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生产效率优化是企业追求的目标,安全生产越来越得到重视,实际生产中需要优化和控制的操作参数较多,传统优化技术计算复杂,寻优过程缓慢,优化结果收敛效果不佳,并且难以兼顾多个优化指标。提出一种聚丙烯生产出料过程的控制方案的多目标智能优化设计方法,以提高经济效益即出料效率、增加生产安全性即降低出料过程的应力影响,以及保证生产稳定性即减少仪表风峰值用量为多个优化目标,在优化生产效率的同时兼顾安全因素。顺序控制中,操作参数多,时间等因素制约条件复杂。在设计的优化技术中,同时优化多个操作参数,同时考虑多个制约条件,即以顺序控制过程中的各出料线的启动时间差和各出料周期的定时器为操作参数,通过人工免疫优化算法,运用非劣分层思想和群智特性进行智能寻优,避免了传统优化计算的复杂程度,加快了优化过程的速度,为在线优化的应用提供了良好的条件。采用实际生产数据,通过仿真优化实验,获得了优异的聚丙烯生产出料过程的优化顺序控制方案。进一步采用周期性的在线优化结构,减少实际工况变化对优化的影响,完善了优化模型,较好的指导了实际的生产控制操作。
The optimization of production efficiency is the goal pursued by the enterprise. Safety production is paid more and more attention. More operational parameters need to be optimized and controlled in actual production. The traditional optimization techniques are complex in calculation, the optimization process is slow, the convergence of the optimization results is not good and difficult Take into account a number of optimization indicators. A multi-objective intelligent optimization design method for the control scheme of polypropylene production and discharging process was proposed to improve the economic efficiency of the discharge efficiency, increase the production safety that is to reduce the stress impact of the discharge process, and to ensure the production stability that is to reduce the instrument Wind peak usage for multiple optimization goals, optimizing production efficiency at the same time taking into account safety factors. Sequence control, the operating parameters and more time constraints and other factors complicated. In the design of optimization techniques, while optimizing a number of operating parameters, taking into account a number of constraints, that is, the sequence of control of the process of starting the discharge time difference and the discharge cycle of the timer as the operating parameters, by artificial immunity Optimization algorithms, using non-inferior layering and group intelligence to optimize the intelligence, avoiding the complexity of the traditional optimization calculation, speeding up the optimization process, and providing good conditions for the application of online optimization. Using the actual production data, the optimal sequence control scheme of the polypropylene production and discharge process was obtained through simulation and optimization experiments. Furthermore, the periodic online optimization structure is further adopted to reduce the impact of actual working condition changes on optimization and optimize the optimization model, which guides the actual production control operation better.