A sensor-dependent vibration data driven fault identification method via autonomous variational mode decomposition for transmission system of shipborne antenna

With the increasing distance and time of voyage, condition monitoring and fault diagnosis of shipborne antenna play a crucial role in ship communication for navigation safety. However, it is still a challenging task to identify the hidden shipborne antenna fault from practical sensor-dependent vibration signals since the vibration features are always multi-modulated and submersed by heavy noise. Therefore, autonomous variational mode decomposition (AVMD) based on Independence-oriented Variational Mode Decomposition (IOVMD) and the Largest Lyapunov Exponent (LLE) criterion is proposed in this paper. First, the signal is decomposed into Intrinsic Mode Functions (IMFs) by IOVMD. Second, LLE of modes is calculated to measure fault information degree and then modes without fault features are eliminated. The combination rule is also defined and modes are combined orderly to enhance the fault feature expression. Then, an index structured by Kurtosis and LLE of combined signals is calculated and the combined signal is selected for demodulation. Finally, the combined signal is analyzed for fault identification by Hilbert Demodulation. A simulation and two cases show the effectiveness and superiority of the proposed method.