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<p>This study presents a dual-path framework for mural heritage conservation that integrates lightweight crack detection with physics-based simulation. In the detection path, a YOLO-MME model based on a MobileNetV4 backbone, enhanced multi-head cross-attention, and an improved IoU-based loss achieves an effective balance between accuracy and computational efficiency for resource-limited deployment. In the simulation path, a bi-layer RFPA3D model is employed to analyze the effects of loading ratio (<i>λ</i> = Δ<i>y</i>/Δ<i>x</i>) and overlay thickness (<i>t</i>) on crack evolution across four stages: initiation, propagation, coalescence, and saturation. Validation on 20 paired mural samples demonstrates strong cross-sectional consistency with field observations, quantified using a multi-level correspondence marker system, yielding high skeleton overlap (IoU = 0.82) and reduced geometric deviation relative to uncalibrated baselines. Importantly, the evaluation framework supports both agreement assessment and failure-mode diagnosis. By coupling data-driven detection with physical modeling, the framework enables standardized documentation and mechanism-oriented conservation decision-making.</p>

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Dual-path detection and physical simulation for sustainable crack evolution monitoring in ancient Chinese murals

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月22日

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  • Yanfeng Hu,
  • Siqi Wu,
  • Yunlong Luo,
  • Zhuoran Ma,
  • Si Cheng

摘要

This study presents a dual-path framework for mural heritage conservation that integrates lightweight crack detection with physics-based simulation. In the detection path, a YOLO-MME model based on a MobileNetV4 backbone, enhanced multi-head cross-attention, and an improved IoU-based loss achieves an effective balance between accuracy and computational efficiency for resource-limited deployment. In the simulation path, a bi-layer RFPA3D model is employed to analyze the effects of loading ratio (λ = Δy/Δx) and overlay thickness (t) on crack evolution across four stages: initiation, propagation, coalescence, and saturation. Validation on 20 paired mural samples demonstrates strong cross-sectional consistency with field observations, quantified using a multi-level correspondence marker system, yielding high skeleton overlap (IoU = 0.82) and reduced geometric deviation relative to uncalibrated baselines. Importantly, the evaluation framework supports both agreement assessment and failure-mode diagnosis. By coupling data-driven detection with physical modeling, the framework enables standardized documentation and mechanism-oriented conservation decision-making.