华南理工大学学报(自然科学版) ›› 2016, Vol. 44 ›› Issue (12): 36-43,52.doi: 10.3969/j.issn.1000-565X.2016.12.006

• 机械工程 • 上一篇    下一篇

高斯过程建模方法在工业过程中的应用

肖红军 刘乙奇 黄道平   

  1. 华南理工大学 自动化科学与工程学院,广东 广州 510640
  • 收稿日期:2016-04-18 修回日期:2016-06-21 出版日期:2016-12-25 发布日期:2016-11-01
  • 通信作者: 黄道平(1961-),男,教授,博士生导师,主要从事智能检测与智能控制研究. E-mail:audhuang@scut.edu.cn
  • 作者简介:肖红军(1979-),男,博士生,副教授,主要从事智能检测与智能控制研究. E-mail:jinsery@163. com
  • 基金资助:

    国家自然科学基金资助项目(61673181,61403142);广东省自然科学基金资助项目(2015A030313225);广东省科技计划项目(2016A020221007);佛山市科技创新专项资金项目(2014AG10018)

Application of Gaussian Process Modeling Method in Industrial Processes

XIAO Hong-jun LIU Yi-qi HUANG Dao-ping   

  1. School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2016-04-18 Revised:2016-06-21 Online:2016-12-25 Published:2016-11-01
  • Contact: 黄道平(1961-),男,教授,博士生导师,主要从事智能检测与智能控制研究. E-mail:audhuang@scut.edu.cn
  • About author:肖红军(1979-),男,博士生,副教授,主要从事智能检测与智能控制研究. E-mail:jinsery@163. com
  • Supported by:

    Supported by the National Natural Science Foundation of China(61673181,61403142),the Natural Science Foundation of Guangdong Province(2015A030313225) and the Science and Technology Planning Project of Guangdong Province (2016A020221007)

摘要: 面对日益复杂的工业过程,传统传感器无法得到有效应用,重要变量无法准确建 模,重要过程无法得到有效优化和诊断,高斯过程模型的提出和应用为工业过程建模、优 化和控制提供了一个广阔的思路,并可兼顾描述不确定信息. 文中针对工业过程的复杂特 性,不仅综述了高斯过程的基本方法以及存在的主要问题,而且归纳了其基本建模、优化、 控制及故障诊断的应用和研究成果. 最后,结合国际上发展及作者的实践经验总结并展望 了高斯过程模型在工业过程中的应用前景和发展趋势.

关键词: 高斯过程模型, 工业过程, 软测量, 故障诊断

Abstract:

As industrial processes have become more and more complex,the traditional sensors are unavailable,and it is difficult to properly model the critical variables and efficiently optimize or diagnose the important parts of a process.The Gaussian process model provides an alternative to the modeling,optimization and control of industrial processes under the constraints of uncertainties.In this paper,aiming at the complexity of industrial processes,the pros and cons of the Gaussian process model are investigated,and its application to the modeling,optimization,control and fault diagnosis of industrial processes as well as the corresponding research results is generalized.Final- ly,the application prospects and development orientations of the Gaussian process model in industrial processes are summarized and forecasted by combining the international research results with the authors' practical experience.

Key words: Gaussian process model, industrial process, soft sensor, fault diagnosis

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