船舶中央冷却系统仿真与智能控制研究

发布时间：2018-03-14 10:06

本文选题：中央冷却系统　切入点：建模仿真　出处：《上海交通大学》2015年硕士论文　论文类型：学位论文

【摘要】：中央冷却系统是船舶动力装置的重要组成部分,系统通过冷却水的循环作用,对各受热部件和换热设备进行冷却,降低其所受到的热负荷,以确保各设备正常可靠的运行。冷却系统的性能优劣直接影响到动力装置的工作性能,从而对船舶的可靠性和经济性产生影响。另一方面,随着能效设计标准的生效,也对船舶冷却系统提出了更高的要求。为此,开展船舶中央冷却系统的仿真研究,采用变频控制方法,对改善系统的工作性能,实现船舶的节能减排,具有重要意义。本文首先介绍船舶中央冷却系统的常见形式和组成结构,根据冷却介质的不同,将系统划分为高温淡水系统、低温淡水系统和海水系统,并论述了主要设备的工作原理。依据中央冷却系统的运行过程,利用传热学和流体力学的相关理论,建立系统的动态数学模型。其次,以动态数学模型为理论依据,利用计算机仿真技术,采用自下而上的设计流程对中央冷却系统各个主要设备进行仿真建模,并进一步获取全系统的仿真模块,以实现对不同运行工况的动态模拟。再次,以某57000dwt散货船中央冷却系统为原型的科研样机作为研究对象,并通过实验数据与仿真结果的比较分析,验证仿真模型的准确性和合理性。根据系统的控制要求,制定变频控制方案,在此基础上对实船中央冷却系统进行仿真研究,获得船舶各类典型工况下的控制策略。通过对系统进行能耗分析,结果表明采用变频技术后,实现不同工况下冷却海水流量的连续变化,充分利用了海水的冷却能力,节能效果显著,有利于降低船舶的运营成本。最后,考虑到中央冷却控制系统的非线性、大延迟等特点,传统PID控制器在跟踪设定值以及抑制扰动方面存在一定的缺陷,在很多情况下达不到理想的控制效果,为了改善控制品质,本文采用神经网络对中央冷却系统进行智能控制,建立了神经网络控制器模型,并应用到系统的变工况动态研究中。研究结果表明,神经网络控制不仅实现了系统的变频控制目标,并且具有很强的自适应性和抗干扰性,可以改善系统的控制性能。
[Abstract]:The central cooling system is an important part of the marine power plant. Through the circulation of cooling water, the central cooling system can cool the heating parts and heat exchangers so as to reduce the heat load on them. In order to ensure the normal and reliable operation of the equipment, the performance of the cooling system directly affects the working performance of the power plant, thus affecting the reliability and economy of the ship. On the other hand, with the entry into force of the energy efficiency design standard, Therefore, the simulation research of ship central cooling system is carried out, and the frequency conversion control method is adopted to improve the working performance of the system and to realize the energy saving and emission reduction of the ship. This paper first introduces the common form and composition of ship's central cooling system. According to the difference of cooling medium, the system is divided into high temperature fresh water system, low temperature fresh water system and seawater system. According to the operation process of the central cooling system, the dynamic mathematical model of the system is established by using the relevant theories of heat transfer and fluid mechanics. Secondly, the dynamic mathematical model is taken as the theoretical basis. Using computer simulation technology, using bottom-up design flow to simulate the main equipment of the central cooling system, and further obtain the simulation module of the whole system to realize the dynamic simulation of different operating conditions. Taking the prototype of a 57000dwt bulk carrier's central cooling system as the research object, the accuracy and rationality of the simulation model are verified by comparing the experimental data with the simulation results, according to the control requirements of the system. On the basis of the design of frequency conversion control scheme, the simulation study of the ship's central cooling system is carried out, and the control strategies under various typical conditions are obtained. Through the analysis of the energy consumption of the system, the results show that the frequency conversion technology is adopted. The continuous variation of cooling seawater flow under different working conditions is realized, the cooling capacity of seawater is fully utilized, the energy saving effect is remarkable, and the operation cost of the ship is reduced. Finally, considering the nonlinearity of the central cooling control system, In order to improve the control quality, the traditional PID controller has some defects in tracking the set value and restraining the disturbance, and can not achieve the ideal control effect in many cases. In this paper, the neural network is used to control the central cooling system intelligently, and the neural network controller model is established, which is applied to the dynamic research of the system under different working conditions. The results show that, Neural network control not only realizes the frequency conversion control target of the system, but also has strong adaptability and anti-interference, which can improve the control performance of the system.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U664.1

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