多模型PCA方法用于不稳定工业过程的监测

A Multi-Model PCA Method for Unstable Industrial Process Monitoring

工业过程的变化会带来过程数据的局部结构变化,因此对不稳定的工业过程进行监测和诊断是一个相当大的挑战。传统的过程监控方法将过程作为一个整体进行培训和建模,但忽略了局部特征。为了构造不稳定过程的结构,本文引入多模型框架,构造了一种新的不稳定工业过程多模型PCA监测方法。与传统方法相比,该方法具有更好的仿真性能。

It is quite a challenge to monitor and diagnose an unstable industrial process,because the changes of the industrial process.Traditional process monitoring methods shows the overall structure of the process data,but ignore the local characteristics.In order to construct the characteristics of the unstable process,this paper introduces a new Multi-Model PCA method for unstable industrial process monitoring.Compared with the traditional method,the proposed method performances better in simulation.