Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Meng Hee, Lim"'
Publikováno v:
In Energy Conversion and Management 15 April 2022 258
Publikováno v:
International Journal of COMADEM; Apr2024, Vol. 27 Issue 2, p45-50, 6p
Publikováno v:
IEEE Access, Vol 7, Pp 46885-46897 (2019)
The development of rolling element bearing fault diagnosis systems has attracted a great deal of attention due to bearing components having a high tendency toward unexpected failures. However, under low-speed operating conditions, the diagnosis of be
Externí odkaz:
https://doaj.org/article/001aa5d8bb7e4294bfa5da5e2937348e
Publikováno v:
IEEE Access, Vol 7, Pp 122644-122662 (2019)
In the age of industry 4.0, deep learning has attracted increasing interest for various research applications. In recent years, deep learning models have been extensively implemented in machinery fault detection and diagnosis (FDD) systems. The deep
Externí odkaz:
https://doaj.org/article/94b7e98584e240a8949030d20c7a1e3b
Publikováno v:
IEEE Access, Vol 7, Pp 138211-138232 (2019)
Genetic algorithm (GA) is an established machine learning technique used for heuristic optimisation purposes. However, this natural selection-based technique is prone to premature convergence, especially of the local optimum event. The presence of st
Externí odkaz:
https://doaj.org/article/e8b8c336fd854e258fed0e5c03b87dba
Publikováno v:
Sensors, Vol 21, Iss 23, p 8114 (2021)
Rotating machinery is one of the major components of industries that suffer from various faults due to the constant workload. Therefore, a fast and reliable fault diagnosis method is essential for machine condition monitoring. In this study, noise el
Externí odkaz:
https://doaj.org/article/ac67e3dcdb62438db1a4d68aedb6cd02
Publikováno v:
PLoS ONE, Vol 12, Iss 12, p e0189143 (2017)
A major issue of machinery fault diagnosis using vibration signals is that it is over-reliant on personnel knowledge and experience in interpreting the signal. Thus, machine learning has been adapted for machinery fault diagnosis. The quantity and qu
Externí odkaz:
https://doaj.org/article/13245355a7194cbead63d3f00a64872d
Publikováno v:
MATEC Web of Conferences, Vol 255, p 02009 (2019)
This article aims to provide a comprehensive review on the condition monitoring techniques of underground storage tanks (UST). Generally, the UST has long been a favourite toxic substance reservation apparatus, thanks to its large capacity and minimu
Externí odkaz:
https://doaj.org/article/f0bfa006e8ed4760aa25aa9db636de25
Publikováno v:
MATEC Web of Conferences, Vol 255, p 02004 (2019)
Intelligent machinery fault diagnosis commonly utilises statistical features of sensor signals as the inputs for its machine learning algorithm. Due to the abundance of statistical features that can be extracted from raw signals and the accuracy of i
Externí odkaz:
https://doaj.org/article/d8f03bfe983444f2b272cad0c0fa7465
Publikováno v:
IEEE Transactions on Industrial Informatics. 16:6263-6271
Massive volumes of data are needed for deep learning (DL) models to provide accurate diagnosis results. Numerous studies of fault diagnosis systems have demonstrated the effectiveness of DL models over shallow machine learning (SL) in terms of featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31325422a6258c4ee91b90f096aadbfc
https://doi.org/10.1109/tii.2020.2967822
https://doi.org/10.1109/tii.2020.2967822