Application of clustering method for the ambiguity groups detection in the diagnostic of analog systems

摘要

W artykule przedstawiono zastosowanie metod uczenia bez nadzoru w celu wykrycia grup niepewno?ci w danych wykorzystywanych do diagnostyki systemów analogowych. Dane przetwarzane s? w celu znalezienia podobnych do siebie przyk?adów nale??cych do ró?nych kategorii uszkodzeń. Metoda clusteringu grafowego zosta?y przetestowane na przyk?adzie silnika indukcyjnego.%The paper presents application of unsupervised learning methods to detect ambiguity groups in the data used in the diagnostics of analog systems. The proposed approach processes labelled data sets from simulated systems to find similar examples belonging to different faulty states. Two algorithms were used in the presented research: graph clustering. Efficiency of the method is compared and verified against the exemplary electrical system, i.e. induction machine. Future prospects of such methods will be also included.