC采用串口等多种通信方式进行连接,主要向底层PLC控制模块传递相关控制指令和控制参数；外部互联网与搅拌站管控系统采用B/S方式来实现连接,用户可以通过范围其服务器,在相关网页上完成下订单等操作。针对多个混凝土搅拌站供应多个工地时,预拌混凝土输送车派车排序这一难题,本文采用基因遗传算法对派车流程进行优化,对已有的相关理论进行了改进,并且提出了简易Pareto Front解的求解方法。同时,运用实际算例对该派车子功能系统的实际效果进行了验证。
【Abstract】 As the expansion of the scale of RMC(Ready-Mix Concrete) production, higher requirement is proposed to the management and control system of large concrete mixing plant. But nowadays,many management and control incorporated systems of large concrete mixing plant are lagging behind in informatization and intellectualization, which affect the production efficiency and quality very much.In order to change this situation,this thesis proposes a collocation method of the management and control system of large concrete mixing plant which bases on "Server+IPC+PLC".The framework of the system consists of tow layers which are the master station and the substations, and between which by using mixed model of C/S and B/S to access both outside and inside.By using distributed centralized control technology, the master station can manage the substations and transfer informations like content of the indents, details of formula and so on. The substations can visit the master station by C/S way and transfer informations like stocks of materials, accomplishment of indents and so on.The substations transfer orders and parameters to its PLC by using serial port and other ways.Customers can place an order and do other things on the web sites on internet by B/S way.Directing to the problem of dispatch plan for several RMC plants supplying several job sites, this thesis uses method of using Genetic Algorithms to optimize the dispatch plan, and improves the relevant theories, and propose the simple method to get Pareto Front solutions.At the same time, testing the performance of subfunction of dispatching system by using actual examples.