A Method for Evaluating the Severity of Intermittent Faults of Electronic Systems Based on Variational Mode Decomposition-Gated Recurrent Units

Considering the problem that the intermittent fault signal of the electronic system is greatly affected by noise and has a lot of redundant information, which results in the limitation of the deep neural network model to evaluate the severity of the intermittent fault. A method for evaluating the severity of intermittent faults based on Variational Mode Decomposition-Gated Recurrent Units (VMD-GRU) is proposed. Firstly, all Intrinsic Mode Function (IMF) components are adaptively decomposed on intermittent fault signals through Variational Mode Decomposition (VMD). Then the sensitivity analysis of the IMF components is performed to select the sensitive components, and the differential enhanced energy operator is used to construct the severity sensitivity factor. Finally, the severity sensitivity factor is used to train the Gated Recurrent Units (GRU) recurrent neural network severity evaluation model. Through the evaluation of intermittent faults of different severity injected into the key circuits of electronic systems, the results show that this method has a strong ability to evaluate the severity of intermittent faults, and is more accurate and effective in evaluating the severity of intermittent faults.