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针对热工过程机理建模存在的局限性,以及常规含氧量设定准则确定中存在的问题,利用锅炉燃烧子系统在长期运行过程中积累的大量历史数据,采用NNARMAX(NN-based AutoRegressive,Moving Average,eXternal input)辨识结合网络结构优化方法对运行数据进行辨识,得到能够描述含氧量以及其他锅炉运行参数同主蒸汽流量之间复杂的动态耦合关系的模型。利用该模型实现最佳含氧量给定自主寻优,并且用于某厂75t/h锅炉燃烧优化调节系统中,取得了良好的工程应用效果。
In view of the limitations of the modeling of thermomechanical process and the problems in the determination of the conventional oxygen content setting criteria, a large amount of historical data accumulated during the long-term operation of the boiler combustion subsystem was used. NNARMAX (NN-based AutoRegressive, Moving Average and eXternal input are used to identify the operation data based on the optimization method of network structure and to obtain a model that can describe the complex dynamic coupling between oxygen content and other boiler operating parameters and main steam flow. This model is used to optimize the oxygen content given optimally, and it is used in a 75 t / h boiler combustion optimization and adjustment system of a certain plant, and has achieved good engineering application results.