Process Monitoring Approach Based on Lifting Wavelet and Multi-way Principal Component Analysis

Qing Yang, Xu Zhang, Feng Tian
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Abstract

A novel technique of batch process monitoring based on lifting wavelet and multi-way principal component analysis (LWMPCA) is developed in this paper. The proposed technique consists of a preprocessing unit based on lifting wavelets transform in combination with MPCA. The superiority of the proposed method is illustrated by applying it to the simulation benchmark of fed-batch penicillin fermentation process with more reliable monitoring charts. The results of simulation clearly demonstrate the effectiveness and feasibility of the proposed method, which detects various faults more promptly with desirable reliability.
基于提升小波和多向主成分分析的过程监控方法
提出了一种基于提升小波和多向主成分分析(LWMPCA)的间歇过程监测方法。该技术由基于提升小波变换的预处理单元与MPCA相结合组成。将该方法应用于青霉素分批补料发酵过程的仿真基准,得到了更可靠的监测图,说明了该方法的优越性。仿真结果清楚地证明了该方法的有效性和可行性,能够更快速地检测出各种故障,并具有良好的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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