Rajat Mishra

Create your portfolio with ProoV
ProoV
DE Verified work portfolio

ProoV Portfolio

Rajat Mishra

View the ProoV leaderboard

Projects

Certified

Self-directed project

Predictive Maintenance: Industrial ML for Fault Detection

Condition-Monitoring Engineer · AI / ML · August 2026

86/ 100

A ProoV case study · educational project, not employment

Built an end-to-end rolling-bearing fault detector from vibration data: plotted and interpreted the faulty waveform, engineered RMS/kurtosis/crest and envelope-spectrum defect-band features, trained a compact depth-1 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 0.41 alarm threshold using the student’s own cost numbers and correctly localized the fault to the outer race via BPFO.

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
  • Used the provided envelope-spectrum helper and correctly found BPFO as the dominant defect band, matching an outer-race fault.
  • Trained a very small decision tree (depth 1, 3 nodes) on training bearings only, which fits the embedded-budget constraint.
  • Reported held-out catch-rate and false-alarm rate rather than evaluating on the training set.
  • Connected the threshold choice to explicit cost figures and stated the cracked ring in plain maintenance language.
  • Leakage-Free Feature Engineering
  • Honest Held-Out Evaluation
The work I submitted19 tasks

11 tasks · 6.9k characters · Python · 8 written answers · 536 words

  • Initial Prediction50 characters
  • Load Plot Signal CodePython · 1.8k characters
  • Load Plot Signal205 characters
  • Example Rms WorkedPython · 697 characters
  • Time Features143 characters
  • Freq FeaturesPython · 1.2k characters
  • Fault Location239 characters
  • Train ClassifierPython · 1.3k characters
  • Evaluation Heldout288 characters
  • Threshold Decision335 characters
  • Decision Memo697 characters
  • Initial Prediction6 words
  • Load Plot Signal Code163 words
  • Load Plot Signal15 words
  • Example Rms Worked72 words
  • Time Features10 words
  • Freq Features119 words
  • Fault Location14 words
  • Train Classifier137 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.

Verified certificateTamper-proof · issued by ProoV
1Project completed
1Verified certificate
86Average score
Create your portfolio with ProoV