Vyshak Kadambur completed Predictive Maintenance: Industrial ML for Fault Detection

Built an end-to-end rolling-bearing fault detector from vibration data: visualized the faulty waveform, extracted time-domain and envelope-spectrum features, localized the fault to the outer race via BPFO, and trained a compact decision tree on training bearings only. Evaluated on held-out bearings with reported catch-rate and false-alarm rate, then defended a cost-based alarm threshold using the candidate’s own numbers in a maintenance memo.

• Leakage-Free Feature Engineering
• Honest Held-Out Evaluation
• Physics-Based Fault Localization
• Cost-Based Decision Making