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Intelligent anti-corrosion expert system based on big data analysis.

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Titel: Intelligent anti-corrosion expert system based on big data analysis.
Autoren: Zhao, Liang, Tao, Wen, Wang, Guangwen, Wang, Lida, Liu, Guichang
Quelle: Anti-Corrosion Methods & Materials; 2021, Vol. 68 Issue 1, p17-28, 12p
Schlagwörter: DATA management, PETROLEUM chemical plants, TAYLORISM (Management), THREE-dimensional modeling, RISK assessment
Abstract: Purpose: The paper aims to develop an intelligent anti-corrosion expert system based on browser/server (B/S) architecture to realize an intelligent corrosion management system. Design/methodology/approach: The system is based on Java EE technology platform and model view controller (MVC) three-tier architecture development model. The authors used an extended three-dimensional interpolation model to predict corrosion rate, and the model is verified by cross-validation method. Additionally, MySQL is used to realize comprehensive data management. Findings: The proposed anti-corrosion system thoroughly considers a full use of corrosion data, relevant corrosion prediction and efficient corrosion management in one system. Therefore, this system can achieve an accurate prediction of corrosion rate, risk evaluation, risk alert and expert suggestion for equipment in petrochemical plants. Originality/value: Collectively, this present study has important ramifications for the more efficient and scientific management of corrosion data in enterprises and experts' guidance in controlling corrosion status. At the same time, the digital management of corrosion data can provide a data support for related theoretical researches in corrosion field, and the intelligent system also offers examples in other fields to improve system by adding intelligence means. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
Beschreibung
Abstract:Purpose: The paper aims to develop an intelligent anti-corrosion expert system based on browser/server (B/S) architecture to realize an intelligent corrosion management system. Design/methodology/approach: The system is based on Java EE technology platform and model view controller (MVC) three-tier architecture development model. The authors used an extended three-dimensional interpolation model to predict corrosion rate, and the model is verified by cross-validation method. Additionally, MySQL is used to realize comprehensive data management. Findings: The proposed anti-corrosion system thoroughly considers a full use of corrosion data, relevant corrosion prediction and efficient corrosion management in one system. Therefore, this system can achieve an accurate prediction of corrosion rate, risk evaluation, risk alert and expert suggestion for equipment in petrochemical plants. Originality/value: Collectively, this present study has important ramifications for the more efficient and scientific management of corrosion data in enterprises and experts' guidance in controlling corrosion status. At the same time, the digital management of corrosion data can provide a data support for related theoretical researches in corrosion field, and the intelligent system also offers examples in other fields to improve system by adding intelligence means. [ABSTRACT FROM AUTHOR]
ISSN:00035599
DOI:10.1108/ACMM-10-2020-2384