V.G. Avgustinovich - Dr.Sc. (Eng.), Professor, Department of Aircraft Engines, Perm National Research Polytechnic University. E-mail: august@avid.ru T.A. Kuznetsova - Ph.D. (Eng.), Associate Professor, Department of Design and Technologies in Electrical Engineering, The Head of Distance Education Technologies Centre, Perm National Research Polytechnic University. E-mail: tatianaakuznetsova@gmail.com

The actual task of modern instrument-engineering is the improvement of the reliability of automatic control of multi-dimensional technological objects based on the development of robust on-board automatic control systems (ACS). The reliability of a gas turbine aircraft engine (GTE) and flight safety is determined by the optimal implementation of real-time data obtaining functions. The monitoring and fault diagnosis problem solution inevitably requires the use of identification methods. The reliability of modern digital automatic control systems of aircraft engine is increased in the flight conditions through the creation of algo-rithmic information redundancy based on built-in mathematical model GTE (GTE BMM). The structure and the accuracy of the BMM determine the real-time identification accuracy, the automatic control quality and engine reliability. Since the on-board ACS operates under external and internal disturbances (noise) in the channel HMW and measure-ment channel, an actual task is to improve the accuracy of the model identification of engine parameters according to the cur-rent on-board measurements. The present study examined the solution of the problem through the development of on-board linear adaptive engine model for civil aircraft, built in the electronic controller, which includes the development of algorithms for the automatic para-metric diagnosis of gas path of an aircraft engine. The relationship of defects arising in GTD noncontrolled changes of the nodes - characteristics (not measurable), and controlled changes (measurable) parameters provides a diagnostic algorithm for the development of gas path defects. The main controlled (measured) parameters are considered: the temperature after the turbine, the outlet pressure of high pressure compressor (HPC), the rotations of the speed of rotors of high pressure turbine (HPT), and low pressure turbine (LPT). For identification of the GTE state was provided the use of a common method of influence coefficient matrix. The me-thod allows for the values available for the measurement, to find changes such GTD characteristics as efficiencies nodes flow area turbine nozzle devices, etc., are not available for the measurement. The matrix of influence coefficients obtained experimentally for each engine model. Coefficients of influence can be de-termined using a mathematical model of high-level engine. For the system of normal equations, the solution of which there is a change of the independent variables, the resulting sum of the squares of the deviation between the parameters of the ma-thematical model and real-GTE is minimized. This system of equations is characterized by the ability to: bad conditionality matrix system of linear equations (the determinant is near to zero); uncertain systems of equations (the number of equations is less than the number of unknowns). To improve the accuracy of identification solutions and sustainability provides the numerical method of Monte Carlo was used. The parametric diagnostic algorithm based on the LPτ ? sequence was developed and tested.

 

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