| Feature | Description |
|---|---|
| Amplitude Spectrum | Represents the magnitude of different frequency components present in a signal, offering insights into its spectral characteristics. The amplitude spectrum is particularly valuable in applications requiring frequency-domain analysis, such as: • Vibration analysis • Signal classification tasks • Speech recognition • Mechanical fault detection using accelerometers • Gesture recognition and motion pattern analysis using IMU data • Structural health monitoring • Motor condition monitoring (identifying harmonics, imbalance, or wear) Its ability to reveal the underlying frequency structure of signals makes it an essential tool in modern signal processing and feature extraction workflows. |
| Spectral Centroid | Represents the center of mass of a spectrum and is closely associated with the perceived brightness of a signal. Typical applications are as follows: • Detection of mechanical wear or friction using vibration sensors • IMU-based motion pattern recognition (for example, differentiating smooth versus abrupt motion) • Structural health monitoring using accelerometers |
| Spectral Spread | Measures the dispersion of the spectrum around its centroid, calculated as the average deviation of the spectrum from its spectral centroid. It is commonly used in: • Vibration pattern characterization in industrial machines • Detecting structural looseness or resonant shifts • Classifying gestures with broad versus narrow frequency content on IMU sensors |
| Spectral Crest | Measures the peakiness or tonality of a signal's spectrum, calculated as the ratio of the maximum magnitude in the spectrum to the arithmetic mean. Typical applications are as follows: • Vibration-based fault detection (detecting sharp tonal peaks from defects) • Motor imbalance or misalignment detection using IMU data • Impact detection for accelerometers or gyroscopes |
| Spectral RMS | Measures the average energy of a signal in the frequency domain, providing valuable information about the spectral content and overall power of a signal. Typical applications are as follows: • Detecting abnormal increases in mechanical vibration energy • Monitoring load or stress variations using IMU sensors • Activity classification in wearables (walking, running, jumping) |