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As a critical load-bearing component connecting the elevator car and the counterweight, the wire rope is essential for elevator safety. However, during long-term service, wire ropes are prone to diameter reduction and wire breakage. To address this, we propose a real-time monitoring framework for elevator wire ropes that integrates parallel projection modeling and shape-adaptive convolution. This framework first enables the automated measurement of wire rope diameter by establishing a parallel projection model. Additionally, we introduce a texture-aware dynamic convolution method that leverages Sobel edge detection and adaptively adjusts convolutional regions based on rope surface patterns to detect surface defects. Experimental results demonstrate high accuracy in both diameter measurement and defect localization, validating the framework’s effectiveness for continuous elevator wire rope monitoring.

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Elevator Wire Rope Condition Monitoring Framework Based on Parallel Projection and Shape-Adaptive Convolution

  • 会议论文

  • 发表日期：

    2026年

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  • Wenming Xu,
  • Xia Zhang,
  • Gang Xiao,
  • Zhenhui Lou,
  • Xiaoping Jiang,
  • Jiangtao Ye,
  • Fengjie Li,
  • Mu Yuan,
  • Wenchao Liu,
  • Zhenbo Cheng

摘要

As a critical load-bearing component connecting the elevator car and the counterweight, the wire rope is essential for elevator safety. However, during long-term service, wire ropes are prone to diameter reduction and wire breakage. To address this, we propose a real-time monitoring framework for elevator wire ropes that integrates parallel projection modeling and shape-adaptive convolution. This framework first enables the automated measurement of wire rope diameter by establishing a parallel projection model. Additionally, we introduce a texture-aware dynamic convolution method that leverages Sobel edge detection and adaptively adjusts convolutional regions based on rope surface patterns to detect surface defects. Experimental results demonstrate high accuracy in both diameter measurement and defect localization, validating the framework’s effectiveness for continuous elevator wire rope monitoring.