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The evaluation of the crack-like damage parameter of blades at the vibroacoustical diagnosis of the gas-turbine engines

Bouraou N., Ignatovich S.

Vibrations in Physical Systems

2012

Vol. 25

83--88

This work is devoted to vibroacoustical condition monitoring of the gas-turbine engines (GTE) blades and diagnosis of the crack-like damages at the steady-state and non-steady-state modes of GTE. For detection of the mentioned damages we proposed the application and further development of the low-frequency vibroacoustical diagnostic methods which use vibrating and acoustical noise as diagnostic information. The following amplitude dimensionless characteristics are used as fault features: probability factor, peak factor and factor of background. The evaluation of the crack-like damage of the blades is carried out at the steady-state and nonsteady-state modes by using the generalized likelihood method. The statistical quality of the received estimations is investigated.

Vibroacoustical diagnosis of the crack-like damages of aircraft engine blades at the steady-state and non-steady-state modes

Bouraou N., Sopilka I.

Vibrations in Physical Systems

2010

Vol. 24

69--74

The work is devoted to condition monitoring and vibroacoustical diagnosis of the crack-like damages of the gas-turbine engines (GTE) blades at the steady-state and non-steady-state modes of GTE. The developed diagnostic model of GTE is presented and the influence of damage on the measured vibro- and acoustical signals at the steady-state and non-steady-state modes of GTE is determined. The application of the following signal processing methods: Polyspectral (Higher-Order Spectral) analysis, Wavelet-transformation and dimensionless characteristics of the vibroacoustical signals is proved. The efficiency of signal processing methods is demonstrated by the results of numerical simulations of the turbine stage at the steady-state and non-steady-state modes of vibration excitation. The fault features are detected and investigated.

Decision making about aircraft engine blades condition by using neural network at the steady-state and non-steady-state modes

Bouraou N., Zazhitskiy O.

Diagnostyka

2008

nr 3(47)

71-74

The work is devoted to problem solution of the gas-turbine engines (GTE) blades condition monitoring and diagnosis of the crack-like damages at the steady-state and non-steady-state modes of GTE. It is based on the development of theoretical basis of the vibroacoustical diagnosis methods, the application of the modern signal processing methods and new information technique for decision making. The application of the following signal processing methods: Wavelet-transformation and dimensionless characteristics of the vibroacoustical signals is proved. Neural networks are used for decision making about blades condition by the above mentioned features application. Classification of turbine blade condition was carried out using a two-layer Probability Neural Network (PNN).