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Updated: May 14, 2026

Real-Time Imaging of Bonding in 3D-Printed Layers
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Detection of Small Debonding Defects in Metal-Rubber Bonded Structures Using an Enhanced EMAT and Multi-Feature

Yang Fang1, Xiaokai Wang1, Yinqiang Qu1

  • 1State Key Laboratory for Strength and Vibration of Mechanical Structures, Shaanxi Engineering Research Centre of NDT and Structure Integrity Evaluation, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
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This study introduces a new detection method for micro-debonding defects in metal-rubber structures using enhanced electromagnetic acoustic transducer (EMAT) technology. The framework combines magnetic-field focusing with multi-feature fusion for improved defect detection sensitivity.

Area of Science:

  • Materials Science
  • Non-Destructive Testing
  • Acoustic Engineering

Background:

  • Metal-rubber bonded structures are prone to micro-debonding defects, which are difficult to detect with conventional methods.
  • Electromagnetic acoustic testing (EMAT) offers a non-contact approach but suffers from low sensitivity to small defects.

Purpose of the Study:

  • To enhance the sensitivity of EMAT for detecting micro-debonding defects in metal-rubber bonded structures.
  • To develop a novel detection framework integrating hardware and image-level improvements.

Main Methods:

  • Designed and simulated a Halbach-type focusing magnet to enhance the bias magnetic field.
  • Extracted and fused three echo features (amplitude, time-domain integral, power spectral density) using an adaptive entropy-weighted strategy.
Keywords:
electromagnetic acoustic testing (EMAT)enhanced magnetic field EMATmetal-rubber bonded structuremulti-feature fusion imagingquantitative evaluation of debonding area

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  • Conducted comparative and ablation studies to validate the contributions of probe enhancement and feature fusion.

    • Main Results:

    • The focused probe significantly improved defect-response strength.
    • Entropy-weighted feature fusion enhanced image contrast, background suppression, and segmentation consistency.
    • The proposed framework reliably detected 5 mm defects in aluminum-alloy-rubber and 10 mm defects in titanium-alloy-rubber specimens.

    Conclusions:

    • The combination of magnetic-field focusing and adaptive multi-feature fusion is a promising approach for detecting micro-debonding defects.
    • This framework offers improved sensitivity and quantitative characterization capabilities for metal-rubber bonded structures.