Electric power design drawing identification and review method and system

Through deep learning and computer vision technology, the automatic identification and review of power design drawings has been solved, and the problems of poor flexibility, high cost and long cycle in the existing technology have been solved, achieving efficient and accurate drawing review.

CN119832556APending Publication Date: 2025-04-15STATE GRID HEBEI ELECTRIC POWER CO LTD +2
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Patent Information

Application Number
CN202411819395.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-11
Publication Date
2025-04-15

AI Technical Summary

Technical Problem

The existing power drawing review methods require manual search of the drawing-related chapters in the electronic list, resulting in poor flexibility, high cost and long review cycle.

Method used

Deep learning and computer vision technology are adopted to automatically identify and review power design drawings through element recognition and text recognition, and build element library and rule library to achieve standardization of identification and review.

Benefits of technology

It realizes automated review, reduces manual intervention, improves work efficiency, improves the accuracy of element recognition and text recognition, reduces human errors and omissions, and improves the quality of design drawings.

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Abstract

The invention discloses an electric power design drawing identification and review method and system, and the method comprises the following steps: S1, obtaining an electric power design drawing, and constructing a primitive library and a rule library; s2, performing primitive recognition on the electric power design drawing based on an edge recognition method and a deep learning method to obtain a corresponding digital image; s3, in OCR recognition, a weak supervised learning method is used, deep learning and a computer vision processing method are combined, texts in the electric power design drawing are recognized, and text information is obtained; s4, comparing the digital image with a primitive library to obtain position and type information of each electrical primitive in the electric power design drawing; and S5, comparing the position, type information and text information of each electrical primitive with a rule base to obtain an identification result, post-processing the obtained identification result, and judging and modifying the result through priori knowledge.
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