Degree of Polymerization Evaluation of power transformer with Near infrared spectroscopy using Back Propagation Neural Networks

The degree of polymerization (DP) of insulating paper is a key factor to measure the performance of power transformer. Near infrared spectroscopy (NIRS) can test the degree of polymerization of insulating paper quickly and nondestructively, however, the poor generalization ability of prediction algorithm limits its application. In this paper, we carry out accelerated aging test on four kinds of insulating paper, which are typical insulating paper of transformer in Hainan power grid. The insulating paper with different degrees of aging were detected by the NIRS and the DP with viscosity method. The data of NIRS and DP were used to establish the quantitative mathematical relationship applied with Back Propagation Neural Networks (BPNN) model. The results show that the BPNN model has a high accuracy, which is more suitable in Hainan power grid.