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What Kian demonstrated
Built an end-to-end rolling-bearing fault detector from vibration data: engineered RMS, kurtosis, crest factor, and defect-frequency envelope energy; trained a compact decision tree on training bearings only; and evaluated it on held-out bearings with catch-rate and false-alarm metrics. The final memo defended a 0.37 alarm threshold using cost tradeoffs and correctly localized the fault to the outer race via BPFO.
- Leakage-Free Feature Engineering
- Honest Held-Out Evaluation
- Physics-Based Fault Localization
- Cost-Based Decision Making
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