Mohammed Imad Uddin Hameed

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Mohammed Imad Uddin Hameed

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Mohammed Imad Uddin Hameed

Metallurgical and Materials Engineering · Rajiv Gandhi University of Knowledge Technologies

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Projects

Certified

Self-directed project

Predictive Maintenance: Industrial ML for Fault Detection

Condition-Monitoring Engineer · AI / ML · August 2026

92/ 100

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-frequency features; trained a compact depth-capped decision tree on training bearings only; and evaluated it on held-out bearings with catch-rate and false-alarm metrics. The candidate also localized the fault to the outer race via BPFO dominance and justified an alarm threshold with explicit maintenance-cost tradeoffs.

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 the supplied BPFO/BPFI/BSF/FTF frequencies and correctly identified BPFO as dominant
  • Chose a shallow decision tree with stated depth 1 and 3 nodes, explicitly within the embedded budget
  • Reported held-out catch-rate and false-alarm rate rather than relying on training performance
  • Defended the alarm threshold with concrete euro costs and a plain-language explanation tied to the model's own numbers
  • Leakage-Free Feature Engineering
  • Honest Model Evaluation
The work I submitted20 tasks

12 tasks · 8.6k characters · Python · 8 written answers · 481 words

  • Initial Prediction62 characters
  • Example Load Plot HealthyPython · 860 characters
  • Load Plot Signal CodePython · 1.8k characters
  • Load Plot Signal205 characters
  • Example Rms WorkedPython · 698 characters
  • Time Features143 characters
  • Freq FeaturesPython · 1.1k characters
  • Fault Location239 characters
  • Train Classifier363 characters
  • Evaluation Heldout288 characters
  • Threshold Decision335 characters
  • Decision Memo2.5k characters
  • Initial Prediction9 words
  • Example Load Plot Healthy81 words
  • Load Plot Signal Code163 words
  • Load Plot Signal15 words
  • Example Rms Worked72 words
  • Time Features10 words
  • Freq Features117 words
  • Fault Location14 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
92Average score
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