基于小波包趋势提取的化工过程稳态检验  

Steady-state detection of chemical processes based on trend extraction with wavelet packet

作　　者：姚书会 楚纪正[1] 

机构地区：[1]北京化工大学信息科学与技术学院,北京100029

出　　处：《化工学报》2013年第12期4416-4421,共6页CIESC Journal

基　　金：国家高技术研究发展计划项目(2007AA04Z191)~~

摘　　要：构建了一种基于小波包阈值降噪的化工过程稳态检验方法。方法包括3个步骤:粗差剔除,小波包变换降噪和稳态辨识,具有简单易行且精度良好的特点。在小波包降噪中,通过引入阈值补偿因子,使得降噪过程更加灵活,以便在去除随机噪声和信号真值保留之间取得均衡效果。两个仿真示例展示了本文方法在单变量和多变量系统稳态检验上的有效性。Steady-state detection is to determine whether the chemical process is operating in a state of steadiness or not. It is an essential step in the field of process optimization and so on. Based on wavelet packet analysis for denoising, a steady state detection scheme is constructed in this study. The scheme includes three steps, removing coarse error, denoising and identifying steady state periods, and is featured with simple implementation and good accuracy. In the denoising step with wavelet packet transform, a compensating factor is introduced for the threshold, making it flexible and easy to achieve the right balance between removal of the noise and preservation of the true value of a signal. Two simulation tests are presented to demonstrate the effectiveness of the scheme of this study.

关 键 词：稳态检验 小波包 降噪 阈值 趋势提取 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置] TQ015.9[自动化与计算机技术—控制科学与工程]