Gearbox fault diagnosis based on VMD-MSE and adaboost classifier

Accurate and efficient fault diagnosis is of great importance for gearbox. This study proposed a fault diagnosis based on variational mode decomposition (VMD) - multiscale entropy (MSE) and adaboost algorithm. First, the VMD is employed to decompose the raw signal in time-frequency domain. Then, MSE is computed to generate the feature vectors. Finally, the classifier based on adaboost is training and several weak classifiers form a strong classifier to realize the fault diagnosis. The feasibility and accuracy of the method is validated by the data from the Prognostics and Health Management Society for the 2009 data challenge competition.