Example configurations

Structural vibration testing & structural health monitoring

Main sequence with three decomposition analyses.

What it is about
Station: Change Detection Simulation Category: Resonance testing & structural monitoring

Demonstrates signal decomposition methods for change detection in structural monitoring. A signal generator creates a synthetic time series from trend, periodic and noise components, which is decomposed by three methods and compared directly: singular spectrum analysis (SSA) separates trend, two periodic components and noise; Hilbert-Huang transform (HHT) and discrete wavelet transform (DWT) each extract the trend component. The trend components are additionally evaluated through an envelope.

The sequence in detail

Workflows in detail

  1. Structural Vibration Testing

    Main sequence with three decomposition analyses.

    Start → signal generator (time series with trend, periodicity, noise) → SSA analysis → HHT analysis → DWT analysis → end; error flow present.

  2. Singular Spectrum Analysis

    Complete decomposition through SSA.

    Characteristic start → SSA trend → SSA periodicity 1 → SSA periodicity 2 → SSA noise → envelope of the trend → characteristic end.

  3. Hilbert-Huang transform

    Trend extraction through HHT.

    Characteristic start → HHT trend → envelope → characteristic end.

  4. Discrete wavelet transform

    Trend extraction through DWT.

    Characteristic start → DWT trend → characteristic end.

Take it with you

Import through the SonicTC DbManager — individually or merged into an existing database.

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