大规模反渗透海水淡化故障诊断专家系统的研究

发布时间：2019-03-24 16:13

【摘要】：随着科技与社会的发展，水资源短缺成为全球瞩目的热点问题之一。反渗透方法因其设备投资省、能量消耗低、建造周期短等优点，正快速成为当今应用最广泛的海水淡化方法。反渗透系统的水质安全受到预处理和膜污染等多方面的影响，通过故障诊断能及时发现问题所在，对保证系统安全、高效的运行具有重要意义。目前全球各地纷纷建立了大规模甚至是超大规模的反渗透海水淡化工程，，研究工作的任务旨在面向超大规模反渗透海水淡化工程，研究故障诊断的方法，并在此基础上初步建立专家系统。研究工作内容如下： 1.通过阅读大量相关文献，分析了目前国内外反渗透海水淡化的发展趋势，在此基础上对故障诊断方法和专家系统技术进行了概述，并将反渗透工程与上述方法和技术结合的研究现状进行了分析，阐述了本研究工作的意义。 2.以舟山六横岛日产10万吨级海水淡化工程为对象，在了解系统工作原理、系统架构以及工艺流程的基础上，对反渗透系统膜组件典型故障进行了深入研究，为故障诊断提供了知识支撑。 3.采用故障树分析法，将最有研究价值的故障与其他故障间的逻辑联系以树状结构表示并对故障树进行定性分析，得到故障树的最小割集、最小径集并进行了结构重要度分析，分析结果对专家系统推理机的设计工作打下基础。 4.应用故障树的最小割集与产生式规则法，对专家系统的知识库进行设计。建立了故障事实表，最小割集事件表，故障规则表，故障条件表和故障维修表为主要内容的知识库；采用基于故障树知识的推理方式、正反混合的推理方向和深度限制优先的搜索策略，建立了推理机。基本完成了对专家系统的设计。 5.在以上研究工作的基础上，基于Visual Studio2008和SQL Server2005开发了反渗透海水淡化故障诊断专家系统软件。该软件能协同反渗透监测系统，实时判断反渗透工作中是否有故障发生，若有对故障进行自动诊断，并给出维修维护建议。不同操作工况下的模拟数据仿真测试和交互式测试分析表明本系统具有良好的故障诊断效果和应用价值。
[Abstract]:With the development of science and technology and society, the shortage of water resources has become one of the hot issues in the world. Reverse osmosis (RO) is rapidly becoming the most widely used seawater desalination method because of its advantages such as low equipment investment, low energy consumption and short construction period. The water quality safety of reverse osmosis system is affected by pretreatment and membrane fouling. The fault diagnosis can find the problem in time, which is of great significance to ensure the safety and efficient operation of the system. At present, various parts of the world have set up large-scale or even super-large-scale reverse osmosis desalination projects. The task of the research work is to study the methods of fault diagnosis for the super-large-scale reverse osmosis desalination projects. And on this basis, the preliminary establishment of expert system. The contents of the study are as follows: 1. The development trend of reverse osmosis seawater desalination at home and abroad is analyzed by reading a large number of relevant literatures. On this basis, the fault diagnosis methods and expert system technology are summarized. The research status of reverse osmosis engineering combined with the above methods and technologies is analyzed, and the significance of this research is expounded. 2. On the basis of understanding the working principle, system structure and technological process of the one hundred thousand ton daily seawater desalination project in Liuheng Island, Zhoushan, the typical faults of membrane module in reverse osmosis system are deeply studied. It provides knowledge support for fault diagnosis. 3. By using fault tree analysis, the logical relationship between the most valuable fault and other faults is expressed in a tree structure and qualitative analysis of the fault tree is carried out. The minimum cut set and the minimum diameter set of the fault tree are obtained, and the importance degree of the structure is analyzed. The analysis results lay the foundation for the design of expert system inference engine. 4. The knowledge base of expert system is designed by the method of minimum cut set and production rule of fault tree. The knowledge base of fault fact table, minimum cut set event table, fault rule table, fault condition table and maintenance table is established. The inference engine is established by using the reasoning method based on fault tree knowledge, the direction of reasoning and the search strategy of depth-limited priority. Basically completed the expert system design. 5. On the basis of the above research, the software of reverse osmosis desalination fault diagnosis expert system is developed based on Visual Studio2008 and SQL Server2005. The software can cooperate with the reverse osmosis monitoring system, judge whether there are faults in reverse osmosis work in real time, if any, diagnose the faults automatically, and give some suggestions for maintenance and maintenance. Simulation test and interactive test analysis of simulated data under different operating conditions show that the system has good fault diagnosis effect and application value.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：P747.5;TP277

【参考文献】