Verification Technology for Virtual Terminal Connection Based on Deep Learning and Attention Image Recognition
In response to the heavy workload of substation configuration description(SCD)verification and current low efficiency and accuracy of manual verification,this paper proposes a virtual terminal connection intelligent verification technology based on deep learning and image recognition.Firstly,it uses Faster R-CNN model of Tensorflow framework to intelligently identify the protection and measurement and control intelligent electronic device(IED)in the SCD virtual connection graph.By comparing the two-stage recognition methods of Advanced EAST and Tesseract OCR with the end-to-end recognition methods of Attention-OCR,it selects the end-to-end Attention OCR method with higher accuracy ultimately to achieve text and number recognition in the SCD virtual connection graph.Then,it uses image processing technology to identify the connection relationship of the SCD virtual connection graph,and organizes the data to obtain the SCD side virtual connection table.Through the forward and reverse comparison of the virtual connection tables on the SCD side and Excel side,a verification report is finally formed to screen out non corresponding information,effectively solving the current problems of low efficiency and accuracy in manual comparison.
万方数据
维普
