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Study of fuzzy neural networks model for system condition monitoring of AUV

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Abstract

A structure equivalent model of fuzzy-neural networks for system condition monitoring is proposed, whose outputs are the condition or the degree of fault occurring in some parts of the system. This network is composed of six layers of neurons, which represent the membership functions, fuzzy rules and outputs respectively. The structure parameters and weights are obtained by processing off-line learning, and the fuzzy rules are derived from the experience. The results of the computer simulation for the autonomous underwater vehicle condition monitoring based on this fuzzy-neural networks show that the network is efficient and feasible in gaining the condition information or the degree of fault of the two main propellers.

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Authors and Affiliations

  1. College of Mechanical and Electrical Engineering, Harbin Engineering University, 150001, Harbin, China

    Wang Yu-jia & Zhang Ming-jun

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  1. Wang Yu-jia
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  2. Zhang Ming-jun
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Wang, Yj., Zhang, Mj. Study of fuzzy neural networks model for system condition monitoring of AUV. JMSA 1, 42–45 (2002). https://doi.org/10.1007/BF02935838

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  • DOI: https://doi.org/10.1007/BF02935838

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