Review of advances in CT detection technology for defects in aero-engine composite materials

YANG Fuqiang; WANG Le; HUANG Kuidong; LI Zhixiang; JIAO Zhi; GUO Longlong

doi:10.13224/j.cnki.jasp.20250363

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YANG Fuqiang, WANG Le, HUANG Kuidong, et al. Review of advances in CT detection technology for defects in aero-engine composite materials[J]. Journal of Aerospace Power, 2025, 41（X）：20250363 doi: 10.13224/j.cnki.jasp.20250363

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Review of advances in CT detection technology for defects in aero-engine composite materials

doi: 10.13224/j.cnki.jasp.20250363

YANG Fuqiang^{1, 3
,},
WANG Le^{1, 3},
HUANG Kuidong^{1, 2, 3,*
,
,},
LI Zhixiang^{1, 3},
JIAO Zhi^{1, 3},
GUO Longlong^{1, 3}

1.
Key Laboratory of Performance Manufacturing for Aero Engine，Ministry of Industry and Information Technology，School of Mechanical Engineering，Northwestern Polytechnical University，Xi’an 710072，China
2.
Ningbo Institute，Northwestern Polytechnical University，Ningbo Zhejiang 315000，China
3.
State Key Laboratory of Cemented Carbide，Northwestern Polytechnical University，Xi’an 710072，China

Received Date: 2025-08-02
Available Online: 2025-12-24

Abstract

Abstract

The research progress of computed tomography (CT) technology in defect detection for aero-engine composite components was systematically reviewed. It addressed the bottleneck problem of accurately detecting and evaluating the cross-scale and multi-form defects generated in composites during their application in aero-engines, focusing discussions from the perspectives of the process mechanisms of defect formation, the technical principles of CT detection, and intelligent recognition algorithms. It provided a detailed analysis of typical defects in key components made of resin-based, metal matrix, ceramic matrix, and carbon-carbon composites. By reviewing the application scenarios of CT technology and starting from the typical defect characteristics and structural morphology differences revealed by CT detection, the effectiveness and limitations of different technologies, such as micro-focus CT and synchrotron radiation CT, were compared in identifying various types of defects. The results indicated that intelligent recognition technology based on deep learning is an effective approach for achieving accurate characterization of cross-scale defects, while multi-modal fusion detection is an important development direction for solving the challenge of micro-defect detection in thick-walled components. This review systematically investigated the compatibility of different matrix composites in CT detection, providing a theoretical basis and technical support for the full-lifecycle intelligent detection and reliability assessment of composite components in aero-engines.

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References

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Review of advances in CT detection technology for defects in aero-engine composite materials

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