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a performance evaluation of three inference engines as expert systems for failure mode identification in shafts论文.pdf

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Engineering Failure Analysis 53 (2015) 24–35 Contents lists available at ScienceDirect Engineering Failure Analysis journal homepage: www.elsevier .com/locate/engfailanal A performance evaluation of three inference engines as expert systems for failure mode identification in shafts Carlos Javier Moreno ⇑, Edgar Espejo Department of Mechanical and Mechatronics Engineering, National University of Colombia, Colombia a r t i c l e i n f o a b s t r a c t Article history: This paper aims to present performance evaluation of three different inference engines Received 20 May 2014 (rule based reasoning, fuzzy based reasoning and Bayesian based reasoning) for failure Received in revised form 8 March 2015 mode identification in shafts. This research was done with a focus on the validation cases Accepted 31 March 2015 and results after their use in failure cases from several industries where the three systems Available online 4 April 2015 were tested under the same conditions. Each system was implemented using the same user interface and knowledge base, with Keywords: different frameworks and techniques as follows: rule based inference reasoning (prolog, Failure analysis C#), Mamdani-fuzzy based reasoning (C, MATLAB ) and Bayesian based reasoning with a Expert system
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