SELECTION OF INFORMATION FOR EXPERT SYSTEM OF THE ASSESSMENT OF TECHNICAL CONDITION OF THE SHIP INTERNAL COMBUSTION ENGINE IN USE
Abstract
An important aspect of the operation of complex technical facilities, which include marine engines, internal combustion, is information support management processes in order to select the most efficient mode, allowing to maintain reliability of the technical object within the deadlines while maintaining the technical and economic indicators. Achieving this is possible only provided that the decision support system is able to monitor not only the specified parameters, but also take into account the technical condition of the object at the current time. In the present study describes the criteria for selection of information for the assessment of marine internal combustion engine technical condition, which is necessary for the adoption of the expert system decision on the choice of operating conditions. The criteria used by the experts for the production of marine engines, internal combustion, as well as their operation experts for the parameters, which are the sources of information about the technical condition of the engine. These criteria are applied in the technical diagnosis and strictly defined for all technical systems. On an example fuel system of the internal combustion engine of the ship described procedure using multivariate correlation analysis to reduce the number of parameters characterizing the state of the system in real time that are necessary to create an expert system knowledge base. As a result of the calculations, it was found that the viscosity between the fuel and the fuel pressure before the high pressure fuel pump there is a direct correlation with regard to the fuel temperature high pressure fuel pump, this option can be considered less informative. These results were confirmed in the field of ship internal combustion engine experts. Using multivariate correlation analysis allow for a sample of the large number of parameters describing the technical condition of the ship’s engine and its systems, and thus to select the most informative, which will be used in future work to create a knowledge base of the expert system.
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