Analysis of Vibration Characteristics of Hydroturbine Based on Relevance Vector Machine

Relevance vector machine (RVM) is a novel kernel method based on sparse Bayesian, which has many advantages such as its kernel functions without the restriction of Mercer’s conditions, and the relevance vectors are automatically determined. With the operation data of the hydropower station, considering the pressure fluctuation, the fitting model of vibration characteristics is established based on RVM, the applications of RVM and Support Vector machine (SVM) in vibration characteristics of turbine are compared.