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Wind Turbine Fault Diagnosis Assistant

Diagnose wind turbine faults from SCADA data and prioritize repairs

3.8(33 reviews)
500+ downloads
Updated Sep 2026
Verified SafeSecurity VerifiedThis skill was analyzed by our AI security scanner for harmful content including data exfiltration, system manipulation, credential theft, and prompt injection. No threats were detected.

What You Can Do

This skill transforms raw operational data into actionable fault diagnoses by analyzing SCADA parameter deviations, cross-referencing failure patterns, and synthesizing multiple data sources. You get structured problem statements with confidence levels, root cause hypotheses ranked by probability, and prioritized repair recommendations with estimated resource requirements—enabling rapid triage and minimizing downtime in critical situations.

Features

SCADA parameter deviation analysis

compares live readings against baseline behavior to identify abnormal patterns

Fault pattern matching

cross-references observed symptoms with known failure modes in wind turbine systems

Multi-source data synthesis

integrates SCADA logs, maintenance records, and field observations into coherent diagnoses

Root cause ranking

generates hypothesis list ordered by probability with supporting evidence

Severity assessment

flags safety-critical conditions requiring immediate escalation vs. scheduled maintenance

Repair prioritization

ranks recommended interventions by urgency and resource impact

Performance degradation tracking

detects yield loss and equipment degradation trends over time

Post-maintenance verification

validates repair effectiveness against baseline parameters

Example Output

Example 1: Gearbox Bearing Temperature Rise

Diagnosis: High-probability bearing degradation (confidence: 87%)

  • Root cause: Inadequate lubrication due to pump flow reduction
  • Supporting evidence: Oil pressure down 12%, bearing temp +8°C, vibration FFT shows 2.3× increase at bearing fault frequency
  • Severity: Schedule within 2 weeks; escalate if temp exceeds 95°C
  • Recommended action: Oil analysis + bearing inspection during next maintenance window

Example 2: Pitch System Anomaly

Diagnosis: Hydraulic pressure loss or pitch actuator stiction (confidence: 76%)

  • Root cause: Debris in hydraulic line or actuator seal degradation
  • Supporting evidence: Pitch response lag +2.5 sec, pressure oscillation ±5 bar, no active fault codes
  • Severity: Non-critical; investigate before blade loading increases
  • Recommended action: Flush hydraulic circuit; test pitch response with manual commands

What's Included

  • SKILL.md: Complete fault diagnosis instruction file
  • SCADA Parameter Baseline Template: Standard reference values for major wind turbine systems (generator, gearbox, pitch, cooling)
  • Fault Pattern Reference Matrix: Common failure modes mapped to symptom signatures and diagnostic indicators
  • Repair Priority Scoring Framework: Weighted criteria for urgency assessment (safety risk, yield impact, resource availability)
  • Field Report Checklist: Structured data collection template for technicians to feed into diagnosis workflow
  • Root Cause Analysis Worksheet: Template for documenting hypothesis development and evidence evaluation

Who It's For

  • Wind farm operations managers — rapid fault triage to coordinate technician dispatch
  • Predictive maintenance engineers — trend analysis and degradation pattern detection
  • Field service technicians — diagnostic support before site visits to reduce troubleshooting time
  • Control system engineers — SCADA anomaly interpretation and parameter drift investigation
  • Assets/reliability teams — post-repair verification and performance validation

Best For

  • Emergency fault diagnosis with limited field data (< 30 min response)
  • Yield loss investigation when root cause is unclear
  • Multi-alarm prioritization under simultaneous fault conditions
  • Developing failure mode detection (bearing temperature creep, vibration trends)
  • Performance baseline deviation tracking over weeks/months
  • Repair effectiveness validation after maintenance completion

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