Research on fault diagnosis technology of centrifugal pump blade crack based on PCA and GMM

Abstract Centrifugal pumps are widely used in modern industry, and blades are the key parts of it. The cracks on blades may result in a very serious consequence. In this paper, a fault diagnosis method based on principal component analysis (PCA) and Gaussian mixed model (GMM) was proposed, which combined signal processing and knowledge. Also, the theory model of proposed methods was established, and Expectation Maximization (EM) algorithm was used to make the model converge. PCA was used to reduce the data dimensionalities and increase the feature resolution, and GMM was used as classifier for crack fault. In order to verify the diagnostic effect of the model, the experimental bench of centrifugal pump was established, and various working conditions of the centrifugal pump were simulated. Experimental results showed that the classifier based on these parameters performed very well in data testing.