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• W2184778939 abstract "In this study, we propose the least disturbance algorithm adding scale factor and shift factor. The dynamic learning ratio can be calculated to minimize the scale factor and shift factor of wavelet function and the variation of net weights and the algorithm improve the stability and the convergence of wavelet neural network. It was applied to build the dynamical model of autonomous underwater vehicles and the residuals are generated by comparing the outputs of the dynamical model with the real state values in the condition of thruster fault. Fault detection rules are distilled by residual analysis to execute thruster fault diagnosis. The results of simulation prove the effectiveness." @default.
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• W2184778939 date "2013-04-30" @default.
• W2184778939 modified "2023-09-22" @default.
• W2184778939 title "Fault Diagnosis of Autonomous Underwater Vehicles" @default.
• W2184778939 cites W1969086509 @default.
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• W2184778939 doi "https://doi.org/10.19026/rjaset.5.4627" @default.
• W2184778939 hasPublicationYear "2013" @default.
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