Fault Diagnosis Method and Application of Power Converter Based on Variational Mode Decomposition combined with Kernel Density Estimation

The fault diagnosis of power converter plays a decisive role in the intelligent and stable operation of DC microgrid. Aiming at the nonlinearity of fault output of converter power transistor and the difficulty of feature extraction, a combination of variational mode decomposition and kernel density estimation was proposed. Firstly, the power converter output signal was collected. Secondly, the signal was subjected to variational mode decomposition to decompose the complex signal into a series of sub-signals, and each modal component was extracted as a feature vector. Finally, the fault diagnosis was realized by means of the kernel density estimation classifier. The experimental results showed that the method reduced the diagnostic cost and improved the diagnostic accuracy, and the method was feasible and effective.