A neural network model for fault detection in conjunction with a programmable logic controller |
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Authors: | Barbara A Osyk Ming S Hung Gregory R Madey |
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Affiliation: | (1) The University of Akron, 44325-4801 Akron, OH, USA;(2) Kent State University, 44240 Kent, OH, USA |
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Abstract: | This paper discusses the feasibility of using neural networks as a tool in the fault detection process. A neural network is integrated with a state language programmable logic controller, an important device in an automatic control system. Time series data related to time spent in a state is gathered and used as input into a neural network, for the purpose of identifying when a fault has occurred. A feedforward neural network is used to identify which (if any) of three types of faults may have occurred. Experimental results related to sensitivity and accuracy measures are presented. A brief review of related applications and research is also presented. |
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Keywords: | Neural networks fault detection programmable logic controller time series |
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