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Consider the elastic torsion formula, which applies to a circular shaft with a consistent cross-section. This formula assumes that the shaft's ends are loaded with rigid plates firmly attached. However, in many cases, torques are applied to the shaft through mechanisms like flange couplings or gears, which are connected by keys inserted into keyways. This application method modifies the stress distribution near the point of torque application, causing it to deviate from the distributions...
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Related Experiment Video

Updated: Jan 10, 2026

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
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Anti-loosening bolt looseness diagnosis method for flange node based on quick response code.

Jun Luo1, Kaili Li1, BaoYa Shi1

  • 1School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China.

Scientific Reports
|November 20, 2025
PubMed
Summary

A new method uses quick response (QR) codes to accurately detect bolt loosening in flange connections. This technique corrects image distortions and tracks rotation for enhanced structural safety monitoring.

Keywords:
Anti-loosening boltsFlange nodeLooseness detectionQuick response codeVision-based technique

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Area of Science:

  • Mechanical Engineering
  • Structural Health Monitoring
  • Computer Vision

Background:

  • Flange connections are vital in engineering but prone to bolt loosening, compromising safety.
  • Vision-based methods for bolt looseness detection face challenges with perspective distortion and historical data.
  • Existing methods struggle to provide reliable quantitative loosening angles and track changes over time.

Purpose of the Study:

  • To develop a novel method for diagnosing anti-loosening bolt looseness using quick response (QR) codes.
  • To address limitations of current vision-based techniques, specifically perspective distortion and lack of historical data.
  • To establish a robust system for accurate bolt loosening angle detection and structural safety assessment.

Main Methods:

  • Designing a QR code with three finder patterns and affixing it to the bolt end face.
  • Employing homography-based perspective rectification using QR code edge intersections for image correction.
  • Utilizing QR code finder patterns to rotate images to a unified reference state, mitigating camera and bolt/nut rotation effects.
  • Establishing a looseness diagnosis method based on changes in nut rotation angles.

Main Results:

  • The proposed method effectively corrects perspective distortion in bolt images.
  • It significantly reduces the impact of camera position deviation and simultaneous rotation of screws and nuts.
  • The system accurately detects the loosening angle of anti-loosening bolts, validated through experimental verification.

Conclusions:

  • The novel QR code-based approach offers an effective solution for bolt looseness detection in flange connections.
  • This method enhances the reliability and accuracy of vision-based monitoring systems by overcoming key limitations.
  • The developed technique contributes to improved structural safety and maintenance through precise bolt loosening diagnosis.