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What Tisha demonstrated
Built a working rolling-bearing fault detector end to end: visualized a faulty vibration snapshot, extracted RMS/kurtosis/crest-factor and defect-band envelope energy, trained a compact depth-capped decision tree on training bearings only, and evaluated it on held-out bearings with catch-rate and false-alarm rate. The memo defended a 0.37 alarm threshold using the student's own cost numbers and correctly identified an outer-race fault from the BPFO peak.
- Leakage-Free Feature Engineering
- Honest Held-Out Evaluation
- Physics-Based Fault Localization
- Cost-Based Threshold Selection
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