An Algorithm of Intelligent Classification For Rotating Mechanical Failure Based on Optimized Support Vector Machine

The classification algorithm of rotating machinery fault cannot effectively recognize the false components and true components in fault signal of rotating machinery. Therefore, an intelligent classification algorithm of rotating machinery fault based on optimized support vector machine was put forward. The K-L divergence was used to measure the nonlinear and symmetry of probability distribution of two processes in rotating machinery, and the error of information in the process of rotating machinery was measured to eliminate the false component of fault signal of rotating machinery. Meanwhile, the multi-value classification support vector machine algorithm based on decision directed acyclic graph was used to process the signal that only had a true component. Moreover, the value of each node in support vector machine decision function was calculated. Finally, based on calculation results, the fault categories were excluded. Thus, the intelligent classification of rotating machinery fault was completed. According to experimental results, the proposed algorithm can accurately eliminate false components in the rotating machinery fault signal. Meanwhile, the classification result is accurate.