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| 根据工业装置现场操作变量分析以及丙烯精馏系统的工艺机理数学模型的模拟计算，利用本文改进的粒子群算法训练神经网络，建立塔釜丙烯浓度软测量模型，克服塔釜在线分析仪存在的滞后和跳动现象；根据对塔的流程模拟和特性分析，我们选择灵敏板温度、塔釜压力、塔釜温度、塔进料量、塔釜采出量等变量作为关键影响变量，预测塔釜丙烯浓度。 |
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瓶盖(金币+10,VIP+0): 10-9 15:46
zap65535(金币-10,VIP+0): “predict the concentration of propylene reactor tower” 不负责任 12-22 11:43
zap65535(金币-10,VIP+0): “predict the concentration of propylene reactor tower” 不负责任 12-22 11:43
| According to multivariate analysis of plant-site operations as well as the systematic process of propylene distillation mechanism of the mathematical model simulation, using this improved particle swarm algorithm trained neural networks, the establishment of the concentration of propylene tower reactor soft-sensor model, to overcome the tower kettle Analyzer lag exists and the jumping phenomenon; based on the tower process simulation and characteristic analysis, we chose to sensitive plate temperature, tower reactor pressure and temperature reactor tower, tower fluxes, tower reactor taken out of the amount of the impact of variables such as a key variable to predict the concentration of propylene reactor tower . |
3楼2009-10-07 08:25:25
2楼2009-10-06 16:27:09
