The high temperature of series arc fault is one of the main causes of electrical fire. Aiming at the problem that there is no effective protection method for the series arc fault in the load circuit of industrial frequency converter, a new method of fault detection and line selection for the series arc fault was proposed. First, the series arc fault experiments in different lines were carried out for the load circuit of three-phase frequency converter commonly used in industrial field. Second, the improved variational mode decomposition based on the principle of energy convergence was used to adaptively decompose the A-phase current signal at the front end of the frequency converter into multiple modal components. After multiplying the single modal component by the energy coefficient, the feature enhancement signals of multiple current signals were reconstructed, and the feature matrix was established. Third, the feature matrix was divided into blocks, and the kernel principal component analysis was used to reduce the dimension of each block matrix, and the matrix composed of the reduced dimension signal was reduced twice to construct the fault feature vector. Finally, the support vector machine optimized by the pelican optimization algorithm was used to detect the series arc fault and select the fault line. The results show that the proposed method can realize the fault detection and line selection of the series arc fault in six lines of the whole circuit of the frequency converter only by analyzing the A-phase current signal at the front end of the frequency converter, and the accuracy of fault detection and line selection is more than 98%.