Idea Research Based on Kernel Method in Fault Diagnosis

It is important to reduce keeping costs and hold up unscheduled downtimes for machinery. So knowledge of what, where and how faults occur is very important. In machine rotation and machine learning Fault diagnosis and detection are important rule. In this paper offer a method based on kernel method that using in fault occur. For this reason create kernel by wavelet packet with associate rule mining and information fusion for decision rule. This kernel has best time detection and optimization misclassification. Our proposed data fusion strategies take into account that a support vector machine with multi-kernel Wavelet-Entropy by finding the optimal hyper plane with maximal margin.