The article presents a diagnosis of turbochargers in the supercharging systems of marine
engines in terms of maintenance decisions. The efficiency of turbocharger rotating machines
was defined. The operating parameters of turbocharging systems used to monitor the correct
operation and diagnose turbochargers were identified. A parametric diagnostic test was performed. Relationships between parameters for use in machine learning were selected. Their
credibility was confirmed by the results of the parametric test of the turbocharger system and
the main engine, verified by the coefficient of determination. A particularly good fit of the
describing functions was confirmed. As determinants of the technical condition of a turbocharger, the relationship between the rotational speed of the engine shaft, the turbocharger
rotor assembly and the charging air pressure was assumed. In the process of machine learning, relationships were created between the rotational speed of the engine shaft and the boost
pressure, and the indicator of the need for maintenance. The accuracy of the maintenance
decisions was confirmed by trends in changes in the efficiency of compressors
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Application of Machine Learning to Classify the Technical Condition of Marine Engine Injectors Based on Experimental Vibration Displacement Parameters Jan Monieta, Lech Kasyk Energies
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Fault Diagnosis Based On Improved Information Entropy And 1dcnn For Marine Turbocharger Rotor With Variable Speed Lei Hu, Haoran Hu, Nao Hu, Luyuan Liu, Fei Dong, Jianguo Yang, Jiahong Zhong Polish Maritime Research
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