An approach for the impact feature extraction method based on improved modal decomposition and singular value analysis

For non-stationary vibration useful information of the impact feature tends to be overwhelmed with strong routine components, which make it difficult to implement pattern recognition. This paper proposes improved signal processing methods of variational mode decomposition (VMD) and singular value decomposition (SVD) for non-stationary impact feature extraction in application to condition monitoring of reciprocating machinery. The impact feature is firstly simulated with the dynamics' analysis of the driving mechanism of a reciprocating pump. Through comparison the merit of the improved VMD method is demonstrated. The singular value of the decomposed modes is extracted with the SVD method. The support vector machine method is used as the classifier for the extracted set of features. The performance of the proposed VMD-based method is validated practically through a set of measured data from the reciprocating pump setup.