A hierarchical diagnosis method of cable aged segment based on transfer function

Abstract

Abstract Traditional offline cable diagnosis methods need power outages during detection, affecting power supply reliability. Here, a hierarchical diagnosis method of cable aged segment based on transfer function is proposed. Firstly, the calculation model of cable transfer function with the aged segment is established; on this basis, the correlation between transfer function and cable aging is analysed. Then, a structure with combined sparse autoencoder and convolutional neural network is trained to estimate the aging location, and a hierarchical diagnosis model of distribution cable based on transfer function is proposed. The sensitivity and accuracy of aged segment detection are improved after hierarchical diagnosis. Finally, the simulation results show that the method proposed in this paper can effectively realize the online identification and location of the cable aged segment. The proposed method makes use of the advantage that the cable transfer function can be obtained online. Compared with the existing methods, this method does not need power outages in the diagnosis process, and the aged segment can be located without a lot of additional equipment.