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Effect of Cracking Furnace Parameters through Transfer Line Exchanger Outlet Temperature

机译:传输线交换器出口温度对裂解炉参数的影响

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In the cracking furnace operation, many process variables involve in the unit, each of which has a particular characteristic and impact to the process. These variables are usually set based on past experience, which lead to inefficient operations such as having a short operating cycle and increasing the probability of severity in the process. Furthermore, frequent process shutdown for decoking furnace with short cycle lengths leads to high operating cost and coil deterioration. In this study, stepwise regression models are developed to determine the relationship between ten input process variables of the cracking furnace and the transfer line exchanger outlet temperature as the output so that key process parameters could be controlled to maintain the desired operating conditions and to predict the outlet temperature three and seven days in advance so that the maintenance schedule for decoking could be planned. By using stepwise regression, the model of process relationship reveals that only eight from ten process variables and their 2nd order interactions best explains the output variable, with the R-squared adjusted of 93.63%. For the 3-day and 7-day ahead prediction models, fewer process variables and their interactions are used to explain the output variable, with MAPE of 4.65% and 1.83% respectively.
机译:在裂化炉操作中,单元中涉及许多过程变量,每个变量具有特定的特性并影响过程。通常根据过去的经验来设置这些变量,这会导致操作效率低下,例如操作周期短并增加了过程严重性的可能性。此外,对于短循环周期的炼焦炉,频繁的过程关闭导致高运行成本和卷材劣化。在这项研究中,开发了逐步回归模型来确定裂化炉的十个输入过程变量与传输线交换器出口温度作为输出之间的关系,以便可以控制关​​键过程参数以维持所需的工作条件并预测出口温度要提前三到七天,以便可以计划除焦的维护时间表。通过逐步回归,过程关系模型显示出十个过程变量中只有八个及其两个 nd 订单交互可以最好地解释输出变量,R平方调整为93.63%。对于提前3天和7天的预测模型,使用较少的过程变量及其相互作用来解释输出变量,MAPE分别为4.65%和1.83%。

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