Abstract
In this paper, an intelligent fault diagnosis algorithm for the Strapdown Inertial Navigation System (SINS)/Ultra Short Baseline (USBL)/ Doppler Velocity Log (DVL)/Depth Gauge (DG) integrated navigation system is designed. For analyzing the change trend of the corresponding statistics after the fault occurs, this method uses the normalized residual sequences to judge the state of the navigation subsystems. The long short-term memory (LSTM) network is applied to monitor the sequences for its excellent performance in handling time series data. The simulation results indicate that the intelligent algorithm based on LSTM network outperforms the traditional chi-square detection method in respect of speed and accuracy. And it can accurately classify oscillation faults, step faults and gradual faults.
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