Research On Classification Method Of Fault Diagnosis For Gearbox Transmission System Of Wind Turbine

In order to find an effective method of fault classification of gear transmission system, fault test and vibration signal are done on the planetary gear transmission system. Empirical Mode Decomposition (Referred to as the EMD) method is used to processes the vibration signal, we obtain several Intrinsic Mode Function (Referred to as the IMF) components Auto Regressive (Referred to as the AR) model of the former four IMF components is established, we obtained the from regression parameter sequence, then calculate the correlation dimension, maximum Lyapunov exponent, sample entropy 3 chaotic characteristic parameters,and as fault identification features. Fusing information of different measuring points with AR model of multi IMF components and different chaotic characteristic parameters,and as Support Vector Machine (Referred to as the SVM) input vector,establishing 6 kinds of different state of the training set,then we can achieve the classification of fault type.The results indicate that make EMD and AR model treatment to the experimental vibration signals, can improve the fault classification accuracy largely.The method is to obtain the eigenvector of wavelet packet signal energy about the normal and 5 different fault states under 3 measuring points. The correlation coefficient of the energy characteristics were calculated for the same measuring point in different states and for different measuring points in the same state. By analyzing the characteristics of these two types of fusion information, the fault diagnosis model was established. In addition, the fault diagnosis model was inspected with 14 groups of signals to be detected, and the results were exactly consistent with the actual fault states. The support vector machine method was adopted to realize classification of 5 different fault states. The outcome was consistent with the actual fault states and it verifies the correctness of the established model of fault diagnosis. Analysis results show that the fault diagnosis model was established through the vibration relevant information fusion, and the model can reflect the characteristics of different fault states. By the model, the weak and the coupling fault were effectively diagnosed for complex gear transmission system.