Spatial domain image generation and fusion method of single-phase grounding fault line selection for small current grounding system

In order to take full use of feature self-learning advantage of deep learning algorithm and its advantages in the field of image processing, and to avoid the information loss problem of manual fault feature extraction in single-phase grounding fault line selection for small current grounding system, a method is proposed by generating a full-information space domain image of fault current and then using image recog-nition and classification algorithm to select the fault line. Firstly, three-phase current is used to construct a three-dimensional spatial domain image, which is respectively project on three planes to obtain multiple projection images, so the key problem of acquiring two-dimensional images is solved. Then, the secondary pixel-level images fusion of the projected images is carried out, by which the corresponding RGB color image is obtained. Finally, the deep learning algorithm is used to identify and classify the image to achieve fault line selection. The comparison of fault line selection results between the proposed method and the existing methods show that under the influence of various factors, the proposed method has no loss of fault information, more obvious image fault characteristics, higher classification accuracy and anti-noise ability, which proves its feasibility in single-phase grounding fault line selection for small current grounding system. © 2021 Electric Power Automation Equipment Editorial Department. All right reserved.