Turbine Faults Diagnosis Based on Gaussian Mixture Models

The Gaussian Mixture Models and the wavelet packet analysis are used to the turbine vibration faults diagnosis.De-compound firstly the vibration faults signal and delete the disturbed component.Then,take the frequency segments which contain the fault characteristics as the fault characteristics vector.To set up the Gaussian Mixture Models with the vectors,and identify the different faults with the built model.The experiment data measured in Benlty experiment platform is adopted to set up the model and identify the faults.In the calculation results,when the modulus equal to twelve,the precision for the faults diagnosis by the Gaussian Mixture Models is approximately 80%～90%.It indicates that the turbine vibration fault can be diagnosed effectively by the Gaussian Mixture Models and the wavelet packet analysis.