Journal of Chemical Engineering & Process Technology
Open Access
ISSN: 2157-7048
+44-20-4587-4809
ISSN: 2157-7048
+44-20-4587-4809
Nazmul Karim
Tanzania
Research Article
Statistical Fault Detection of Chemical Process - Comparative Studies
Author(s): Majdi Mansouri, Mohammed ZS, Raoudha Baklouti, Mohamed Nounou, Hazem Nounou, Ahmed Ben Hamida and Nazmul KarimMajdi Mansouri, Mohammed ZS, Raoudha Baklouti, Mohamed Nounou, Hazem Nounou, Ahmed Ben Hamida and Nazmul Karim
This paper addresses the statistical chemical process monitoring using improved principal component analysis (PCA). PCA-based fault-detection technique has been used successfully for monitoring systems with highly correlated variables. However, standard PCA-based detection charts, such as the Hotelling statistic, T2 and the sum of squared residuals, SPE, or Q statistic, are not able to detect small or moderate events since they use only data from the most recent measurements. Different fault detection (FD) charts, namely generalized likelihood ratio test (GLRT), shewhart control chart and exponentially weighted moving average chart (EWMA) control chart have been shown to be among the most effective univariate fault detection methods and more suitable for detection small faults. The objective of this work is to improve the PCA-based fault detection by using more sophisticate.. View More»
DOI:
10.4172/2157-7048.1000282