[PDF] Real-time fault diagnosis using knowledge-based expert system | Semantic Scholar Skip to search formSkip to main content> Semantic Scholar's Logo Search Sign InCreate Free Account You are currently offline. Some features of the site may not work correctly. DOI:10.1016/J.PSEP.2007.10.014 Corpus ID: 17900554Real-time fault diagnosis using knowledge-based expert system @article{Nan2008RealtimeFD, title={Real-time fault diagnosis using knowledge-based expert system}, author={C. Nan and F. Khan and M. T. Iqbal}, journal={Process Safety and Environmental Protection}, year={2008}, volume={86}, pages={55-71} } C. Nan, F. Khan, M. T. Iqbal Published 2008 Engineering Process Safety and Environmental Protection Abstract Abnormal operating conditions (faults) cost process industry billons of dollars per year and can be prevented if they are predicted and controlled in advance. Advanced software applications, based on the expert system, has the potential to assist engineers in monitoring, detecting, and diagnosing abnormal conditions and thus providing safe guards against these unexpected process conditions. Abnormal operating conditions (faults) could be modeled and predicted with high confidence using… Expand View via Publisher lue.ethz.ch Save to Library Create Alert Cite Launch Research Feed Share This Paper 79 CitationsHighly Influential Citations 1 Background Citations 23 Methods Citations 20 View All Figures and Tables from this paper figure 1 table 1 figure 2 table 2 figure 3 table 3 figure 4 figure 5 figure 6 table 7 figure 8 table 8 figure 9 table 9 figure 10 figure 11 figure 12 figure 13 figure 14 figure 15 figure 16 figure 17 figure 18 figure 19 figure 21 figure 23 figure 24 figure 25 figure 26 figure 27 View All 30 Figures & Tables 79 Citations Citation Type Citation Type All Types Cites Results Cites Methods Cites Background Has PDF Publication Type Author More Filters More Filters Filters Sort by Relevance Sort by Most Influenced Papers Sort by Citation Count Sort by Recency Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets Hu-Chen Liu, Qing-Lian Lin, Ming-Lun Ren Engineering, Computer Science Comput. 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