Aayush Bhuyan completed Predictive Maintenance: Industrial ML for Fault Detection

Built a working rolling-bearing fault detector end to end: visualized vibration data, engineered RMS/kurtosis and envelope-spectrum features at the supplied defect frequencies, and localized the fault to the outer race via BPFO. Trained a depth-capped decision tree on training bearings only, then evaluated it on held-out bearings with catch-rate and false-alarm metrics and justified a 0.43 alarm threshold using cost figures.

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