Baza Publikacji Pracowników Politechniki Lubelskiej

Status:
Autorzy:	Gajewski Jakub, Jedliński Łukasz, Jonak Józef
Rok wydania:	2013
Wersja dokumentu:	Drukowana \| Elektroniczna
Język:	angielski
Wolumen/Tom:	35
Strony:	30 - 36
Impact Factor:	1,589
Web of Science® Times Cited:	36
Scopus® Cytowania:	44
Bazy:	Web of Science \| Scopus \| WoS \| Scopus
Efekt badań statutowych	NIE
Materiał konferencyjny:	NIE
Publikacja OA:	TAK
Licencja:
Sposób udostępnienia:	Witryna wydawcy
Wersja tekstu:	Ostateczna wersja opublikowana
Czas opublikowania:	W momencie opublikowania
Abstrakty:	angielski
	In the article, classification test results of the condition of mining tool blades were presented. The tools work as a unit on a multi-tool head. On the research position, signals of mining power for sharp and blunt tools were recorded. Noise of signal power is reduced with the use of discrete wavelet transform in order to emphasize information. Statistical features of signals of mining power were specified, which were later used as entry data for the artificial neural network. Then, the fuzzy neural network, on the basis of calculated signal features, classifies the mining tools in terms of their wear.

Classification of wear level of mining tools with the use of fuzzy neural network