Методи аналізу післяпольотних даних газотурбінного двигуна ТВ3-117В

The methods of analyzing post-flight data of gas turbine engines are considered, in particular, a typical method of diagnosing parameters reduced to standard atmospheric conditions, the use of a diagnostic regression model, the methods of factor analysis, the method of principal components, and trend analysis according to the r-criterion and S-criterion. The main attention is paid to the methods of factor analysis and trend analysis, which significantly increase the accuracy and reliability of diagnostics of the technical condition of engines. The use of factor analysis methods in combination with trend analysis provides a more accurate identification of long-term trends and relationships between various parameters of engine operation, which contributes to improving the diagnostic and forecasting processes. The advantages of the complex use of factor analysis and trend analysis methods for monitoring and diagnosing the technical condition of TV3-117V gas turbine engines, which increase the reliability, safety, and economic efficiency of their operation, are considered. The main parameters of the TV3-117V engine, which should be selected for trend control, were determined. Neural network technologies and fuzzy logic may be overkill for the analysis of the operational data of gas turbine engines because of the high demands on computing resources. The software developed by JSC "Element" is considered, and it is intended for the evaluation and analysis of post-flight data of aircraft engines and bench test data. It was found that software for the analysis of the operational data of engines needs improvement to reduce the influence of human factors and increase the automation of diagnostic processes. The automation of data analysis and integration of complex diagnostic models can significantly increase the accuracy and reliability of database interpretation. The expediency of using diagnostic models of engines, built either according to the statistical processing data of databases or based on simulation models, is described. It was found that a comparison of the simulation simulation data with engine bench test databases showed a high degree of correspondence between the diagnostic model and the real behavior of the engine. Recommendations for the optimal application of operational data analysis methods to increase the reliability, safety, and economic efficiency of TV3-117V aircraft engines are given.