Selbstgesteuertes Projekt
Predictive Maintenance: Industrial ML for Fault Detection
Condition-Monitoring Engineer · KI / ML · September 2026
Eine ProoV-Fallstudie · Lernprojekt, kein Arbeitsverhältnis
Built an end-to-end rolling-bearing fault detector from vibration data: engineered RMS, kurtosis, crest factor, and envelope-spectrum defect-band energy; trained a compact depth-1 decision tree on training bearings only; and evaluated it on held-out bearings with reported catch-rate and false-alarm rate. The final memo justified a 0.42 alarm threshold using the student’s own cost numbers and correctly localized the fault to the outer race via the BPFO peak.
Bewertet nach
- Feature engineering (signal to honest numbers)25%
- Held-out evaluation (honest measurement)25%
- Cost-based threshold decision + memo25%
- Compact model + embedded-budget justification15%
- Plain-language explanation10%
Bestanden · Bestehensgrenze 60/100
Was herausstach6
- Computed envelope-spectrum energy around all four supplied defect frequencies and correctly identified BPFO as dominant
- Trained a depth-capped decision tree on training bearings only and stated depth and node count against the embedded budget
- Defended the alarm threshold with concrete miss-vs-false-alarm costs and tied the fault location to the 236.4 Hz BPFO peak
- Leakage-Free Feature Engineering
- Honest Held-Out Evaluation
- Physics-Based Fault Localization
Meine eingereichte Arbeit19 Aufgaben
11 Aufgaben · 6.4k Zeichen · Python · 8 Textantworten · 431 Wörter
- Initial Prediction50 Zeichen
- Load Plot Signal CodePython · 1.9k Zeichen
- Load Plot Signal205 Zeichen
- Example Rms WorkedPython · 697 Zeichen
- Time Features143 Zeichen
- Freq FeaturesPython · 1.2k Zeichen
- Fault Location239 Zeichen
- Train Classifier363 Zeichen
- Evaluation Heldout288 Zeichen
- Threshold Decision335 Zeichen
- Decision Memo1.0k Zeichen
- Initial Prediction6 Wörter
- Load Plot Signal Code163 Wörter
- Load Plot Signal15 Wörter
- Example Rms Worked72 Wörter
- Time Features10 Wörter
- Freq Features120 Wörter
- Fault Location14 Wörter
- Train Classifier31 Wörter
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