NVHWind / chemical / steel predictive-maintenance providers
Envelope-Demodulation Bearing Fault Diagnosis
01
Pain Points
- !Early faults are buried in broadband vibration; the raw spectrum shows no inner/outer race, rolling-element, or cage signature.
- !The four characteristic frequencies must be computed on the spot from geometry and RPM — error-prone by hand.
- !"Outer race of fan #3 has failed" lacks a reproducible diagnostic path.
02
The Tinia Approach
High-frequency band-pass + Hilbert envelope + characteristic-frequency matching pinpoints the fault location and severity trend — reuse on a new model by changing only the geometry parameters.
Resonance-band band-passEnvelope demodulationEnvelope-spectrum FFTCharacteristic-frequency matchingLabel verification
03
Nodes Used
IIR Filteriir_filter
Resonance-band band-pass preprocessingEnvelope Demodulationenvelope_demod
Extract the modulation envelope via Hilbert transformFFT Spectrum Analysisfft_spectrum
Compute the envelope spectrumIndicator Mathindicator_math
Compute and match BPFO/BPFI/BSF/FTF frequenciesSpectrum Viewerspectrum_viewer
Label characteristic-frequency positions and verify harmonicsCore nodes; add or remove steps as needed for your data and standards — the node graph is always editable.
04
Expected Output
- Envelope spectrum + four characteristic-frequency markers + harmonic verification.
- Fault-location identification (outer race / inner race / rolling element / cage).
- Severity trend over time to support maintenance scheduling.
Reference Standards / Engineering PracticeAlgorithm standardization (no single mandatory standard)
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