Fault diagnosis is a critical task in the daily operation of chemical processes. In this paper, a hybrid fault diagnosis method is proposed that combines a process-knowledge-based qualitative reasoning technique with fault detection based on a …
With the emergence of Industry 4.0 and Big Data initiatives, there is a renewed interest in leveraging the vast amounts of data collected in (bio)chemical processes to improve their operations. The objective of this article is to provide a …
With the emergence of Industry 4.0 and Big Data initiatives, there is a renewed interest in leveraging the vast amounts of data collected in (bio)chemical processes to improve their operations. The objective of this article is to provide a …
Process monitoring is of importance to maintain process safety, reliability, performance and cost efficiency. This work presents a hybrid fault detection approach that combines process knowledge such as first-principles and process causal relations …
Process monitoring is of importance to maintain process safety, reliability, performance and cost efficiency. This work presents a hybrid fault detection approach that combines process knowledge such as first-principles and process causal relations …
Simulated moving-bed chromatography (SMBC) separation of a solution containing three different saccharides was investigated by real-time, inline monitoring of the concentration of each saccharide with Fourier transform near-infrared spectroscopy …
Simulated moving-bed chromatography (SMBC) separation of a solution containing three different saccharides was investigated by real-time, inline monitoring of the concentration of each saccharide with Fourier transform near-infrared spectroscopy …
To implement on-line process monitoring techniques that utilize principal component analysis (PCA) or partial least squares (PLS) models, it is important to use reliable data that represents normal process operation when constructing the models. In …
To implement on-line process monitoring techniques that utilize principal component analysis (PCA) or partial least squares (PLS) models, it is important to use reliable data that represents normal process operation when constructing the models. In …