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Related Experiment Video

Updated: Feb 28, 2026

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
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Research on an Automatic Solution Method for Plane Frames Based on Computer Vision.

Dejiang Wang1, Shuzhe Fan1

  • 1School of Mechanics and Engineering Science, Shanghai University, 99 Shangda Road, Shanghai 200444, China.

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|February 27, 2026
PubMed
Summary

This study introduces a deep learning method for automatic internal force analysis of plane frames from images. The approach achieves over 90% accuracy, offering a faster, more efficient alternative to traditional structural mechanics calculations.

Keywords:
YOLOobject detectionplane framestructural internal force analysisstructural mechanics

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Area of Science:

  • Structural Engineering
  • Computer Vision
  • Artificial Intelligence

Background:

  • Traditional internal force analysis of plane frames is time-consuming and error-prone.
  • General-purpose Finite Element Analysis (FEA) software has limitations in pre-processing and learning curve.
  • There is a need for rapid and intelligent solutions in structural analysis.

Purpose of the Study:

  • To develop a deep learning-based automatic solution for plane frame internal force analysis.
  • To extract structural information from printed schematics using computer vision.
  • To enable rapid and accurate internal force calculation and visualization.

Main Methods:

  • Image acquisition of plane frame schematics using smartphones.
  • Image pre-processing including rectification and enhancement.
  • Object detection and recognition using the YOLOv8 algorithm to extract structural data (nodes, loads, constraints).
  • Static analysis using the Matrix Displacement Method for internal force calculation.
  • Generation of internal force diagrams.

Main Results:

  • Achieved 99.1% detection accuracy for structural primitives.
  • Exceeded 90% overall solution accuracy for mechanical problems in the test set.
  • Demonstrated a convenient and efficient computational method for plane frame analysis.

Conclusions:

  • The proposed deep learning method significantly improves the efficiency and convenience of plane frame internal force analysis.
  • This approach automates the extraction of structural information and subsequent analysis.
  • The method shows high accuracy and potential for practical application in structural engineering.