Özet:

The structure of diagnosing the technical condition of the gas turbine engine (GTE) is given. It is proposed a method of training the intellectual automated system of diagnostics and control reconfiguration (IASDCR) by GTE modes based on integration of fuzzy logic and neural networks. The theoretical and experimental capabilities of IASDCR classification of current condition of GTE in specific operational situations are proposed. It is designed and synthesized the structure of IASDCR GTE, based on the proposed model. The method provides the ability to customize such systems for the diagnosis and management of different types of GTE reconfiguration during their operation, thereby increasing the reliability of classification and prediction of residual life, and prevents the transition of emergency situation in catastrophic situation. The expediency of using hybrid IASDCR based on radial basis networks and fuzzy logic theory, which allowed to classify the vibrational state GTE DR-59L with a probability of 0,96 and GTE DT-71P with a probability of 0,92. Author Biography Микола Петрович Кравчук, National Aviation University, Komarova Ave, 1, Kyiv, Ukraine, 03058 Candidate of Technical Sciences, Assistant Department of Automation and Energy Management 

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