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<p>Bridge infrastructures face challenges from aging, overloading, and environmental hazards, making structural health monitoring (SHM) crucial for functionality, safety, and longevity. Conventional SHM techniques are limited by intrusive sensors and restricted coverage. With advancements in vision-based techniques, digital image correlation (DIC) has emerged as a non-contact method capable of full-field displacement, strain, and crack monitoring. This review reveals a growing research interest in the application of DIC for bridge SHM, particularly accelerating after 2020. The key DIC applications involve crack detection, modal identification, displacement tracking, and fatigue assessment. However, challenges persist, including calibration sensitivity, environmental influence, and limited real-time and full-structure abilities. To overcome these, a roadmap is proposed integrating DIC with Internet of Things (IoT), drone-based imaging, energy-efficient algorithms, advanced vision models, and digital twins for intelligent SHM. This integration supports safer, smarter, and more resilient bridge infrastructure systems.</p>

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Digital Image Correlation (DIC) for Structural Health Monitoring of Bridge Systems: A State-of-the-Art Review with Future Research Directions

  • 期刊论文

  • 发表日期：

    2025年11月19日

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  • Ibrahim A. Tijani,
  • Tadesse G. Wakjira,
  • M. Shahria Alam,
  • Nasim Uddin

摘要

Bridge infrastructures face challenges from aging, overloading, and environmental hazards, making structural health monitoring (SHM) crucial for functionality, safety, and longevity. Conventional SHM techniques are limited by intrusive sensors and restricted coverage. With advancements in vision-based techniques, digital image correlation (DIC) has emerged as a non-contact method capable of full-field displacement, strain, and crack monitoring. This review reveals a growing research interest in the application of DIC for bridge SHM, particularly accelerating after 2020. The key DIC applications involve crack detection, modal identification, displacement tracking, and fatigue assessment. However, challenges persist, including calibration sensitivity, environmental influence, and limited real-time and full-structure abilities. To overcome these, a roadmap is proposed integrating DIC with Internet of Things (IoT), drone-based imaging, energy-efficient algorithms, advanced vision models, and digital twins for intelligent SHM. This integration supports safer, smarter, and more resilient bridge infrastructure systems.