MATHEMATICAL MODEL OF AUTOMATION OF THE DIAGNOSIS OF INTERNAL COMBUSTION ENGINES OF THE YAMZ-238 FAMILY

Constructive improvement of mobile energy means, in particular their main unit - the internal combustion engine, is directed on: maintenance of differentiation of size of parameters of functioning of mechanisms of systems depending on variability of conditions and modes of operation of cars; increase of technical resource at use of cars on purpose in the set operating conditions. The existing methods and tools for diagnosing vehicle engines do not fully determine their current technical condition, which requires the development of mathematical models to automate the process of diagnosing their components and parts was found іn the analysis of literature sources. The object of diagnosis is a diesel internal combustion engine of the YaMZ-238 family, which is part of the power unit of most vehicles. Mathematical model of automation of the process of diagnosing internal combustion engines of the YaMZ-238 family is presents in the article. Replacing real technical devices with their idealized models allows the widespread use of various mathematical methods. In this case, the internal combustion engine of the YaMZ-238 family, as the object of diagnosis, is presented in the form of a «black box», the input and output parameters of which have a finite set of values. In general, the mathematical model is a system of functional relationships between each diagnostic signal and structural parameters. For internal combustion engines of the YaMZ-238 family, a diagnostic matrix has been compiled, which includes a list of faults and signs of faults. It is determined that the process of diagnosis based on the model of the diagnostic object is possible if the inverse transformation of the number of signs of malfunctions into the number of structural parameters (malfunctions) of the object was unambiguous. The proposed mathematical model of automation of the process of diagnosing internal combustion engines of the family YaMZ-238 will detect faults of components and parts depending on their characteristics.