基于JIT-MOSVR的软测量方法及应用

doi:10.11949/j.issn.0438-1157.20161605

化工学报 ›› 2017, Vol. 68 ›› Issue (3): 947-955.DOI: 10.11949/j.issn.0438-1157.20161605

基于JIT-MOSVR的软测量方法及应用

汪世杰¹, 王振雷¹, 王昕²

1 华东理工大学化工过程先进控制和优化技术教育部重点实验室, 上海 200237;
2 上海交通大学电工与电子技术中心, 上海 200240

收稿日期:2016-11-14 修回日期:2016-11-24 出版日期:2017-03-05 发布日期:2017-03-05
通讯作者: 王振雷,wangzhen_l@ecust.edu.cn
基金资助:
国家科技支撑计划项目（2015BAF22B02）；国家自然科学基金面上项目（21276078）；上海市自然然科学基金项目（14ZR1421800）；流程工业综合自动化国家重点实验室开放课题基金项目（PAL-N201404）。

Soft-sensor method based on JIT-MOSVR and its application

WANG Shijie¹, WANG Zhenlei¹, WANG Xin²

1 Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;
2 Center of Electrical & Electronic Technology, Shanghai Jiao Tong University, Shanghai 200240, China

Received:2016-11-14 Revised:2016-11-24 Online:2017-03-05 Published:2017-03-05
Contact: 10.11949/j.issn.0438-1157.20161605
Supported by:
supported by the National Key Technology R&D Program (2015BAF22B02),the National Natural Science Foundation of China (2127 6078),the Natural Science Foundation of Shanghai (14ZR1421800) and the State Key Laboratory of Synthetical Automation for Process Industries (PAL-N201404).

摘要/Abstract

摘要：

针对传统多模型软测量方法在面对复杂、多变工况时缺少在线更新机制、更新时输出精度降低等问题，提出了一种基于即时学习算法（JIT）的多模型在线软测量方法（MOSVR）。离线阶段首先采用模糊C均值聚类（FCM）对训练数据进行聚类，接着采用SVR建立初始模型集。在线部分以多模型输出作为主要输出，当出现新工况时，通过在线模型更新策略（OSMU）将输出模式切换为JIT，同时多模型集进行在线更新。该方法不仅拥有多模型输出的快速性、精确性，而且在模型更新时通过JIT模式还能保证输出的连续性、稳定性、精确性。最后将该软测量方法进行了数值仿真并运用到乙烷浓度软测量中，验证了该方法的有效性。

关键词: 软测量, 动态建模, 过程系统, 模型, 即时学习

Abstract:

In case of complex and changeable working conditions, traditional multi-model soft-sensor techniques lacked an online update mechanism and decreased accuracy upon updating. A new soft-sensor method based on just-in-time algorithm (JIT) and multi-model online support regression (MOSVR) was proposed. In offline phase, fuzzy C-mean clustering (FCM) was employed to classify training data and SVR was used to build initial model set. In online phase, main output was multi-model SVR works, which would be switched to JIT model by online strategy of model updating (OSMU) and the current model set was updated online simultaneously when new working condition was encountered. The new method not only possessed rapidity and accuracy of multi-model outputs, but also guaranteed continuity, stability and accuracy of JIT outputs at model updating. Method effectiveness was demonstrated by numerical simulation and application in soft-sensor measurement of ethane concentration in ethylene production.

Key words: soft-sensor, dynamic modeling, process systems, model, just-in-time

中图分类号:

TP273

汪世杰, 王振雷, 王昕. 基于JIT-MOSVR的软测量方法及应用[J]. 化工学报, 2017, 68(3): 947-955.

WANG Shijie, WANG Zhenlei, WANG Xin. Soft-sensor method based on JIT-MOSVR and its application[J]. CIESC Journal, 2017, 68(3): 947-955.

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基于JIT-MOSVR的软测量方法及应用

Soft-sensor method based on JIT-MOSVR and its application

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