Review of Health Monitoring and Intelligent Fault Diagnosis for High-Strength Bolts: Failure Mechanisms, Multi-Modal Sensing, and Data-Driven Approaches

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Abstract
High-strength bolted connections are fundamental load-bearing components in critical engineering infrastructures such as wind turbines, bridges, and heavy machinery. Under complex service environments involving dynamic loading, vibration, corrosion, and temperature variations, bolts are prone to interacting failure mechanisms, including fatigue fracture, corrosion-assisted cracking, hydrogen embrittlement, and progressive preload loss, which pose significant challenges for reliable condition monitoring and early fault diagnosis. This review provides a structured synthesis of recent advances in bolt health monitoring and intelligent fault diagnosis. A unified framework is established to link multi-physics failure mechanisms with multi-modal sensing technologies and data-driven diagnostic methods. Key sensing approaches—such as piezoelectric impedance techniques, ultrasonic phased array inspection, and computer vision-based monitoring—are critically reviewed in terms of their physical principles, diagnostic capabilities, and limitations. Furthermore, the transition from traditional model-based and signal-processing-driven methods to machine learning- and deep learning-based approaches is examined, with emphasis on multi-modal data fusion, real-time monitoring, and lifecycle-oriented health management enabled by IoT and digital twin technologies. Finally, key challenges and future research directions toward robust and scalable intelligent bolt health management systems are outlined. This review’s primary contribution lies in establishing a novel, integrated framework that links failure physics to sensing and diagnosis, thereby providing a structured roadmap for transitioning from isolated component monitoring to lifecycle-oriented, intelligent health management systems for critical bolted connections.
Funding Information
  • Young Backbone Teachers in Zhongyuan University of Technology (2025XQG03)
  • Plan for Enhancing the Strength of Advantageous Disciplines in Zhongyuan University of Technology: “Civil Engineering” (SD202423)
  • National Natural Science Foundation of China (52508178)
  • Basic and Applied Basic Research Foundation of Guangdong Province (2025A1515010155)
  • Natural Science Foundation of Henan Province (252300423474)
  • Open Project Funding for Henan Key Laboratory of Grain and oil storage facility & safety (2025KF02)
  • Guangzhou Construction Group Co., Ltd. Technology Plan Project (2024-KJ081)
  • Science and Technology in Henan Province (242102241025)

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