An Circuit Fault Diagnosis Method with K-Means Kernel Density Estimation

摘要

A K-Means kernel density estimation was proposed and it was used in the pretreatment process of circuit fault diagnosis. The unequal division and losing division problem caused by the traditional method are solved by this method. It also avoid the singular problem which is usually caused by the high dimension of characteristic data. A kernel function is designed and it was integrated with fuzzy support vector machine method to solve the classification problem of multi-faults. At last, a solution of optimal bandwidth is given to improve the proposed method.