An artifical neural network usage in measurement of exhaust gas emission from marine engines: case study

The paper presents the case study of use the artificial neural network to predict the main propulsion marine engine load. Mentioned load of the engine is important parameter to assess the emission level of toxic compounds into the atmosphere according to ISO standard and MARPOL convention. The engine load depends on the ship speed, rotational speed of the engine, propeller blades settings, the direction and the speed of wind, the condition of sea and the direction and the speed of sea currents and construction parameters of the ship. The realization of the aim of the work requires the direct measurement of presented parameters and measurement of exhaust gas composition. The experiment was carried out onboard STS “Pogoria”. Obtained results are enough to use the ANN to predict engine load to measure the emission level of toxic compounds.