【作者】 王金林；

【导师】 邵之江； 钱积新；

【作者基本信息】 浙江大学 ， 系统工程， 2004， 硕士

【摘要】 乙醛是一种重要的中间体，然而由于目前国内乙醛总产量不高，造成其售价偏高。利用先进的信息技术和自动化技术，优化现有乙醛装置的生产操作和管理，是提高国内乙醛装置生产能力的有效手段。本文对乙醛生产过程的实时在线操作优化进行了深入研究，解决了其中涉及的几个关键技术问题，包括稳态检测、数据调和、软测量建模等，并在工业现场实施投运了实时优化系统，取得了很好的经济效益。 本文的创新点和主要工作在于： 1．针对乙醛生产过程数据采集时间的多样性，提出了数据融合和稳态判断的联合算法；使用该算法对乙醛生产过程的数据进行融合、稳态检测，形成样本集合。 2．针对包含化学反应过程的生产流程，提出了基于原子衡算的数据调和算法，并将之应用于乙醛生产过程的数据调和。调和计算中考虑了粗乙醛流量和小放空气体流量的密度补偿。通过数据调和，分析并定位了流量测量中存在的大幅度零点误差，提高了测量系统的精度。 3．针对乙醛生产过程中的粗乙醛浓度，分别使用线性回归、非线性回归和主元分析方法建立软测量模型，开发了软测量系统。通过八个月的现场运行，不断地进行在线校正，软测量模型有效地测量出粗乙醛浓度值。提出了样本选取率、回归模型的一致性系数等概念。 4．根据上述软测量模型建立了乙醛收率模型，并开发了实时优化系统。实时优化操作系统使生产在保持平稳的前提下逐步调优，不断改进操作条件。通过四个月的实时优化实施，有效地提高了乙醛收率，促进了操作经验和优化理论的结合。并提出了基于经济目标的操作优化命题，建立了经济优化模型，讨论了该模型与其关键优化参数之间的关系。更多还原

【Abstract】 Invention of the Wacker process, which is an industrial process for the commercially manufacture of acetaldehyde by directly oxidizing ethene, is a milestone to petrochemical industry. It provides the basis for industrial-scale production of acetic acid, acetone, ethyl acetate, ketene, acetic anhydride, butyraldehyde and vinyl acetate. Optimizing the process operation and management by means of advanced information technology and automation technology is an efficient approach to increase acetaldehyde’s production capability. The real-time optimization(RTO) scheme was studied in this thesis, with focus on the crucial problems of steady state detection, data reconciliation, soft modeling and optimization implementation. A practical operation optimization system was developed and applied to the real plant.The main contributions of the work can be summarized in the following:1. It is pointed out that data preprocessing is of great importance to modeling and optimization. A unified algorithm for data merge and steady state detection was presented.2. For reaction process, a data reconciliation arithmetic based on atoms was developed. To get mass flow rate of vent gas and coarse aeetaldehyde from their volume flow rate data, density compensations are performed with regressed relationship between density and (temperature, pressure and concentration). Gross error exiting in flow rate was identified during the calculation. Quality of measurements was improved and balanced data were provided as an important basis for modeling and optimization.3. The soft-sensing model of the concentration of coarse aeetaldehyde was established. Two important concepts of model verification were proposed, ratio of selection for modeling and coefficient of coincidence. The model is updated on hourly basis to compensate the mismatch continually. The whole system was implemented and was kept running for eight months. The average deviation between the predicted values and the off-line laboratory analysis results is about 1.36 percent. The model is effective and practical, and is ready for optimization use.4. Formulation and implementation of yield optimization were intensively studied. The effect of proposed RTO scheme was validated in an overburdened real chemical plant, which implies the effectiveness and practicability of the technique. RTO would make profit for aeetaldehyde production process 6,862,000 yuan RMB per year. Furthermore, the optimization problem was re-formulated with economics introduced. Some key parameters of the model and their impact on overall economics were discussed.更多还原