Monitoring of fuel oil process of marine diesel engine

Abstract

Hotelling’s T2 control chart is very efficient for detecting sudden changes in a process; however, it loses sensitivity to detect small and progressive changes and its performance decreases when the number of variables monitored at the same time is high. Because of this, conventional methods for variable reduction such as PCA were used, but they have difficulties in detecting the variability of the process when the correlation between variables is poor. We propose a Method for detection of Small and Sudden Deviations in the process (SSDM), applicable when the correlation between variables is low; which is typical in marine propulsion processes. First, fuel oil process variables of a marine diesel engine running, poorly correlated between them, were reduced through the analysis of correlations. Afterwards, the selected variables were monitored through Hotelling’s T2 control charts and sudden, out-of-range changes were detected. The variable that generated the deviation in the process was identified and the predictive variables were monitored through Cusum charts; the origin of small and progressive changes in the process below the alarm threshold set by the manufacturer was identified. The proposed method (SSDM), based on the combination of (Hotelling’s T2 + Cusum), can be implemented in any type of process in marine propulsion in a satisfactory and economical way, helping in the identification of the origin of any type of deviation (small and sudden) in the process early enough to implement the right predictive actions.