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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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Related Experiment Video

Updated: Feb 14, 2026

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
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Digital Image Correlation-Based Bolt Preload Monitoring.

Linsheng Huo1, Liukun Zhao1, Aocheng Hu1

  • 1State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.

Sensors (Basel, Switzerland)
|February 13, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new non-contact method using Digital Image Correlation (DIC) for bolt preload monitoring. This approach precisely tracks surface strain to detect bolt loosening, enhancing structural safety.

Keywords:
bolt looseness monitoringbolt preloaddigital image correlationstructural health monitoring

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Area of Science:

  • Engineering
  • Structural Health Monitoring
  • Materials Science

Background:

  • Bolt connections are critical in engineering structures but prone to loosening, posing safety risks.
  • Existing bolt-loosening detection methods are often inefficient, inaccurate, or require contact sensors.

Purpose of the Study:

  • To develop a novel non-contact method for monitoring bolt preload.
  • To overcome the limitations of conventional bolt-loosening detection techniques.

Main Methods:

  • Utilizing Digital Image Correlation (DIC) with an industrial camera to capture speckle images of bolt heads.
  • Measuring surface strain on the bolt head before and after deformation.
  • Calculating the strain field and tracking its changes to correlate with bolt preload.

Main Results:

  • A linear relationship was established between the bolt head surface strain field and bolt preload.
  • The DIC-based method demonstrated precise and efficient bolt preload monitoring.
  • Experimental validation confirmed the accuracy and user-friendliness of the proposed technique.

Conclusions:

  • The novel non-contact DIC method offers a precise, efficient, and user-friendly solution for bolt preload monitoring.
  • This technique shows significant potential for applications in structural health monitoring and ensuring structural integrity.