Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mohammad-Reza Pourramezan"'
Publikováno v:
ACS Omega, Vol 9, Iss 1, Pp 1398-1415 (2023)
Externí odkaz:
https://doaj.org/article/5968c6b8148349a5bea3cf7c97621686
Publikováno v:
Lubricants, Vol 11, Iss 9, p 382 (2023)
Predictive maintenance of mechanical systems relies on accurate condition monitoring of lubricants. This study assesses the performance of soft computing models in predicting the elemental spectroscopy (Fe, Pb, Cu, Cr, Al, Si, and Zn) of engine lubri
Externí odkaz:
https://doaj.org/article/75ee3825a05445f28aadc570130a1246
Condition monitoring is a primary principle for predictive maintenance. In this regard, several techniques have been employed, each of which has its strengths and weaknesses. In this work, the relationships between the electrical (ε', ε", tan δ) a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f442bf034dbd25ba58aaa2b394c9f5f
Publikováno v:
Neural Computing and Applications. 34:5465-5477
Evaluating the condition of the lubricant plays an influential role in the maintenance engineering of mechanical systems. This study has several objectives and finally offers a method based on the neural network. That method uses more limited indicat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06d533ffe82bcbc591c433d00734ee54
https://doi.org/10.1007/s00521-021-06688-y
https://doi.org/10.1007/s00521-021-06688-y
Publikováno v:
Expert Systems with Applications. 203:117494
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f97a8ca5afffd6cbaf679b9ddbddf84
https://doi.org/10.1016/j.eswa.2022.117494
https://doi.org/10.1016/j.eswa.2022.117494