Inference Engine Design Supervised Machine Learning Method On Electric Feeding System Of Liquid Propellant Rockets

Prawira Nusantara, Rudy Gultom, Achmad Farid

Abstract


For Indonesia, having greater deterrence from potential threats is the mandate of the Preamble of the 1945 Constitution in the fourth paragraph. Therefore, 7 priority programs (Combat Aircraft, Submarines, Medium Tanks, Rockets, Missiles, Radars, and Propellants) have been launched by the Government of Indonesia through the Ministry of Defense in the field of technology. To support the program, in this paper an inference engine is built by applying the supervised machine learning method on the WSN architecture which is embedded in a liquid propellant rocket electric feed system to obtain the desired rocket thrust. The data used in this research are pump motor speed, valve opening angle, propellant flow rate, propellant pressure, and propellant thrust. The results of this study obtained an inference engine that is able to provide a pressure prediction model with an accuracy value of "r2 = 0.962", a flow rate prediction model with an accuracy value of "r2 = 0.9835", and a thrust prediction model with an accuracy value of "r2 = 0.963

Keywords


Electric Feed System, WSN, Inference Engine, and Supervised Machine Learning

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DOI: http://dx.doi.org/10.52155/ijpsat.v30.2.4033

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