Operation Modal Analysis with WaveImage

This module can be used to analyze structures under stochastic or ambient excitation (e. g. wind, traffic), where a measurable excitation is complicated or impossible, e.g. structures are too small or too large. Operational Modal Analysis (OMA) is also known as ambient modal analysis, ambient vibration testing or output-only modal analysis. It uses the dynamic response of a structure on-site under its environmental conditions to determine its modal parameters (natural frequencies, mode shapes and damping).

Various time-based algorithms are available for the extraction of the modal parameters. The evaluation of the vibration analysis is possible without expert knowledge, since suitable evaluation parameters are automatically determined from the input data.

Fast and Automated Modal Analysis

  • Natural frequency and resonance
  • Damping
  • Mode shapes

Algorithms

State-of-the-art modal analysis algorithms in time and frequency domain for single and multiple setups

Frequency Domain:

  • Complex Mode Indicator Function (CMIF)
  • Operational Polyrefrence Least Squares Complex Frequency (Operational Poly-LSCF)

Time Domain:

  • Unweighted Principal Component (SSI*- UPC)
  • Principal Component (SSI*- PC)
  • Canonical Variate Analysis (SSI*- CVA)
  • Covariance Analysis (SSI*- COV)

*SSI = Stochastic Subspace Identification

Support of Multi-Setup

Supported strategies:

  • PoSER (Post Separate Estimation Re-scaling)
  • PoGER (Post Global Estimation Re-Scaling)
  • PreGER (Pre Global Estimation Re-Scaling)

Views

Different views for animation:

  • 3D geometry
  • 3D geometry + photo
  • Photo only

Different views for evaluation:

  • Complexity plot
  • Modal Assurance Criterion (2D and 3D)
  • Order traces like frequency, damping, frequency vs. damping and complexity

Methods

Order-Based:

  • Optimized and extreme clear stability chart with very high accuracy of physical modes and removed noise
  • Use of projection channels reduce the calculation overhead and guarantees high accuracy in modal parameter estimation
  • Projection channels can be found manually or fully automatic
  • Modal parameter estimation in time and frequency domain
  • Single or multiple test setups possible
  • Very fast estimation of big data models
  • Very limited user interaction is required

Non-Order-Based:

  • Automatic peak finding using artificial intelligence
  • No parameters required to find peaks
  • Very fast and memory save estimation
  • Single or multiple test setups possible
  • Use of projection channels reduce the calculation overhead and guarantees high accuracy in modal parameter estimation
  • Projection channels can be found manually or fully automatic
  • Global modal parameter estimation can be made manually or automatic

Comparison of Modes

  • Modal Assurance Criterion – MAC (2D and 3D)
  • Complexity plot
  • Comparison of the animations