Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Beike Zhang"'
Publikováno v:
Kemija u Industriji, Vol 66, Iss 11-12, Pp 601-610 (2017)
HAZOP (Hazard and Operability Analysis) is a method of safety analysis, which is widely used in chemical processes. The conventional methods for safety analysis consist of human based safety analysis and computer aid safety analysis. All of them are
Externí odkaz:
https://doaj.org/article/a089e78507754fe79258b748fb1ea820
Publikováno v:
In IFAC Proceedings Volumes 2013 46(13):478-483
Publikováno v:
Journal of Loss Prevention in the Process Industries. 82:105005
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f3fe6114b5e8ab22c0da3610c006769
https://doi.org/10.1016/j.jlp.2023.105005
https://doi.org/10.1016/j.jlp.2023.105005
Publikováno v:
Journal of Intelligent Manufacturing. 32:971-987
Intelligent fault diagnosis methods based on signal analysis have been widely used for bearing fault diagnosis. These methods use a pre-determined transformation (such as empirical mode decomposition, fast Fourier transform, discrete wavelet transfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::97657a309c648d3b208a92eaf8312c07
https://doi.org/10.1007/s10845-020-01600-2
https://doi.org/10.1007/s10845-020-01600-2
Publikováno v:
Processes
Volume 9
Issue 7
Processes, Vol 9, Iss 1178, p 1178 (2021)
Volume 9
Issue 7
Processes, Vol 9, Iss 1178, p 1178 (2021)
In the field of chemical safety, a named entity recognition (NER) model based on deep learning can mine valuable information from hazard and operability analysis (HAZOP) text, which can guide experts to carry out a new round of HAZOP analysis, help p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5fbd5be4633fb45375fed69f156968f
Publikováno v:
Computers in Industry. 139:103647
Hazard and operability analysis (HAZOP) is a remarkable representative in industrial safety engineering. However, a great storehouse of industrial safety knowledge (ISK) in HAZOP reports has not been thoroughly exploited. In order to reuse and unlock
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f11d7f5cbe159a5135454e351546007
https://doi.org/10.1016/j.compind.2022.103647
https://doi.org/10.1016/j.compind.2022.103647
Publikováno v:
Journal of Loss Prevention in the Process Industries. 76:104736
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09f8ad319df66637b67fdf321c2763f2
https://doi.org/10.1016/j.jlp.2022.104736
https://doi.org/10.1016/j.jlp.2022.104736
Publikováno v:
2020 Chinese Automation Congress (CAC).
Under the background of big data era, the safety management of construction enterprises should turn their attention to big data, enhance the depth and breadth of information utilization, and explore the safety management of construction enterprises i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::104ffad3084b54c8358167530ec7e0b7
https://doi.org/10.1109/cac51589.2020.9327108
https://doi.org/10.1109/cac51589.2020.9327108
Publikováno v:
2020 Chinese Automation Congress (CAC).
HAZOP plays an important role in chemical safety, in the project of Chinese named entity recognition of HAZOP, In response to the problem of low accuracy of entity recognition and low efficiency of model training in the past methods, this paper propo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5879f77a87b8057bea62453f9663cb47
https://doi.org/10.1109/cac51589.2020.9326618
https://doi.org/10.1109/cac51589.2020.9326618
Publikováno v:
2020 Chinese Control And Decision Conference (CCDC).
The traditional fault diagnosis method of rolling bearing relies on signal analysis and processing technology, and the accuracy of fault identification is low; artificial neural network(ANN) and support vector machine(SVM) need to extract features ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::470bb0d81c4117dad430272f2cde403e
https://doi.org/10.1109/ccdc49329.2020.9164026
https://doi.org/10.1109/ccdc49329.2020.9164026