Abstract
Background
Ferromagnetic materials are widely used in industry, requiring precise quality assessment. Magnetic adaptive testing (MAT) provides higher sensitivity and simpler operation than traditional NDT methods but is limited by insufficient feature utilization.
Objective
To enhance the assessment of plastic deformation in SS400 steel by fully exploiting MAT signal information.
Methods
A multi-feature extraction and fusion evaluation (MFE-FE) method was developed to extract diverse features from raw and integrated MAT signals—including original, rectified, histogram, and envelope forms—and combine them through a fusion algorithm.
Results
Predictive models based on the fused features were experimentally validated, showing markedly improved detection accuracy and sensitivity compared with conventional approaches.
Conclusions
The proposed MFE-FE method maximizes MAT signal utilization, enabling more accurate evaluation of plastic deformation and offering strong potential for industrial applications.
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