Bolt Loosening and Preload Loss Detection Technology Based on Machine Vision

Steel bridges often experience bolt loosening and even fatigue fracture due to fatigue load, forced vibration, and other factors during operation, affecting structural safety. This study proposes a high-precision bolt key point positioning and recognition method based on deep learning to address the high cost, low efficiency, and poor safety of current bolt loosening identification methods. Additionally, a bolt loosening angle recognition method is proposed based on digital image processing technology. Using image recognition data, the angle-preload curve is revised. The established correlation between loosening angle and pretension for commonly utilized high-strength bolts provides a benchmark for identifying loosening angles. This finding lays a theoretical foundation for defining effective detection intervals in future bolt loosening recognition systems. Consequently, it enhances the system’s ability to deliver timely warnings, facilitating swift manual inspections and repairs.

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