Abstract
The obtaining of gas turbine engine mathematical models from experimental data with identification or refinement of their unit characteristics and the use of such models in parametric diagnostics methods is considered. The solution of improperly posed problems, where the number of equations is not equal to the number of unknowns, is proposed to be solved by a mathematical method specially developed using the stability of estimates.
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REFERENCES
Ahmed, H.S.A. and Osipov, B.M., Multimode Identification to Obtain an Adequate Gas Turbine Engine Model for its Diagnosing by Thermal-Gas Dynamic Parameters, Vestnik MAI, 2020, vol. 27, no. 1, pp. 133–143.
Ahmed, H.S.A. and Osipov, B.M., Multi-Mode Identification of Obtaining the Adequate Model of Turbojet Engine TJ-100A-Z for Diagnostics by Thermalgasdynamic Parameters, Vestnik PNIPU, 2020, no. 60, pp. 5–14.
Ahmed, H.S. and Osipov, B.M., Diagnostics of a Gas Turbine Engine with Localization of Defects in its Nodes, Vestnik PNIPU, 2020, no. 61, pp. 12–21.
Ahmed, H.S.A. and Osipov, B.M., Diagnostics Algorithm with Gas Turbine Engine Mathematical Model Application, Vestnik MAI, 2020, vol. 27, no. 3, pp. 155–166.
Keba, I.V., Diagnostika aviatsionnykh gazuturbinnykh dvigatelei (Diagnostics of Aviation Gas-Turbine Engines), Moscow: Transport, 1980.
Tikhonov, A.N., On Incorrect Tasks of Linear Algebra and Reliable Method of their Solution, Doklady AN, 1965, vol. 163, no. 3, pp. 591–595.
Akhmedzyanov, A.M., Dubravskii, N.G., and Tunakov, A.P., Diagnostika sostoyaniya VRD po termogazodinamicheskim parametram (Diagnostics of Air-Jet Engine Condition by Thermogasdynamic Parameters), Moscow: Mashinostroenie, 1983.
Knyazeva, V.V., Chubarov, O.Yu., and Neretin, E.S., Fault Conditions Diagnostic Technique for Firing Trials Based on Controlled Parameters Measurements, Vestnik MAI, 2014, vol. 21, no. 5, pp. 106–115.
Ntantis, E.L., Capability Expansion of Non-Linear Gas Path Analysis, Ph.D. Thesis, UK: Cranfield University, 2008.
Celaya, J.R., Saxena, A., and Goebel, K., Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms Based on Kalman Filter Estimation, Proc. of the Annual Conference of the Prognostics and Health Management Society, Minneapolis, USA, 2012, vol. 3.
Dmitrienko, G.V., Mukhin, D.V., Rivin, G.L., and Fedorov, A.A., Radiowave Methods of Polymer Composite Defect Diagnostics under Nonsteady Temperatures, Izv. Vuz. Av. Tekhnika, 2020, vol. 63, no. 2, pp. 176–180 [Russian Aeronautics (Eng. Transl.), vol. 63, no. 2, pp. 366–370].
Arkhipov, A.N., Volgina, M.V., Matushkin, A.A., Ravikovich, Yu.A., and Kholobtsev, D.P., Probabilistic Assessment of Life for Gas Turbine Engine Parts Considering Manufacture Tolerances, Izv. Vuz. Av. Tekhnika, 2019, vol. 62, no. 3, pp. 95–102 [Russian Aeronautics (Eng. Transl.), vol. 62, no. 3, pp. 455–462].
Sabirzyanov, A.N., Glazunov, A.I., Kirillova, A.N., and Titov, K.S., Simulation of a Rocket Engine Nozzle Discharge Coefficient, Izv. Vuz. Av. Tekhnika, 2018, vol. 61, no. 2, pp. 105–111 [Russian Aeronautics (Eng. Transl.), vol. 61, no. 2, pp. 257–264].
Fershalov, Yu.Ya., Technique for Physical Simulation of Gasodynamic Processes in the Turbomachine Flow Passages, Izv. Vuz. Av. Tekhnika, 2012, vol. 55, no. 4, pp. 71–74 [Russian Aeronautics (Engl. Transl.), vol. 55, no. 4, pp. 424–429].
Yashkov, V.A. and Porunov, A.A., State-of-the-Art and Prospects for Development of Fluidic Devices for Measurement of Kinematical Parameters in Moving Objects, Izv. Vuz. Av. Tekhnika, 2011, vol. 54, no. 2, pp. 76–80 [Russian Aeronautics (Engl. Transl.), vol. 54, no. 2, pp. 227–232].
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Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Aviatsionnaya Tekhnika, 2021, No. 2, pp. 113 - 119.
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Ahmed, H.S., Osipov, B.M. Algorithm for Gas Turbine Engine Diagnostics with the Use of Empirical Mathematical Model. Russ. Aeronaut. 64, 297–304 (2021). https://doi.org/10.3103/S1068799821020185
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DOI: https://doi.org/10.3103/S1068799821020185