A CNN-Transformer model classifies simulated probe-card vibration into healthy, cracked, or loose-screw states with 99.8% accuracy, and attention weights rank sensor locations for placement optimization.
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Transformer-Based Approach to Optimal Sensor Placement for Structural Health Monitoring of Probe Cards
A CNN-Transformer model classifies simulated probe-card vibration into healthy, cracked, or loose-screw states with 99.8% accuracy, and attention weights rank sensor locations for placement optimization.