首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于PSO-SVM的工艺装置液位监测方法
引用本文:陈晓霞,韩雪峰,邓瑶,蒋军成,唐景华.基于PSO-SVM的工艺装置液位监测方法[J].安全与环境学报,2017,17(1):100-105.
作者姓名:陈晓霞  韩雪峰  邓瑶  蒋军成  唐景华
作者单位:南京工业大学城市建设与安全工程学院,南京210009;江苏省城市与工业安全重点实验室,南京210009;南京扬子石化金浦橡胶有限公司,南京,211500
基金项目:国家自然科学基金重点项目
摘    要:生产装置的"假液位"现象严重影响了工业生产过程的正常运行。为此,运用软测量思想建立数学模型,监测直接测量结果,防止假液位的发生,保障生产安全。通过比较机理建模法与基于数据驱动建模法的优劣,提出采用PSO-SVM法建立数学模型,并以SBR泄料槽液位的监测为例进行分析。以集管进料压力P_1、泄料槽入口温度T_A丁二烯分离系统压力p_O这3个量作为辅助变量来预测泄料槽液位L。结果表明,该模型预测值与实际值符合良好,具有较强的预测性能,能够较好地对SBR泄料槽液位进行监测,有效避免SBR泄料槽假液位的产生。

关 键 词:安全工程  假液位  数据驱动  PSO-SVM  SBR  泄料槽

Renovated method for liquid level monitoring of the processing instruments based on the PSO-SVM principle
CHEN Xiao-xia,HAN Xue-feng,DENG Yao,JIANG Jun-cheng,TANG Jing-hua.Renovated method for liquid level monitoring of the processing instruments based on the PSO-SVM principle[J].Journal of Safety and Environment,2017,17(1):100-105.
Authors:CHEN Xiao-xia  HAN Xue-feng  DENG Yao  JIANG Jun-cheng  TANG Jing-hua
Abstract:This paper is aimed at introducing a renovated method for liquid level monitoring of the processing instruments based on the PSO-SVM principle in order to solve the problem on how to apply the idea of soft measurement to the monitoring of the industrial production.The said renovated method is intended to be used directly for measuring the production process to ensure the production safety by avoiding the false level interference in it.However,there still exist some assumptions made by using the method,saying that it cannot fully reflect the reality of the actual industrial production system.Therefore,as a means of supplementation,we have proposed a so-called PSO-SVM method for the liquid level monitoring of the processing instruments based on the data-driven modeling under the support of the vector machine sparse for the small samples with the nonlinear high dimensional data.In so doing,it would be possible to overcome the known "dimension disaster" by avoiding being trapped into the local minimum dots.However,on the whole,the method we have developed proves to perform successfully in generalization ability and stand out in the data-driven modeling methods.In order to optimize the functions of the model,we have managed to use the particle-swarming optimal algorithm to optimize the parameters based on the SVM model.Last of all,we have also established a mathematical model based on the PSO-SVM for analyzing the liquid level monitoring of the SBR discharge chute by taking into account the three auxiliary variables,that is,the feed pressure of manifold PI,the inlet temperature of the discharge chute TA and the pressure of the butadiene separation system Po so as to get the level of the discharge chute L.The reliability and validity of the application results of the model show that the predicted values prove to be well in accord with the actual ones,wheres the model turns to be successful in operation as is predicted.Thus,the model we have established can be taken as a reference to the effective monitoring of the liquid level of SBR discharge chute due to its nice performance in the actual application so as to avoid "the false level" interference and ensure the production safety.
Keywords:safety engineering  false level  data-driven  PSO-SVM  SBR  discharge chute
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号