@article{Myrhorod_Hvozdeva_Budashko_2022, author = {Myrhorod, Volodymyr and Hvozdeva, Iryna and Budashko, Vitalii}, title = {Multiparameter Approximation Model of Temperature Conditions of Marine Diesel Generator Sets, Based on Markov Chain Monte Carlo}, journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation}, volume = {16}, number = {4}, pages = {779-784}, year = {2022}, url = {./Article_Multiparameter_Approximation_Model_Myrhorod,64,1270.html}, abstract = {In the article we propose a multi-parameter approximation model, based on Markov chain Monte Carlo, which describes the relationship between the temperature regime, operating conditions and electromechanical parameters of marine diesel generator sets. The approximation model is constructed on the basis of the analysis of experimental data of the exhaust gases temperature of marine diesel generator sets in their long-term operation. As a statistical model of random processes of temperature deviations from the approximation model, a Markov process model is proposed that takes into account the possible correlation of the initial data. Since the measuring channels of modern diagnostic systems are digital, due to discretization in time and level, the studied processes form a Markov chain, which makes it possible to establish the important features of such processes. The use of approximation models ensures the stationarity conditions and the correctness of the proposed Markov model in the conditions of multi-mode operation of marine diesel generator sets. The proposed multi-parameter approximation model, based on Markov chain Monte Carlo, allows you to take into account random perturbations that lead to a random change in the output coordinates of the diagnostic object. The proposed improvement of the model makes it possible to ensure its adequacy to real processes of changing the parameters of the temperature regimes of marine diesel generator sets. The proposed multi-parameter approximation model, based on Markov chain Monte Carlo, can be used in the systems of technical diagnostics of marine diesel generator sets in order to increase the reliability of diagnostic conclusions.}, doi = {10.12716/1001.16.04.20}, issn = {2083-6473}, publisher = {Gdynia Maritime University, Faculty of Navigation}, keywords = {Markov Model, Marine Diesel Engine, Markov Chain Monte Carlo (MCMC), Diagnostics, Temperature Condition, Multi-Parameter Approximation Model, Marine Diesel Generator, Technical Diagnostics} }