科技创新与应用2025，Vol.15Issue(2)：20-25,6.DOI:10.19981/j.CN23-1581/G3.2025.02.004
面向铁塔图纸的关键信息智能提取算法设计
摘要
Abstract
Automatic identification and information extraction of tower design drawings in power engineering design is an urgent problem to be solved urgently.This paper proposes an intelligent recognition system for tower design drawings based on deep learning and optical character recognition(OCR)technology.The system consists of three main modules:segmented structure recognition,text recognition and key information extraction.The segmented structure recognition module adopts an improved U-Net convolutional neural network model;the text recognition module is optimized based on Tesseract 4.0,which improves the accuracy of character recognition.The key information extraction module uses a rule-based parsing engine to extract key information from the identified segmentation structures and texts.Experimental results show that the system achieves a higher level tower structure recognition F1 value of 96.35%and a character recognition accuracy of 99.10%in terms of accuracy,generalization and efficiency in tower drawing recognition.The system can effectively support the digital and intelligent transformation of power engineering design and management,and has broad application prospects.关键词
铁塔图纸/深度学习/光学字符识别/关键信息提取/U-Net/TesseractKey words
tower drawing/deep learning/optical character recognition(OCR)/key information extraction/U-Net/Tesseract分类
信息技术与安全科学引用本文复制引用
郑林,汤杰波,应成才,凌彦,徐瑞吉,毛科技..面向铁塔图纸的关键信息智能提取算法设计[J].科技创新与应用,2025,15(2):20-25,6.基金项目
国家自然科学基金(62072410) （62072410）
浙江省基础公益研究计划项目(LGG22F020014) （LGG22F020014）
