Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Yuri A. W. Shardt"'
Publikováno v:
IEEE Access, Vol 8, Pp 9115-9123 (2020)
This paper proposes a modified relevance vector machine with slow feature analysis fault classification for industrial processes. Traditional support vector machine classification does not work well when there are insufficient training samples. A rel
Externí odkaz:
https://doaj.org/article/74a13c1c9d9144ed95ead5195c5022ec
Publikováno v:
IEEE Access, Vol 6, Pp 6777-6782 (2018)
This paper proposes a simultaneous robust decoupled output feedback control approach for multivariate industrial processes with parameter uncertainties. Based on the desired control performance indicators, the expected transfer function of the closed
Externí odkaz:
https://doaj.org/article/9c208c0b7cbe4c919674d03a5d45e3f1
Publikováno v:
IEEE Access, Vol 6, Pp 43808-43823 (2018)
The explosion of different fault detection (FD) statistics in multivariate statistics-based FD approaches has meant that the practitioner is faced with the unenviable job of determining which to use in a given circumstance. Moreover, compared to exte
Externí odkaz:
https://doaj.org/article/80c5b78cc29c4fc99a2acb4eb023b29c
Publikováno v:
Mathematics, Vol 9, Iss 16, p 1947 (2021)
The paper deals with the problem of developing a multi-output soft sensor for the industrial reactive distillation process of methyl tert-butyl ether production. Unlike the existing soft sensor approaches, this paper proposes using a soft sensor with
Externí odkaz:
https://doaj.org/article/2bf8eae4522146bcae239002511b8d11
Publikováno v:
Journal of Control Science and Engineering, Vol 2017 (2017)
Artificial bee colony (ABC) is a novel population-based optimization method, having the advantage of less control parameters, being easy to implement, and having strong global optimization ability. However, ABC algorithm has some shortcomings concern
Externí odkaz:
https://doaj.org/article/c09cf6712736488698c2543c5a0da15e
Publikováno v:
Journal of Control Science and Engineering, Vol 2017 (2017)
The thickness of the steel strip is an important indicator of the overall strip quality. Deviations in thickness are primarily controlled using the automatic gauge control (AGC) system of each rolling stand. At the last stand, the monitoring AGC syst
Externí odkaz:
https://doaj.org/article/a31ddadce11b4b309eeb809dbfd9ec2e
Publikováno v:
Sensors, Vol 18, Iss 9, p 3058 (2018)
Advanced technology for process monitoring and fault diagnosis is widely used in complex industrial processes. An important issue that needs to be considered is the ability to monitor key performance indicators (KPIs), which often cannot be measured
Externí odkaz:
https://doaj.org/article/9659b0b5c3574aebb86ce4f20eb1ecf7
Publikováno v:
Energies, Vol 11, Iss 5, p 1150 (2018)
This paper proposes a second-order active disturbance rejection control (ADRC)-based control strategy with an integrated design of the flux damping method, for the fault ride-through (FRT) improvement in wind power generation systems with a doubly-fe
Externí odkaz:
https://doaj.org/article/ed21757821d14c2f8f7f242083f81379
Publikováno v:
IEEE Sensors Journal. 22:19533-19542
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4f566b6544314ae4df4d4e68632ffbb
https://doi.org/10.1109/jsen.2022.3200069
https://doi.org/10.1109/jsen.2022.3200069
Autor:
Chen Ou, Hongqiu Zhu, Yuri A. W. Shardt, Lingjian Ye, Xiaofeng Yuan, Yalin Wang, Chunhua Yang
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-11
The growth of data collection in industrial processes has led to a renewed emphasis on the development of data-driven soft sensors. A key step in building an accurate, reliable soft sensor is feature representation. Deep networks have shown great abi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4b1968b8469d2ac842b223ee5e656a1
https://doi.org/10.1109/tnnls.2022.3144162
https://doi.org/10.1109/tnnls.2022.3144162