Thermodynamic Mechanism and Data Hybrid Driven Model Based Marine Diesel Engine Turbocharger Anomaly Detection with Performance Analysis

For the marine low-speed diesel engine, the performance evaluation based turbocharger anomaly detection plays an important role in the condition monitoring process. A thermodynamic mechanism and data hybrid driven model is proposed for the turbocharger anomaly detection in this paper. The turbocharger efficiency, as the Key Performance Indicator (KPI), is modeled using the thermodynamic mechanism method. In the monitoring process, the turbocharger healthy baseline is established with the data-driven method, which divides the efficiency space into “Normal Area” and “Fault Area”. Results of the presented method are verified by the studies of the real low-speed diesel engine monitoring case on a large ocean-going bulk carrier.