Vashchenko Y. Improving technology of diagnosing state for traction asynchronous drive electric rolling stock

Object of research - emergency operating modes and diagnosing process technical condition of electric traction rolling stock with asynchronous engines. Aim of research - improve diagnostics technology of asynchronous electric traction drive rolling stock by determining the characteristic features of emergency operation, identification these regimes and development of methods for prevention potential failures. Methods - common methods of theoretical electrical engineering; theory of electrical machines; automatic control theory; methods of measurement and data processing; simulation modeling techniques; methods of spectral analysis techniques based on models and object recognition methods and decision making. Theoretical and practical results, is to empower staff protection features through use technology diagnosis based on algorithms developed in application package Matlab / Simulink. The recommendations for the practical use proposed technologies for designing and configuring protection systems asynchronous traction electric rolling stock. Scientific innovation: its received further development mathematical model of induction motor for emergency operation research, which is different from known magnetization curve approximation using fuzzy logic. Its received further development analysis of transient electromagnetic processes asynchronous traction electric rolling stock that allows to determine diagnostic parameters and characteristics inherent in different types emergency operation. For the first time the technique of identifying inverter unbalance modes and other faults based on spectrum analysis of input inverter current and bandpass filters, which differs from the known adaptation to variable speed, decrease the required number of monitored parameters and increased calculation speed. For the first time the technique of diagnosing parameters using the extended Kalman filter algorithm, which is different from the known possibility of evaluating the effectiveness of its work on statistical criterias. Further developed methods of diagnostics of asynchronous electric traction drive rolling stock, based on artificial neural networks that can recognize and decide on emergency regimes. The degree of implementation, the practical value of confirmed acts for implementation results thesis at state enterprise "Research Institute" HEMZ ", in educational process of Ukrainian state university of railway transport and educational-science institute retraining and increase personnel qualifications (Kharkov city). Using area - industry design, manufacture and maintenance of electric transport, development diagnostics and protection systems rolling stock equipment, in learning process.