Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Mohamed-Salah Ouali"'
Publikováno v:
Results in Engineering, Vol 19, Iss , Pp 101234- (2023)
Analysis of industrial data imposes several challenges. These data are acquired from heterogeneous sources such as sensors, cameras, IoT, etc, and are stored in different structures and formats with different sampling frequencies. They are also store
Externí odkaz:
https://doaj.org/article/176e0c7fec984d52ab7d266549729d69
Autor:
Kerelous Waghen, Mohamed-Salah Ouali
Publikováno v:
Algorithms, Vol 15, Iss 6, p 178 (2022)
This paper develops a data-driven fault tree methodology that addresses the problem of the fault prognosis of an aging system based on an interpretable time causality analysis model. The model merges the concepts of knowledge discovery in the dataset
Externí odkaz:
https://doaj.org/article/1af179382beb4fe2beb89d59cc46c603
Publikováno v:
Journal of Intelligent Manufacturing. 34:57-83
The complexity of industrial processes imposes a lot of challenges in building accurate and representative causal models for abnormal events diagnosis, control and maintenance of equipment and process units. This paper presents an innovative data-dri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::585ce5f1aea691d6750f01d929777f33
https://doi.org/10.1007/s10845-021-01903-y
https://doi.org/10.1007/s10845-021-01903-y
Publikováno v:
IFAC-PapersOnLine. 55:1582-1587
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::844c6b8f5c169bacb0daff8192f341da
https://doi.org/10.1016/j.ifacol.2022.09.616
https://doi.org/10.1016/j.ifacol.2022.09.616
Publikováno v:
Journal of Quality in Maintenance Engineering, 2015, Vol. 21, Issue 3, pp. 346-357.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JQME-03-2014-0013
Publikováno v:
Journal of Intelligent Manufacturing. 33:1531-1544
This paper proposes a novel data preprocessing method that converts numeric data into representative graphs (polygons) expressing all of the relationships between data variables in a systematic way based on Hamiltonian cycles. The advantage of the pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60c7d7143832afc27f19a6cafb4e0ad4
https://doi.org/10.1007/s10845-021-01742-x
https://doi.org/10.1007/s10845-021-01742-x
Autor:
Mohamed-Salah OUALI, Kerelous Waghen
Publikováno v:
Algorithms; Volume 15; Issue 6; Pages: 178
This paper develops a data-driven fault tree methodology that addresses the problem of the fault prognosis of an aging system based on an interpretable time causality analysis model. The model merges the concepts of knowledge discovery in the dataset
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::056cefa3fe67c6b8caf60513630d7874
Publikováno v:
2022 Annual Reliability and Maintainability Symposium (RAMS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7fb84f8cc58334265c5e6f7c6e75a72
https://doi.org/10.1109/rams51457.2022.9893981
https://doi.org/10.1109/rams51457.2022.9893981
Publikováno v:
Expert Systems with Applications. 203:117288
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1148e71ad5b701bf5c95530b862334d8
https://doi.org/10.1016/j.eswa.2022.117288
https://doi.org/10.1016/j.eswa.2022.117288
Autor:
Mohamed-Salah Ouali, Kerelous Waghen
Publikováno v:
Expert Systems with Applications. 136:376-391
This paper proposes an effective hybrid-based methodology, called interpretable logic tree analysis (ILTA), which characterizes and quantifies event causality occurring in engineering systems with the minimum involvement of human experts. It integrat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71873f5a4824dc8c873e8d6576ada45f
https://doi.org/10.1016/j.eswa.2019.06.042
https://doi.org/10.1016/j.eswa.2019.06.042