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Nonlinear multivariate filtering and bioprocess monitoring for supervising nonlinear biological processes

Paper ID Volume ID Publish Year Pages File Format Full-Text
36210 45124 2006 10 PDF Available
Title
Nonlinear multivariate filtering and bioprocess monitoring for supervising nonlinear biological processes
Abstract

On-line monitoring of bioprocesses is crucial to the safe production of high-quality products. However, biological processes tend to have nonlinear behavior patterns that depend on the influent loads, temperature, microorganism activity and so on. Moreover, since biosystems are generally operated under process control systems, data from biosystems tend to be characterized by autocorrelation and dynamic patterns. Although several nonlinear principal component analysis techniques have been recently developed for bioprocess monitoring, no nonlinear monitoring research that considers the bioprocess dynamics has been developed. In order to better monitor bioprocesses, a new dynamic nonlinear monitoring method that combines a kernel principal component analysis (KPCA) and an exponentially weighted moving average (EWMA) is proposed in this research. The kernel functions of KPCA can capture the nonlinearity of bioprocesses and the filtering of EWMA can catch the dynamics of bioprocesses. The proposed method is applied to two case studies: a simple dynamic nonlinear process and a simulation benchmark of a biological treatment process. The simulation results clearly show that the proposed method outperforms other static and linear methods, especially for detecting small shifts in processes.

Keywords
Bioprocess monitoring; Fault diagnosis; Multivariate filtering; Process monitoring; Nonlinear dynamics; Systems engineering; WWTP
First Page Preview
Nonlinear multivariate filtering and bioprocess monitoring for supervising nonlinear biological processes
Publisher
Database: Elsevier - ScienceDirect
Journal: Process Biochemistry - Volume 41, Issue 8, August 2006, Pages 1854–1863
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering