Algorytm diagnostyki zużycia ostrza oparty na wielu sieciach neuronowych *

STRESZCZENIE: Porównano różne sposoby określania zużycia ostrza – z wykorzystaniem sieci neuronowych RBF, metody hierarchicznej oraz standardowego zliczania czasu pracy. Analizę sygnałów z procesu skrawania przeprowadzono dla trzech różnych zestawów badań doświadczalnych. Wyniki otrzymane w przypadku zespołu sieci neuronowych są zbliżone do wyników z algorytmu hierarchicznego – jest to potencjalnie bardzo skuteczna metoda szacowania zużycia ostrza.

SŁOWA KLUCZOWE: diagnostyka stanu narzędzia, sieci neuronowe RBF

ABSTRACT: Presented is a comparison of different methods of estimating tool wear – obtained for group of RBF neural networks, hierarchical methods and the standard time counting. The analysis of the signals from the machining process carried out for three different experiments, clearly demonstrating the effect of presented methods. The results obtained for group of RBF neural networks are similar to results obtained for hierarchical methods.

KEYWORDS: tool condition monitoring, RBF neural network

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DOI: https://doi.org/10.17814/mechanik.2017.3.42