Open AccessThe artificial intelligence methods testing in case of engineering diagnostics system creation of the synchronous machines
Author(s) -
Владимир Иосифович Полищук,
K.V. Baratova
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/618/1/012042
Subject(s) - rotor (electric) , fuzzy logic , computer science , reliability (semiconductor) , control engineering , toolbox , fault (geology) , winding machine , synchronous motor , artificial intelligence , engineering , mechanical engineering , power (physics) , physics , electrical engineering , quantum mechanics , seismology , programming language , geology , operations management
Due to the lack of the exact mathematical processes description for internal faults diagnosis of synchronous machine rotor winding. To solve the problem of concurrent processing of the indirect diagnostic signs complex connected with the concrete type of multiple disabilities. It is the author’s opinion that such problem is necessary to solve by artificial intelligence systems accepted in the theory and practice. The architecture of intelligent diagnostic system and the technical condition forecast of the synchronous machine rotor winding on the basis of the fuzzy logic mathematical tool are offered. Diagnosing reliability of and selectivity support determination of synchronous machine rotor winding defect category is reached by complex conjugation of separation of diagnostic information sensitive methods on the basis of intellectual digital signal processing methods. It is proved experimentally that the fuzzy logic using provided diagnosing reliability of synchronous machine rotor winding turn-to-turn short-circuit at the 1,5% level of rotor pole winding Visualization of all making decision stages about the existence and defect type was made in Fuzzy Logic Toolbox software package.