AiVibeQuality, Reliability & Maintenance
Envelope Analysis (Demodulation)
Envelope analysis is a vibration signal processing technique that isolates repetitive impacts, such as those from bearing or gear defects, by filtering a high-frequency band, extracting its envelope and examining the spectrum of that envelope.
Impacts from a small defect excite high-frequency resonances of the bearing and machine structure. These responses repeat at the defect frequency but are weak compared with low-frequency vibration from unbalance or misalignment. Envelope analysis band-pass filters the signal around a resonance region, rectifies it and extracts the envelope, often with a Hilbert transform or a low-pass filter, and then computes the spectrum of that envelope. Peaks in the envelope spectrum appear at the repetition rates of the impacts, such as BPFO or BPFI, and their harmonics.
The technique is widely used to detect early rolling-element bearing damage, gear tooth faults and other impacting faults in motors, pumps, fans, gearboxes and spindles, often well before overall vibration levels change. Many portable analysers and online systems include envelope or demodulation functions, and related high-frequency techniques such as the shock pulse method are also used for bearing condition assessment.
Results depend on choosing a suitable filter band, and methods such as spectral kurtosis help select it automatically. Accelerometer mounting must transmit high frequencies, so stud or magnetic mounting on a clean, flat surface is preferred over handheld probes. Envelope spectra can also show peaks from electrical interference or other impacting sources, so findings should be confirmed with trend data and other techniques.
Key points
- Extracts repetitive impacts from high-frequency vibration.
- Filters a resonance band, takes the envelope and computes its spectrum.
- Detects early bearing and gear faults before overall levels rise.
- Filter band choice and sensor mounting strongly affect results.
Where AiVibe comes in
AiAmbA AI Factory use cases include predictive maintenance and visual inspection on textile, automotive and electronics lines. AiAmbA IoT normalises industrial signals from protocols such as OPC UA and MQTT, with driver availability confirmed per installation.
Explore AiVibe’s work in Quality, Reliability & Maintenance →