A Compound KPCA Fault Diagnosis Model
Xiaoyang Yu · Journal of North University of China · 2009
The concrete form of kernel function in the KPCA fault diagnosis model has great impact on the diagnosis performance.A new compound kernel function model is presented based on RBF Gaussian kernels and polynomial kernels.The construction of the model and the implementation steps of the fault diagnosis algorithms are given.In the condition of considering the global information the model guarantees partial sensitivity and good fitting ability.Compared with other KPCA algorithms' simulation results,the proposed model not only avoids prior hypothesis but also has higher fault diagnosis efficiency.