Cluster Based Anomaly Detection with Applications in the Maritime Industry

Abstract

In this paper we propose a cluster based version of the anomaly detection methodology based on signal reconstruction, using Auto Associative Kernel Regression (AAKR), combined with residuals analysis, using Sequential Probability Ratio Test (SPRT). We demonstrate how the proposed cluster based methodology can be successfully applied for anomaly detection on a marine diesel engine in operation. Furthermore, we demonstrate the vast reduction in computation time compared to the original framework, and discuss other possible advantages and disadvantages of the proposed methodology.