延迟焦化加热炉热效率的机理建模与实时估计应用

doi:10.11949/0438-1157.20191072

摘要/Abstract

摘要：

在延迟焦化装置中，焦化炉热效率是操作先进性关键评价指标，然而实际工业生产中难以在线测得加热炉热效率。本文基于机理建模，推导了管式加热炉状态空间预测模型。为降低干扰影响，提出了一种基于粒子滤波的联合估计方法来修正加热炉热效率模型预测，并分析了其收敛性。实际应用结果证实了所提方法的可行性和有效性，为实现延迟焦化装置先进控制奠定了基础。

关键词: 预测, 控制, 管式加热炉, 机理建模, 参数估计, 加热炉热效率, 粒子滤波, 联合估计

Abstract:

Coking heating furnace is the key plant in the delayed coking unit. Thermal efficiency is one of the most important key performance indications. In this work, the thermal efficiency dynamic model is established based on the first principles of heat transfer equations and heat balance conditions. A joint particle filtering method combined with Kalman filter and particle filter is proposed to correct the model prediction and the convergence of the proposed method has been analyzed. The application results confirmed the feasibility and effectiveness of the proposed method, and laid the foundation for the advanced control of the delayed coking unit.

Key words: prediction, control, tubular heating furnace, first principle modeling, parameter estimation, thermal efficiency, joint particle filtering, united estimation

中图分类号:

TP 273

黄健, 赵众. 延迟焦化加热炉热效率的机理建模与实时估计应用[J]. 化工学报, 2020, 71(7): 3140-3150.

Jian HUANG, Zhong ZHAO. Mechanism modeling and real-time estimation application of thermal efficiency for delayed coking furnace[J]. CIESC Journal, 2020, 71(7): 3140-3150.

图/表 10

参考文献 33

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化验分析数据	模型预测值	相对误差	误差百分比
94.1283	93.97047	0.157898	0.17
94.0898	93.96148	0.128333	0.14
94.0552	94.06848	-0.01326	0.02
94.0855	93.92905	0.156486	0.17
94.1410	93.89776	0.243265	0.26
94.1543	93.88981	0.264489	0.28
94.0818	93.92463	0.157184	0.17
94.0240	94.04803	-0.02398	0.03
93.9775	94.01946	-0.04191	0.05
94.1575	94.08129	0.076286	0.08
94.1625	94.08595	0.076617	0.08
94.1695	94.07200	0.097571	0.10
94.1224	94.03293	0.089539	0.10
94.1636	94.06520	0.098439	0.11
94.1688	94.05069	0.118199	0.13
94.0913	94.10989	-0.0185	0.02
93.9819	94.07428	-0.09235	0.10
93.9182	94.06282	-0.14457	0.15
93.9344	94.06899	-0.13455	0.14
94.1415	94.03183	0.109697	0.12

化验分析数据	模型预测值	相对误差	误差百分比
94.1283	93.97047	0.157898	0.17
94.0898	93.96148	0.128333	0.14
94.0552	94.06848	-0.01326	0.02
94.0855	93.92905	0.156486	0.17
94.1410	93.89776	0.243265	0.26
94.1543	93.88981	0.264489	0.28
94.0818	93.92463	0.157184	0.17
94.0240	94.04803	-0.02398	0.03
93.9775	94.01946	-0.04191	0.05
94.1575	94.08129	0.076286	0.08
94.1625	94.08595	0.076617	0.08
94.1695	94.07200	0.097571	0.10
94.1224	94.03293	0.089539	0.10
94.1636	94.06520	0.098439	0.11
94.1688	94.05069	0.118199	0.13
94.0913	94.10989	-0.0185	0.02
93.9819	94.07428	-0.09235	0.10
93.9182	94.06282	-0.14457	0.15
93.9344	94.06899	-0.13455	0.14
94.1415	94.03183	0.109697	0.12

滤波	热效率标准误差
KF	0.0603
PF	0.0778
JPF	0.0232

滤波	热效率标准误差
KF	0.0603
PF	0.0778
JPF	0.0232

粒子数	RMSE	运行时间
50	0.0786/0.0231	2.3650/2.5360
100	0.0256/0.0157	2.4410/2.8600
150	0.0227/0.0123	2.4830/3.0600
200	0.0184/0.0099	2.8520/3.1840
300	0.0112/0.0073	3.3480/3.5290
500	0.0096/0.0045	3.9350/4.0370