Gear Fault Diagnosis

Gear Fault Diagnosis

Detect gear faults through spectral analysis of vibration signals, focusing on gear mesh frequency (GMF) harmonics, sidebands, and modulation patterns.

Prerequisite: The predictive-maintenance-mcp MCP server must be connected.

Background

Gear faults produce characteristic vibration patterns:

• Gear Mesh Frequency (GMF) = number_of_teeth x shaft_RPM / 60
• Healthy gears show GMF and low-level harmonics
• Faulty gears show increased GMF harmonics, sidebands at shaft speed, and broadband noise

Workflow

Step 1 — Signal Selection and Parameters

Load the signal with load_signal(...) or select from list_stored_signals().

Gather from the user:

• Shaft RPM (or shaft frequency in Hz)
• Number of teeth on the gear of interest
• Gear ratio (if analyzing a gear pair)

Calculate:

• GMF = teeth x RPM / 60
• Shaft frequency = RPM / 60

Step 2 — Statistical Screening

Call extract_features_from_signal(signal_id=...).

Gear fault indicators:

• Kurtosis > 3: impulsive content (tooth damage)
• Crest Factor > 5: localized damage
• RMS increase: overall vibration energy rise

Step 3 — FFT Analysis

Call analyze_fft(signal_id=...).

Inspect the spectrum for:

Pattern	Indicates
GMF with low harmonics, no sidebands	Normal gear operation
Increased GMF harmonics (2x, 3x, 4x GMF)	Gear wear or misalignment
Sidebands around GMF at shaft frequency spacing	Localized tooth damage
Broadband noise increase	Advanced wear or pitting
Ghost frequencies (non-harmonic peaks)	Manufacturing defects

Step 4 — Envelope Analysis (for Modulation)

Call analyze_envelope(signal_id=..., filter_low=..., filter_high=...).

Center the filter band around GMF or its harmonics to extract amplitude modulation patterns. Sidebands in the envelope spectrum at shaft frequency confirm gear fault modulation.

Step 5 — Advanced Spectral Analysis

Call compute_spectrogram_stft(signal_id=...) to check for time-varying patterns. Gear faults with localized damage show periodic energy bursts at the shaft rotation rate.

Call compute_power_spectral_density(signal_id=...) for a smoothed spectral view that reduces noise and highlights persistent gear mesh patterns.

Step 6 — ISO 20816-3 Severity

Call evaluate_iso_20816(signal_id=..., machine_group=..., support_type=...).

Report vibration zone and urgency level.

Step 7 — Diagnosis Summary

Present findings:

GEAR FAULT DIAGNOSIS
====================
Signal: {signal_id}
Gear Mesh Frequency: {gmf} Hz ({teeth} teeth x {rpm} RPM)

Spectral Findings:
  GMF amplitude: {value} — {normal/elevated/high}
  Harmonics: {count} significant harmonics detected
  Sidebands: {present/absent} at {shaft_freq} Hz spacing

Assessment: {diagnosis}
Confidence: {level}
ISO Zone: {zone}

Recommendation: {action}

Step 8 — Report Generation

Call generate_fft_report(signal_id=...) and optionally generate_diagnostic_report_docx(...).

Diagnosis Decision Table

GMF Level	Harmonics	Sidebands	Kurtosis	Diagnosis
Normal	1-2 harmonics	None	< 3	Healthy
Elevated	3+ harmonics	None	< 3	Wear / misalignment
High	Multiple	Present	3-6	Localized tooth damage
High	Many + broadband	Many	> 6	Advanced gear damage

Important Notes

• GMF calculation requires accurate tooth count and RPM
• Some gearboxes have multiple gear stages — analyze each separately
• Gear and bearing faults can coexist; if bearing frequencies are also present, recommend running the bearing-diagnosis skill as well
• Use cautious language for all diagnoses
• All processing is local — no data leaves the machine