| Study of Fuzzy Neural Networks Model for System Condition Monitoring of AUV |
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| 作者姓名： | WANG Yu-jia ZHANG Ming-junCollege of Mechanical and Electrical Engineering Harbin Engineering University Harbin China |
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| 作者单位： | WANG Yu-jia，ZHANG Ming-junCollege of Mechanical and Electrical Engineering，Harbin Engineering University，Harbin 150001，China |
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| 摘 要： | 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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Study of fuzzy neural networks model for system condition monitoring of AUV |
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| WANG Yu-jia,ZHANG Ming-junCollege of Mechanical and Electrical Engineering,Harbin Engineering University,Harbin ,China.Study of Fuzzy Neural Networks Model for System Condition Monitoring of AUV[J].Journal of Marine Science and Application,2002,1(2):42-45. |
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| Authors: | Yu-jia Wang Ming-jun Zhang |
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| Institution: | (1) College of Mechanical and Electrical Engineering, Harbin Engineering University, 150001 Harbin, China |
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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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| Keywords: | fuzzy neural network condition monitoring autonomous underwater vehicle |
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