This module can be used to analyze structures that have been excited with a targeted and known function. The two most common types of excitation are impulse excitation (e.g. with the WaveHitMAX) and shaker excitation. Experimental modal analysis (EMA) determines the modal parameters (eigenfrequencies, mode shapes, and modal damping) of a given structure from measured response functions.

State-of-the-art algorithms are available to extract these modal parameters. Sectional extraction makes this possible even at high modal density.

The module allows the analysis of multiple input and multiple output measurements (SISO, SIMO, MISO, MIMO). Correlation with Finite Element Analysis (FEA) models is possible both visually and computationally (MAC comparison).

Even without expert knowledge, the analysis of vibration measurements succeeds, because suitable algorithms and their parameters can be determined automatically from the input data.

Fast and Automated Modal Analysis

  • Natural frequency and resonance
  • Damping
  • Mode shapes

State-of-the-art Modal Analysis Algorithms

in time and frequency domain for SISO, SIMO, MISO, MIMO measurements

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

Views and Visualisation

General

  • Driving point FRFs are marked separately for presentation
  • Coherence can be display if measured
  • Synthesized FRFs can be display
  • Interaction between geometry and shown measurement data

Different views for animation

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

     

    Different views for evaluation

    • Complexity plot
    • Modal assurance criterion (2D and 3D)
    • Order traces like frequency, damping, frequency vs. damping and complexity
    • Participation factors

    Methods

    Order-Based:

    • Optimized and extreme clear stability chart with very high accuracy of physical modes and removed noise
    • 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
    • Global modal parameter estimation can be made manually or automatic

    Comparison of calculated and imported modes

    • Modal assurance criterion (2D and 3D)
    • Complexity plot
    • Comparison of the animations