Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Alexander E. Prosvirin"'
Autor:
Syed Ahmmed, Prajoy Podder, M. Rubaiyat Hossain Mondal, S M Atikur Rahman, Somasundar Kannan, Md Junayed Hasan, Ali Rohan, Alexander E. Prosvirin
Publikováno v:
BioMedInformatics, Vol 3, Iss 4, Pp 1124-1144 (2023)
This study focuses on leveraging data-driven techniques to diagnose brain tumors through magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we introduce and fine-tune two robust frameworks, ResNet 50 and Inception V3,
Externí odkaz:
https://doaj.org/article/8b386f2859d748498b71d3e1d7b9e985
Publikováno v:
IEEE Access, Vol 9, Pp 65838-65854 (2021)
Centrifugal pumps are important types of electro-mechanical machines used for fluid and energy conveyance. Mechanical faults in centrifugal pumps lead to abnormal impacts in the vibration signal of the system. Those impacts induce nonstationarity in
Externí odkaz:
https://doaj.org/article/6a7feaea69ba4cd9b7ebb53a72a2f83f
Publikováno v:
IEEE Access, Vol 8, Pp 223030-223040 (2020)
This paper proposes a three-stage fault diagnosis strategy for multistage centrifugal pumps. First, the proposed method identifies and selects fault characteristic modes of vibration to overcome the substantial noise produced by other unrelated macro
Externí odkaz:
https://doaj.org/article/59d2331b7e914c459c80d31f0f8f4215
Publikováno v:
IEEE Access, Vol 7, Pp 121728-121741 (2019)
A rubbing fault is a complex non-linear and non-stationary fault that frequently occurs in rotating machinery such as turbines. One of the most frequently applied signal processing techniques for the analysis of rub-impact faults in rotating machines
Externí odkaz:
https://doaj.org/article/9cf3f32243a140f1994e7412b16d88fd
Publikováno v:
Sensors, Vol 21, Iss 19, p 6579 (2021)
This paper proposes a Gaussian mixture model-based (GMM) bearing fault band selection (GMM-WBBS) method for signal processing. The proposed method benefits reliable feature extraction using fault frequency oriented Gaussian mixture model (GMM) window
Externí odkaz:
https://doaj.org/article/1c2d03135494483c9932f3d3f14b1445
Publikováno v:
Sensors, Vol 21, Iss 1, p 18 (2020)
Gearbox fault diagnosis based on the analysis of vibration signals has been a major research topic for a few decades due to the advantages of vibration characteristics. Such characteristics are used for early fault detection to guarantee the enhanced
Externí odkaz:
https://doaj.org/article/0655be0ec3ba4534af97edb245871774
Publikováno v:
Sensors, Vol 20, Iss 21, p 6265 (2020)
A blade rub-impact fault is one of the complex and frequently appearing faults in turbines. Due to their nonlinear and nonstationary nature, complex signal analysis techniques, which are expensive in terms of computation time, are required to extract
Externí odkaz:
https://doaj.org/article/cbb6ed0bbf074e76a52cc693a2c353fb
Publikováno v:
Sensors, Vol 20, Iss 7, p 1884 (2020)
Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is challenging but necessary to ensure safety and economical operation in industries. Research has shown that bearing faults are the most frequently occurring
Externí odkaz:
https://doaj.org/article/641c12e0819a4d5eb3eb1dab82f849e9
Publikováno v:
Applied Sciences, Vol 10, Iss 4, p 1344 (2020)
A robot manipulator is a multi-degree-of-freedom and nonlinear system that is used in various applications, including the medical area and automotive industries. Uncertain conditions in which a robot manipulator operates, as well as its nonlinearitie
Externí odkaz:
https://doaj.org/article/5aca6725713d4af3aaa8f34ce041f2c7
Publikováno v:
Sensors, Vol 18, Iss 7, p 2040 (2018)
The complex nature of rubbing faults makes it difficult to use traditional signal analysis methods for feature extraction. Various time-frequency analysis approaches based on signal decomposition, such as empirical mode decomposition (EMD) and ensemb
Externí odkaz:
https://doaj.org/article/09e1522177724f25adadbd9ef6ae4959