A fault detection algorithm for pipeline insulation layer based on immune neural network
- 12 January 2022
- journal article
- research article
- Published by Elsevier BV in International Journal of Pressure Vessels and Piping
- Vol. 196, 104611
- https://doi.org/10.1016/j.ijpvp.2022.104611
Abstract
No abstract availableKeywords
This publication has 30 references indexed in Scilit:
- Novel near-infrared spectrum analysis tool: Synergy adaptive moving window model based on immune clone algorithmAnalytica Chimica Acta, 2018
- Innate and adaptive lymphocytes sequentially shape the gut microbiota and lipid metabolismNature, 2018
- S1P-dependent interorgan trafficking of group 2 innate lymphoid cells supports host defenseScience, 2018
- The structural basis of flagellin detection by NAIP5: A strategy to limit pathogen immune evasionScience, 2017
- Single-cell transcriptomics to explore the immune system in health and diseaseScience, 2017
- Demonstration of increased corrosion activity for insulated pipe systems using a simplified electrochemical potential noise methodJournal of Loss Prevention in the Process Industries, 2017
- T helper 1 immunity requires complement-driven NLRP3 inflammasome activity in CD4 + T cellsScience, 2016
- Design of early fault detection technique for electrical assets using infrared thermogramsInternational Journal of Electrical Power & Energy Systems, 2014
- Antiviral immunity via RIG-I-mediated recognition of RNA bearing 5′-diphosphatesNature, 2014
- The use of artificial neural network to evaluate insulation thickness and life cycle costs: Pipe insulation applicationApplied Thermal Engineering, 2014