Багаторівнева обробка віброакустичних сигналів для вдосконалення діагностики газотурбінних двигунів

The object of this study is the process of monitoring the technical condition of an aircraft gas turbine engine (GTE). One of the most dangerous causes of accidents is damage caused by foreign objects, in particular small metal particles, hailstones, bolts, fuselage fragments, etc., entering the engine turbine during flight or during takeoff and landing. The task addressed was to improve the methods of gas turbine engine vibroacoustic diagnostics, which would increase its sensitivity to small changes in diagnostic signals caused by the ingress of small foreign objects into the engine turbine. To solve this problem, it has been proposed to use multi-level processing of vibration signals obtained as a result of physical modeling of the rotating system (RS) and simulation of the ingress of small foreign objects. Multi-level processing combines the use of time-frequency, bispectral, and fractal analysis methods to determine the quantitative integrated diagnostic indicator – Minkowski dimensionality. The following average values of Minkowski dimensionality were obtained for the estimates of the bispectral modulus: without external influence – 1.075; ingress of small foreign objects – 1.01; friction of the blades against a foreign object as a result of its ingress into the RS turbine – 1.21. It has been established that an increase in the Minkowski dimensionality indicates the development of an operational disturbance caused by the ingress of foreign objects, even very small ones. This paper reports experimental confirmation of the effectiveness of using multi-level processing of vibration signals for diagnosing operational disturbances due to the ingress of foreign objects into RS. It has been established that multi-level processing makes it possible to detect hidden trends in a noisy signal that are difficult to detect using conventional processing methods