Self-directed project
Predictive Maintenance: Industrial ML for Fault Detection
Condition-Monitoring Engineer · AI / ML · September 2026
A ProoV case study · educational project, not employment
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.
Graded against
- 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%
Passed · pass mark 60/100
What stood out6
- 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
The work I submitted19 tasks
11 tasks · 6.4k characters · Python · 8 written answers · 431 words
- Initial Prediction50 characters
- Load Plot Signal CodePython · 1.9k characters
- Load Plot Signal205 characters
- Example Rms WorkedPython · 697 characters
- Time Features143 characters
- Freq FeaturesPython · 1.2k characters
- Fault Location239 characters
- Train Classifier363 characters
- Evaluation Heldout288 characters
- Threshold Decision335 characters
- Decision Memo1.0k characters
- Initial Prediction6 words
- Load Plot Signal Code163 words
- Load Plot Signal15 words
- Example Rms Worked72 words
- Time Features10 words
- Freq Features120 words
- Fault Location14 words
- Train Classifier31 words
Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.