Hotelling T2 Index Based PCA Method for Fault Detection in Transient State Processes

Title & Authors
Hotelling T2 Index Based PCA Method for Fault Detection in Transient State Processes
Asghar, Furqan; Talha, Muhammad; Kim, Se-Yoon; Kim, SungHo;

Abstract
Due to the increasing interest in safety and consistent product quality over a past few decades, demand for effective quality monitoring and safe operation in the modern industry has propelled research into statistical based fault detection and diagnosis methods. This paper describes the application of Hotelling $\small{T^2}$ index based Principal Component Analysis (PCA) method for fault detection and diagnosis in industrial processes. Multivariate statistical process control techniques are now widely used for performance monitoring and fault detection. Conventional methods such as PCA are suitable only for steady state processes. These conventional projection methods causes false alarms or missing data for the systems with transient values of processes. These issues significantly compromise the reliability of the monitoring systems. In this paper, a reliable method is used to overcome false alarms occur due to varying process conditions and missing data problems in transient states. This monitoring method is implemented and validated experimentally along with matlab. Experimental results proved the credibility of this fault detection method for both the steady state and transient operations.
Keywords
Principal Component Analysis (PCA);hotelling $\small{T^2}$ index method;fault detection and diagnosis;steady state and transient operations;false alarms;
Language
English
Cited by
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