Investigation of a Blade Inspection Method by Using Double Planar Coils

The blade, as a core component in modern industrial systems, exerts significant influence on the performance of both aeroengines and steam turbines through its inspection accuracy and efficiency. Blade inspection serves dual purposes: evaluating machining precision for error compensation, and enabling failure diagnosis for expedited maintenance. This study proposes an electroforming-based planar coil sensor (Φ3.5 mm × 1.5 mm) for key-point sampling, optimizing measurement efficiency. The sensor's fabrication methodology is systematically detailed, and its efficacy is validated through numerical simulations and experimental trials. Results demonstrate >95% detection accuracy for defects of varying depths and geometries, with consistent response characteristics. Case studies confirm the sensor's capability to reliably identify internal/external defects using minimal measurement points while sustaining real-time performance.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-10-13
DOI
https://doi.org/10.1109/jsen.2025.3618327
Primary Topic
Metallurgy and Material Forming
Type
article
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article

Investigation of a Blade Inspection Method by Using Double Planar Coils

Zhouzhi Gu, X. Zheng
IEEE Sensors Journal
Metallurgy and Material Forming
article

Investigation of a Blade Inspection Method by Using Double Planar Coils

Zhouzhi Gu, X. Zheng
article en

Abstract

The blade, as a core component in modern industrial systems, exerts significant influence on the performance of both aeroengines and steam turbines through its inspection accuracy and efficiency. Blade inspection serves dual purposes: evaluating machining precision for error compensation, and enabling failure diagnosis for expedited maintenance. This study proposes an electroforming-based planar coil sensor (Φ3.5 mm × 1.5 mm) for key-point sampling, optimizing measurement efficiency. The sensor's fabrication methodology is systematically detailed, and its efficacy is validated through numerical simulations and experimental trials. Results demonstrate >95% detection accuracy for defects of varying depths and geometries, with consistent response characteristics. Case studies confirm the sensor's capability to reliably identify internal/external defects using minimal measurement points while sustaining real-time performance.

IEEE Sensors JournalVol. 25(22)
Huaiyin Institute of Technology (CN)
Openalex Percentile: Top 67%
Metallurgy and Material Forming
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