Zobrazeno 1 - 4
of 4
pro vyhledávání: '"DUYGU BAĞCI DAŞ"'
Autor:
DUYGU BAĞCI DAŞ, Derya Birant
Autonomous Underwater Vehicles (AUV) have a significant role in ocean research and the marine environment with the aim of performing different scientific and commercial tasks. During an underwater operation, fault detection for AUV is essential for c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dbb45c1cd9e47ce4fb8d9fbd8025ad83
https://avesis.deu.edu.tr/publication/details/76c28748-7f28-4d2d-94c0-9fa8a63ac1f3/oai
https://avesis.deu.edu.tr/publication/details/76c28748-7f28-4d2d-94c0-9fa8a63ac1f3/oai
Autor:
Oğuzhan Daş, DUYGU BAĞCI DAŞ
This study examines the impact of the mother wavelet, sensor selection, and machine learning (ML) models for smart fault diagnosis of rotating machines via discrete wavelet transform (DWT). The ability of Daubechies, Haar, Biorthogonal (Bior), Symlet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abe4bbadccb6ed46d204b9eb60a12f19
https://hdl.handle.net/11454/79476
https://hdl.handle.net/11454/79476
Autor:
Oğuzhan DAŞ, Duygu BAĞCI DAŞ
Publikováno v:
European Journal of Science and Technology.
The Finite Element Method (FEM) is a popular technique that is employed to analyze and understand the behavior of a structure. Although it has various advantages, there are some drawbacks such as developing accurate mathematical models, the computati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b9dbc1a963d5664253b8eff0fca500e
https://doi.org/10.31590/ejosat.1135944
https://doi.org/10.31590/ejosat.1135944
Publikováno v:
Heliyon, Vol 9, Iss 6, Pp e17584- (2023)
As the concept of Industry 4.0 is introduced, artificial intelligence-based fault analysis is attracted the corresponding community to develop effective intelligent fault diagnosis and prognosis (IFDP) models for rotating machinery. Hence, various ch
Externí odkaz:
https://doaj.org/article/a8e29d7317de4a54a6e03fd1a127c940