Publications Repository - Gdańsk University of Technology

Fast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection of the fuel delivery system of a two-stroke marine engine. The selected diagnostic data is theexhaust gas composition, with four components considered: oxygen, carbon oxide, nitric oxide, and carbondioxide. With these diagnostics, the method distinguishes eight different engine faults from the efficient state.The manuscript presents in detail the methodology for applying the SVDD method in a marine engine. Themethod of obtaining diagnostic data and its scaling is described. The method of training and validating thealgorithm is also presented, along with ready-made algorithms for use. The 100% accuracy of the proposedfault detection method. Based on the obtained results, the proposed fault detection method is promising fora simple application. Moreover, generalised algorithms that may be adapted to different technical solutionsare also presented.

Authors

• dr inż. Klaudia Wrzask link open in new tab ,
• dr hab. inż. Jerzy Kowalski link open in new tab ,
• Van Vang Le,
• Dr Van Bac Nguyen,
• Dao Nam Cao