Jialin Liu , Hao-Che Chien , David Shan-Hill Wong , Cheng-Ting Hsieh
{"title":"基于人工智能(AI)代理模型的硫磺回收装置高级过程控制","authors":"Jialin Liu , Hao-Che Chien , David Shan-Hill Wong , Cheng-Ting Hsieh","doi":"10.1016/j.jtice.2025.106119","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>The modified Claus process is a major technology used for the recovery of elemental sulfur from acid gases. The process consists of two steps. In the first step, a portion of H<sub>2</sub>S is oxidized to SO<sub>2</sub> in a reaction furnace; the second step comprises the reaction of the remaining H<sub>2</sub>S with SO<sub>2</sub> at lower temperatures over a catalyst. The major manipulated variables (MVs) to maximize the sulfur recovery efficiency (SRE) are the combustion air flow rate and inlet gas temperature for the converter. However, both MVs encounter a process gain reverse problem for the controlled variable (CV), which refers to the outlet total sulfur. In addition, process control is limited by the significant time delay between the air flow rate and tail gas analyzer.</div></div><div><h3>Methods</h3><div>In this study, an artificial intelligence (AI) surrogate model was built and the movement of the MVs was evaluated using to minimize the sum of the predicted total sulfur in the prediction horizon. The assumption of future disturbance data is not necessary for the proposed approach.</div></div><div><h3>Significant findings</h3><div>In field operations, a specific H<sub>2</sub>S/SO<sub>2</sub> in the tail gas is maintained by the combustion air that is inefficient to minimize total sulfur. The total sulfur content can be reduced by approximately 12 % from 1.6 %–1.4 % compared with that of field operations by the advanced process control.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"172 ","pages":"Article 106119"},"PeriodicalIF":5.5000,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advanced process control for sulfur recovery units by artificial intelligence (AI) surrogate model\",\"authors\":\"Jialin Liu , Hao-Che Chien , David Shan-Hill Wong , Cheng-Ting Hsieh\",\"doi\":\"10.1016/j.jtice.2025.106119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>The modified Claus process is a major technology used for the recovery of elemental sulfur from acid gases. The process consists of two steps. In the first step, a portion of H<sub>2</sub>S is oxidized to SO<sub>2</sub> in a reaction furnace; the second step comprises the reaction of the remaining H<sub>2</sub>S with SO<sub>2</sub> at lower temperatures over a catalyst. The major manipulated variables (MVs) to maximize the sulfur recovery efficiency (SRE) are the combustion air flow rate and inlet gas temperature for the converter. However, both MVs encounter a process gain reverse problem for the controlled variable (CV), which refers to the outlet total sulfur. In addition, process control is limited by the significant time delay between the air flow rate and tail gas analyzer.</div></div><div><h3>Methods</h3><div>In this study, an artificial intelligence (AI) surrogate model was built and the movement of the MVs was evaluated using to minimize the sum of the predicted total sulfur in the prediction horizon. The assumption of future disturbance data is not necessary for the proposed approach.</div></div><div><h3>Significant findings</h3><div>In field operations, a specific H<sub>2</sub>S/SO<sub>2</sub> in the tail gas is maintained by the combustion air that is inefficient to minimize total sulfur. The total sulfur content can be reduced by approximately 12 % from 1.6 %–1.4 % compared with that of field operations by the advanced process control.</div></div>\",\"PeriodicalId\":381,\"journal\":{\"name\":\"Journal of the Taiwan Institute of Chemical Engineers\",\"volume\":\"172 \",\"pages\":\"Article 106119\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2025-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Taiwan Institute of Chemical Engineers\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1876107025001725\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Taiwan Institute of Chemical Engineers","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1876107025001725","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Advanced process control for sulfur recovery units by artificial intelligence (AI) surrogate model
Background
The modified Claus process is a major technology used for the recovery of elemental sulfur from acid gases. The process consists of two steps. In the first step, a portion of H2S is oxidized to SO2 in a reaction furnace; the second step comprises the reaction of the remaining H2S with SO2 at lower temperatures over a catalyst. The major manipulated variables (MVs) to maximize the sulfur recovery efficiency (SRE) are the combustion air flow rate and inlet gas temperature for the converter. However, both MVs encounter a process gain reverse problem for the controlled variable (CV), which refers to the outlet total sulfur. In addition, process control is limited by the significant time delay between the air flow rate and tail gas analyzer.
Methods
In this study, an artificial intelligence (AI) surrogate model was built and the movement of the MVs was evaluated using to minimize the sum of the predicted total sulfur in the prediction horizon. The assumption of future disturbance data is not necessary for the proposed approach.
Significant findings
In field operations, a specific H2S/SO2 in the tail gas is maintained by the combustion air that is inefficient to minimize total sulfur. The total sulfur content can be reduced by approximately 12 % from 1.6 %–1.4 % compared with that of field operations by the advanced process control.
期刊介绍:
Journal of the Taiwan Institute of Chemical Engineers (formerly known as Journal of the Chinese Institute of Chemical Engineers) publishes original works, from fundamental principles to practical applications, in the broad field of chemical engineering with special focus on three aspects: Chemical and Biomolecular Science and Technology, Energy and Environmental Science and Technology, and Materials Science and Technology. Authors should choose for their manuscript an appropriate aspect section and a few related classifications when submitting to the journal online.