Diagnostics of rolling bearings using artificial neural networks

Autor:	M V Suslov, A l V Bykov, A I Vinokur, V P Petrov, E G Bezzateeva, S N Litunov, G B Kulikov
Rok vydání:	2021
Předmět:	History Artificial neural network Computer science Control engineering Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1901:012027
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1901/1/012027
Popis:	The vibration of bearings No. 60,206 with radial clearance of 0…0.45 mm is investigated. Analysis of the frequency response (FR) of vibration acceleration reveals information frequencies of 6 Hz, 15 Hz, 26 Hz, and 46 Hz, which coincide with the calculated values. The dependence of the vibration acceleration amplitude on the radial clearance for the specified frequencies is determined. The possibility of rolling bearing wear estimation by vibroacoustic diagnostic methods using artificial neural networks is proved. Diagnostic accuracy with the 4:4-3:1 MI network ranges from 75.6% for a radial clearance of 0.15 mm to 100% for a clearance of 0 mm.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bb23cd55dccbddcf5591c37432dc1700 https://doi.org/10.1088/1742-6596/1901/1/012027 Zobrazit plný text záznamu