计算机与现代化 ›› 2022, Vol. 0 ›› Issue (02): 65-69.

• 人工智能 • 上一篇    下一篇

基于瞬时频率响应函数的间歇过程时段划分

  

  1. (北京化工大学信息科学与技术学院,北京100029)
  • 出版日期:2022-03-31 发布日期:2022-03-31
  • 作者简介:李宇斌(1996—),男,河北唐山人,硕士研究生,研究方向:复杂工业过程智能检测,E-mail: 2067248215@qq.com; 通信作者:于涛(1976—),男,甘肃平凉人,讲师,研究方向:复杂工业过程智能检测,视觉检测,E-mail: Yutao@mail.buct.edu.cn。
  • 基金资助:
    国家自然科学基金资助项目(61973025)

Phase Partition of Batch Process Based on Instantaneous Frequency Response Function

  1. (College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China)
  • Online:2022-03-31 Published:2022-03-31

摘要: 多时段特性是间歇过程的本质特性之一,对间歇过程实现有效的时段划分是故障监测的基础。传统的时段划分方法大多针对过程的输入输出数据,对输入输出数据突变较为敏感。本文提出一种基于瞬时频率响应函数的间歇过程时段划分方法,该方法基于系统的瞬时动态特性,用瞬时频率响应函数替代输入输出数据进行时段划分,利用小波变换估计系统的瞬时频率响应函数进行核主元分析降维,通过模糊C均值聚类对降维后频率响应函数进行聚类划分时段。实验结果表明,本文所提出的方法能够实现对间歇过程的时段划分,并具有较高的鲁棒性。


关键词: 间歇过程, 时段划分, 频率响应函数, 小波变换

Abstract: Multi-phases characteristic is one of the essential characteristics of batch process, and the effective phase partition of batch process is the basis of fault monitoring. Most of the traditional phase partition methods focus on the input and output data of the process, which is sensitive to the input and output data mutation. In this paper, a phase partition method of batch process based on instantaneous frequency response function is proposed. This method uses instantaneous frequency response function to replace the input and output data for phase partition based on the instantaneous dynamic characteristics of the system. Wavelet transform is used to estimate the instantaneous frequency response function of the system and the kernel principal component analysis is used to reduce the dimension. The frequency response function is clustered by fuzzy C-means clustering to partition the phase. Experimental results show that the proposed method can realize the phase partition of batch process and has high robustness.

Key words: batch process, phase partition, frequency response function, wavelet transform