Ammonia converter production optimization method based on data excavation technology

A technology of data mining and optimization methods, applied in instrumentation, adaptive control, control/regulation systems, etc.

Inactive Publication Date: 2008-05-28
宁波思华数据技术有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There is still a certain gap from the actual production application
In the actual production process, the production conditions of the ammonia synthesis unit are affected by various factors such as temperature, pressure, flow rate, and gas composition. The current production process parameters are basically determined based on experience, and there is great potential for optimization.

Method used

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  • Ammonia converter production optimization method based on data excavation technology
  • Ammonia converter production optimization method based on data excavation technology
  • Ammonia converter production optimization method based on data excavation technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] Example 1: Production Optimization Model of No. 1 Synthesis Plant

[0034] 1. Optimizing the target variable and optimizing the independent variable: the fresh gas entering the tower (FI0811a, Nm 3 / h) is the target variable, relevant process parameters such as fresh gas hydrogen content (AI0811c, %), cold shock three flow (FI0805a, Nm 3 / h), the inlet temperature of the first section of the synthesis tower (TI0801_2a, ℃), the outlet temperature of the second section of the synthesis tower (TI0801_5a, ℃), the temperature of the third section of the synthesis tower (TIC08004a_PV, ℃), the temperature of the third section of the synthesis tower (TI0801_12a, ℃), synthesis 42 process parameters such as the temperature of the fourth section of the tower (TI0801_16a, ℃), the inlet gas temperature of the waste boiler (TI0803a) and the outlet temperature of the water cooler (TI0807a, ℃) were analyzed as independent variables. Fresh gas volume greater than 26500Nm 3 The sample ...

Embodiment 2

[0043] Example 2: Production Optimization Model of No. 2 Ammonia Synthesis Unit

[0044] 1. Optimizing the target variable and optimizing the independent variable: the fresh gas entering the tower (FI0811b, Nm 3 / h) is to optimize the target variable, relevant process parameters such as fresh gas hydrogen content (AI0811c, %), the first stage inlet temperature of the synthetic tower (TI0801_7b, ℃), the first stage outlet temperature of the synthetic tower (TIC0801_2b_PV, ℃), the second stage temperature of the synthetic tower (TI0801_3b, ℃), the temperature of the second stage of the synthetic tower (TI0801_10b, ℃), the temperature of the third stage of the synthetic tower (TIC0801_12b_PV, ℃), the temperature of the third stage of the synthetic tower (TI0801_6b, ℃), the temperature of the waste boiler inlet gas (TI0804b) and the water cooler A total of 42 process parameters such as outlet temperature (TI0807b, °C) were analyzed as independent variables. Fresh gas volume great...

Embodiment 3

[0053] Example 3: Production Optimization Model of No. 3 Ammonia Synthesis Unit

[0054] 1. Optimizing the target variable and optimizing the independent variable: take the fresh gas entering the tower (FI0811c, Nm 3 / h) is to optimize the target variable, relevant process parameters such as fresh gas hydrogen content (AI0811c, %), cycle gas hydrogen content (AI0802c, %), synthesis tower one section inlet temperature (TI0801_2c, ℃), synthesis tower one section outlet temperature ( TIC0801_4c_PV, ℃), the temperature of the second stage of the synthesis tower (TIC0801_6c_PV, ℃), the temperature of the third stage of the synthesis tower (TIC0801_9c_PV, ℃), the temperature of the third stage of the synthesis tower (TI0801_12c, ℃), the secondary outlet temperature (TI0816c) and the outlet temperature of the water cooler (TI0820c, ℃), etc. 52 process parameters are analyzed as independent variables. Fresh gas volume greater than 27500Nm 3 The sample of / h is an excellent class sam...

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Abstract

A production method optimization method of an ammonia synthesizer which is based on the data mining technology belongs to a research frontier of the cross discipline field of chemical engineering, system engineering, and data mining and the like. The invention combines production characteristics of ammonia synthesizers, in accordance to parameter data and analytical measurement data of history production technology of the ammonia synthesizers which are gathered by the distributed control system, namely DCS, production and optimization target of the ammonia synthesizers and mathematical models between the relative technological parameters are established by utilizing the data mining technology. And real time data which are produced by the ammonia synthesizers are input in the mathematical models which are established, and production status of the ammonia synthesizers are assured by the models, and models establishing and maintenance, working order diagnosing, target predicting, and optimum operation guide of ammonia synthesizers are achieved. And the ammonia synthesizers are operated under optimum state, and production capability and control level of the device are improved. The method has the advantages of safety and reliability, small risk, low cost, and easy pauperization.

Description

technical field [0001] The invention relates to a production optimization method for ammonia synthesis equipment based on data mining technology, which belongs to the research frontier of interdisciplinary fields such as chemical engineering, system engineering, and data mining, and covers production process optimization models and model maintenance, real-time monitoring of production status, and production engineering. Real-time diagnosis of conditions and optimization of production process parameters. technical background [0002] Petroleum and chemical enterprises are the basic pillar industries of our country and occupy a pivotal position in our national economy. However, compared with the production level of the world's petrochemical industry, my country's petroleum and chemical industry still has a big gap. For example, the cash operating expenses required for processing one ton of products reflect the production cost level of enterprises. In 2003, the world’s average...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/02
Inventor 陆治荣陆文聪刘纯权杨善升刘亮刘太昂顾天鸿刘欣宋向礼杨明杨跃伏跃
Owner 宁波思华数据技术有限公司
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