A Novel Parameter-Adaptive VMD Method Based on Grey Wolf Optimization with Minimum Average Mutual Information for Incipient Fault Detection

Recently, variational mode decomposition (VMD) has attracted wide attention on mechanical vibration signal analysis. However, there are still some dilemmas in the application of VMD, such as determination number K and quadratic penalty term α. In order to acquire appropriate parameters an improved parameter-adaptive VMD method based grey wolf optimizer (GWO) is developed by taking minimum average mutual information into consideration (GWOMI). Firstly, (K, α) adaptively determined through GWOMI. Then, decomposed effective modes extracted according maximum kurtosis. Finally, processed Hilbert envelope analysis incipient fault features. With simulation experimental analysis, it clearly found that performs better than existing ones.